How AI Mention Trackers Work: A Clear Guide to Understanding Visibility in Large Language Models

Artificial intelligence is becoming more deeply embedded in the way users search for, engage with, and consume information online. Businesses are now facing a new visibility frontier: large language models (LLMs) like ChatGPT, Claude, Google’s Gemini, and Perplexity. These AI tools are rapidly shifting how people discover brands and products, but there has long been a missing piece for marketers: how can you measure your brand’s presence across these tools?

Enter AI mention trackers—tools like Profound, Peec AI, and others that are helping brands figure out how often they appear in AI-generated answers. Think of them as the modern-day equivalent of media monitoring tools, but instead of scanning newspapers or websites, they scan what the AIs are “saying” about you. Let’s walk through exactly how these tools work, step by step, in simple and clear terms.

Step 1: Feeding Questions to AI Models

The first thing an AI mention tracker does is simulate real-world user queries. For example, if you sell coffee, it might generate prompts like:

  • “What are the best coffee brands for home brewing?”
  • “Which companies sell sustainable coffee beans?”

These questions are either preloaded by the tool or customized by the user. Then, the tool asks these questions to various AI platforms—ChatGPT, Claude, Perplexity, and others. These queries are sent using APIs or simulated browser sessions, mimicking the behavior of a real user.

To make the results more robust, the tool may vary how it phrases the questions, capturing a wider net of responses. This ensures the data reflects how real users might engage with AI tools.

Step 2: Collecting the AI’s Answers

Once the questions are submitted, the AI models reply with natural-language answers. The tracker collects all of these answers—a big pool of unstructured text. If the AI provides source citations or links (as Bing or Google often do), the tool grabs those too.

This phase is about capturing everything that the AI outputs, regardless of whether your brand appears yet.

Step 3: Detecting Brand Mentions

Now comes the scanning. The tool searches through each AI-generated answer looking for specific brand names, website URLs, or product terms. It checks to see if, for example, “Acme Coffee” or “acmecoffee.com” shows up in the text.

This is similar to a human pressing “Ctrl+F” and looking for their company’s name. The tool notes:

  • Where the mention appeared
  • How often it appeared
  • In what context (Was it a top recommendation? Just a mention in passing?)

If the brand doesn’t appear, that’s recorded too. These “non-mentions” are equally important because they show where the AI isn’t recognizing your brand.

Step 4: Counting and Aggregating Mentions

Counting and Aggregating Mentions

The tracker now tallies up the results across many queries and platforms. This helps quantify your brand’s visibility. You might learn that your brand appeared in:

  • 8 out of 20 questions on ChatGPT
  • 10 out of 20 on Google Gemini
  • Only 3 out of 20 on Bing Chat

These numbers are typically translated into metrics like “share of voice” (SOV) or mention frequency. Tools like Profound display this in an easy-to-read dashboard, comparing your visibility to your competitors.

Over time, this creates trend lines that show whether your brand’s AI visibility is improving or declining.

Step 5: Attributing Mentions to Sources

A crucial part of these tools is identifying why an AI mentioned your brand. In many cases, it’s because of external sources cited by the AI model. For example:

  • Bing Chat might footnote your brand with a link to a popular review site
  • Google’s AI Overviews might mention your company and cite your blog or Wikipedia

The tracking tool records these citations and links them to your mentions. This is called “citation analysis.” It helps you understand which articles, websites, or publications are fueling your AI visibility.

When an AI doesn’t mention you but mentions a competitor, these tools can also highlight what sources were cited for them. This gives you ideas about where you might need more coverage.

Step 6: Presenting the Results

Presenting the Results

All of this data gets organized into a simple dashboard. It might tell you:

  • Your brand was mentioned in 40% of answers about “best coffee brands” on ChatGPT this month
  • That’s up from 30% the month before
  • The most frequently cited source was HomeBarista.com
  • Competitor JavaWorld appeared more often than you on Google SGE

Some tools also analyze sentiment: whether the AI’s tone was positive, neutral, or negative about your brand. While more advanced, this adds another layer to understanding your visibility.

A Real-Life Example: Acme Coffee

Imagine you run a fictional brand called Acme Coffee. You want to know if AI tools are recommending you when people ask about coffee.

  1. The tracker sends prompts like “What are the best coffee brands?” to ChatGPT, Claude, Google Gemini, and Bing Chat.
  2. ChatGPT responds with: “Some great coffee brands are Acme Coffee, BeanCo, and JavaWorld.” The tool flags that Acme was mentioned.
  3. Google’s AI says: “According to HomeBarista.com, Acme Coffee roasts top-tier beans.” The tool notes the mention and attributes the source.
  4. Bing Chat doesn’t mention Acme at all but includes JavaWorld. That’s also important intel.

After querying multiple questions and platforms, the tracker produces a report:

  • Acme was mentioned in 7 out of 10 queries on ChatGPT
  • 5 out of 10 on Google Gemini
  • 3 out of 10 on Bing Chat
  • Most Acme mentions cited HomeBarista.com
  • JavaWorld beat Acme by 2 mentions across the board

Tools Like Ahrefs Add Another Layer

Tools Like Ahrefs Add Another Layer

Some platforms, like Ahrefs, take a slightly different but powerful approach. Rather than running queries in real time, Ahrefs leverages a vast existing database of AI responses and questions. You can type in a brand name or topic like “sneakers,” and instantly see a list of relevant queries and AI answers that reference the topic.

This lets you:

  • Identify competitor gaps (queries where your competitors show up but you don’t)
  • Discover new topic opportunities (queries you never thought of that relate to your niche)

This retrospective approach complements real-time trackers like Profound or Peec AI by giving you a broader strategic view.

Tracking LLM Traffic in GA4: Why It Matters

AI visibility isn’t just theoretical. Brands are already seeing meaningful traffic driven by AI tools. Tracking this traffic in Google Analytics 4 (GA4) is now essential.

While Google Search Console still blends AI Overview and AI Mode traffic with regular search, GA4 gives you tools to segment this data more precisely.

Two Main Tracking Approaches:

  1. GA4 Explore Reports:
    • Create a session segment using a custom regex filter to capture traffic from AI sources like ChatGPT, OpenAI, Copilot, Gemini, Perplexity, etc.
    • Visualize this data with line graphs, bar charts, or tables.
  2. Looker Studio Reports:
    • For detailed reports: Create a new channel group in GA4 for AI traffic.
    • For quicker views: Use the same regex filter in your Looker Studio tables and charts.

These dashboards let you:

  • Track how much traffic is coming from AI tools
  • See which pages are being visited from AI answers
  • Understand whether your AI visibility is translating into real engagement

Final Thoughts: Why This Matters

The future of search is increasingly conversational and AI-driven. Tools like Profound, Peec AI, and Ahrefs help marketers stay ahead by answering this crucial question:

“Are the AIs talking about me?”

If they are, great—you can double down on what’s working. If not, you can take action to increase visibility by improving the content on sites that AIs pull from.

AI mention trackers give marketers, PR pros, and SEOs a crucial lens into how modern algorithms perceive and recommend their brands. By bridging the gap between traditional SEO metrics and AI-powered search behaviors, these tools ensure your strategy remains both measurable and forward-looking.

Start tracking now, and you’ll not only see how often you appear in the AI conversation, you’ll start shaping it.

The New State of Search in 2025 and Beyond: Optimizing for AI Mode and LLM Discovery

If you’ve felt whiplash from Google’s nonstop updates: AI Overviews, generative snippets, and now the full rollout of AI Mode into core results, you’re not imagining it. Search is undergoing its most radical transformation since the birth of PageRank. And the implications extend far beyond Google. In a world where LLMs like ChatGPT, Perplexity, and Claude are actively retrieving, reasoning, and rewriting content, visibility is no longer measured in blue links.

In this guide, you’ll understand how AI Mode works under the hood, what Google recommends explicitly (and what it doesn’t say out loud), and how to structure your content for retrieval augmented generation(RAG), across Google and the new class of LLM-native search engines.

1. From “Ten Blue Links” to a Web of AI Summaries

For decades, SEO meant chasing organic rankings. But in 2025, users expect a different experience: conversational, multimodal, and personalized. Google’s AI Mode, which rolled out U.S.-wide on May 20, 2025, doesn’t just augment results, it replaces traditional listings with AI-generated summaries that quote from multiple sources simultaneously.

This is not a Google-only story. Platforms like ChatGPT, Perplexity, and Gemini also synthesize content from across the web, using similar pipelines: chunking, embedding, retrieval, reranking, and LLM generation. Your content might be cited without ever earning a click, or worse, it may not be retrieved at all if it’s not semantically aligned.

AI Mode’s secret weapon is deep personalization: Google fuses data from Gmail, Calendar, Chrome, Maps, and YouTube to tailor summaries. The shift is clear: we’ve moved from “optimize for keywords” to “optimize for meaning.”

2. Google’s AI Mode: The Stack That Writes the Answers

Google’s AI Mode: The Stack That Writes the Answers

To demystify how your content is selected and quoted in AI Mode, here’s a breakdown of Google’s layered system, most of which is mirrored by other LLMs and is what RAG consists of:

LayerRoleHow it Works
BERT / T5Linguistic interpretersTranslate queries to understand intent and direction.
Vector EmbeddingsSemantic mapmakersPlace ideas in conceptual space; “jaguar” the car ≠ “jaguar” the animal.
ScaNN RetrievalUltra-fast content locatorsFetch the most semantically relevant chunks in milliseconds.
Hybrid RerankersRational judgesCombine keyword scores and semantic scores; pick the most coherent passage.
Gemini Flash/ProCreative summarizersCompose a humanlike response from many retrieved sources.

Google, OpenAI, and Perplexity all use a variation of this stack. The question is no longer, “Is my page ranking?”. It’s, “Is my content retrievable, relevant, and reusable in an AI summary?”

3. The AI Optimization Imperative: What Google (and Others) Recommend

Google’s own blueprint, published May 21, 2025, provides clarity, but with nuance. These principles aren’t just best practices for Google—they apply to any LLM-powered platform that retrieves and assembles answers.

✅ Do:

  • Create original, human-centric content – Generic rewrites vanish from summaries. Depth wins.
  • Ensure crawlability – Don’t accidentally block Google-Extended, GeminiBot, or GPTBot.
  • Optimize structure for readability – Use headings, schema, and direct answers.
  • Include rich media – Images and videos can appear in multimodal answers.
  • Use preview controls wisely – Overrestrictive snippet settings can remove you entirely.
  • Verify your structured data – If it misaligns with visible content, it may be ignored or penalized.

❌ Don’t:

  • Chase AI placement hacks – Prompt templates change daily.
  • Stuff with synonyms – Semantic distance matters more than density.
  • Block LLMs for “content protection” – You’ll be excluded from the answer graph.

Note: Traditional SERPs and classic SEO are not obsolete—but they are rapidly shrinking in importance. Many users will still browse organic results, especially for transactional queries. However, AI-generated responses, smart assistants, and multimodal summaries are becoming the default interface for information retrieval. SERPs now represent just one channel among many in the optimization landscape.

4. An AI-First Optimization Framework

An AI-First Optimization Framework

Below is the exact workflow our agency uses when auditing sites for AI Mode and LLM optimization. We’ve even specified tools that you can use at each stage purely for the education of the reader. This is not an endorsement and we have no affiliation with any of these brands:

Open the gates to AI crawlers

  • Audit robots.txt and server logs for Google-Extended, Google-LLM, GeminiBot, and GPTBot.
  • Remove legacy disallow rules on JS, CSS, or /api/ endpoints; AI models fetch full render trees.

Tool: logflare.app, openai.com/gptbot

Generate question-driven topic clusters to mimic “Query Fan-Out”

  • De-duplicate and cluster by user intent (how, why, cost, vs).
  • Prioritize clusters based on traffic opportunity and business value.

Tool: alsoasked.com

Draft semantically rich content

  • Begin each section with a concise 1–2 sentence direct answer (<80 words).
  • Support with original research, media, expert commentary.
  • Use H2/H3 subheads as natural language questions.

Tool: surferseo.com

Validate vector-level alignment

  • Embed draft paragraphs using OpenAI or TensorFlow.
  • Compute cosine similarity between your content and target queries.
  • Iterate until ≥ 0.85 similarity is achieved.

Tool: Screaming Frog SEO Spider v22.0

Monitor AI citations & mentions

  • Track when your URL appears in Google AI Overviews, Perplexity, ChatGPT, etc.
  • Set alerts for declines; rework and refresh passages accordingly.

Tool: tryprofound.com

5. Case Study Snapshot: A Cross-LLM Win

A health brand published an article titled “Are stainless steel bottles safe during pregnancy?” using this methodology:

  • Opened with a 70-word evidence-based answer.
  • Embedded lab-test data (image) and a 45-second expert video.
  • Verified 0.91 cosine similarity with key intent queries.
  • Appeared in Google AI Mode, Perplexity responses, and ChatGPT citations.
  • Result: 28% increase in time-on-site and a 17% higher cart-to-visit rate from AI referrals.

6. FAQ: What This Means for SEO

Is SEO dead?

No—but it’s evolving. Optimization now includes vector alignment, retrievability, and AI authority.

Do I need new pages just for AI Mode?
Not at all. Structuring your existing content with questions and direct answers serves both AI and human audiences.

What metrics matter now?
Track AI citations, retrieval frequency, and embedding scores. Legacy KPIs like CTR and bounce rate are secondary in zero-click environments.

7. Action Checklist (Print This)

✅ Allow GPTBot, GeminiBot, Google-Extended
✅ Refresh content clusters quarterly
✅ Lead each H2 with a sub-100-word answer
✅ Verify cosine similarity ≥ 0.85
✅ Track citations across ChatGPT, Perplexity, Google
✅ Validate structured data and crawlability
✅ Optimize for conversions and engagement—not vanity metrics

8. Final Thoughts

The AI era isn’t on the horizon, it’s here. AI Mode is becoming the standard lens for Google Search, and LLM-native discovery platforms are competing directly for user attention. Success now means thinking like a retrieval engine, not just a rank chaser.

Ready to thrive in this new landscape? Start with our AI Optimization Checklist, then audit your five highest-traffic pages using LLM-aware tools.

The future of search rewards those who are findable, quotable, and semantically aligned.

Why Is ROAS No Longer Enough in Google Ads? Here’s What to Do Instead

The world of Google Ads is changing. While ROAS—Return on Ad Spend—has been the go-to performance metric for years, savvy advertisers are now realizing its limitations. ROAS gives a narrow view of campaign efficiency, but it doesn’t tell the full story when it comes to profit, scale, or long-term growth. Today’s smart marketers are moving beyond this metric to embrace outcome-based strategies rooted in actual business value.

Key Takeaways

  • ROAS often masks the true profitability of campaigns
  • Smart Bidding now prioritizes real business results
  • Demand Gen campaigns reach customers across YouTube, Gmail, and Discover
  • AI is powering not just bidding—but creative and insights too
  • First-party data is now a strategic advantage
  • Strategic scaling wins over sudden budget spikes

Detailed Guide

What’s new in Google Ads?

Google has made major updates to streamline and empower campaign performance. Smart Bidding has been simplified—you now choose “Maximize Conversions” with optional Target CPA, or “Maximize Conversion Value” with optional Target ROAS. This means you’re optimizing for actual results, not micromanaging bid settings.

Demand Gen campaigns are another big leap. They replace Video Action campaigns and run across YouTube, Discover, and Gmail. These formats are built for both brand engagement and conversions, making them ideal for full-funnel strategies. AI also now supports you at every step—from writing headlines to discovering new keywords—giving you predictive power that helps you stay ahead of trends.

Why is ROAS misleading?

ROAS feels like a clear performance metric, but it’s often deceptive. Imagine two campaigns:

  • One spends $1,000/day at 2× ROAS, generating $30,000/month in profit
  • Another spends $100/day at 5× ROAS, but only nets $12,000/month

Which would you choose? The 5× ROAS might look better on paper, but the first campaign brings in over twice the profit. ROAS ignores volume and real economic impact. And that’s why it’s no longer enough.

What should you measure instead?

Start tracking POAS—Profit on Ad Spend. Unlike ROAS, POAS factors in cost of goods sold, transaction fees, and overhead. This gives you a more accurate view of how your ads are really performing. You can even push this data back into Google Ads using server-side tracking, helping the algorithm optimize based on what actually drives profit.

How should you think about attribution?

The buyer’s journey is no longer a straight line. People interact with your brand across devices and platforms before they buy. That’s why last-click attribution is outdated. Modern advertisers are moving to data-driven attribution through GA4. This lets you understand which touchpoints actually influence conversions and make better decisions across your entire funnel.

How do you use first-party data effectively?

With third-party cookies on the way out, your own customer data is more valuable than ever. Tap into your CRM and purchase history to build audience segments based on real buyer behavior. Then, use Google’s Customer Match and Enhanced Conversions to connect this data to your campaigns. This not only improves targeting but also boosts conversion rates significantly.

How important is creative strategy now?

With AI doing more of the heavy lifting behind the scenes, creative is one of your biggest competitive advantages. Dynamic creative testing lets you see which copy, visuals, and CTAs resonate with different segments. Messaging should be tailored—what works for cold leads probably won’t work for warm retargeting audiences. Winning ad creatives are intentional, not generic.

What role do Demand Gen campaigns play?

Demand Gen campaigns give you a unique way to build both brand and performance. They’re immersive, visual, and appear where people are most engaged—YouTube, Gmail, and Discover. These formats are great for building top-of-funnel awareness and generating remarketing audiences that are more likely to convert later. They’re not just about clicks; they’re about presence.

How do you scale effectively?

Many brands rush to increase budgets once they see success—but that can backfire. Controlled scaling is a smarter approach. Increase your ad budget by no more than 20% every 3–5 days. Use Google’s campaign experiments to test changes before committing fully. Try new geos or devices to tap into fresh audiences. Smart scaling is strategic, not reactive.

A Simple Comparison That Says It All

Let’s look at two scenarios:

Scenario A

  • 2× ROAS
  • $1,000/day ad spend
  • $60,000 monthly revenue
  • 50% margin = $30,000 profit

Scenario B

  • 5× ROAS
  • $100/day ad spend
  • $15,000 monthly revenue
  • 80% margin = $12,000 profit

Even with a lower ROAS, Scenario A generates more than twice the profit. That’s why volume and context matter far more than a single efficiency ratio.

FAQs

What does POAS mean in digital advertising?
POAS stands for Profit on Ad Spend. It’s a smarter metric that factors in your costs to reveal true campaign profitability.

How do I implement POAS in Google Ads?
Use server-side tracking or offline conversion uploads to send profit-per-transaction data back into Google Ads for better optimization.

Are Demand Gen campaigns worth it?
Yes. They’re highly effective for reaching new users and warming them up for conversion with immersive, cross-channel engagement.

Can I still scale if I have a small budget?
Absolutely. Just scale slowly and watch key metrics closely. Start with controlled experiments before rolling changes out broadly.

Checklist

  • Move from ROAS to POAS for better insights
  • Simplify Smart Bidding strategy
  • Launch a Demand Gen campaign for top-of-funnel reach
  • Sync your CRM data using Customer Match
  • Test creative variations regularly
  • Use GA4 to move beyond last-click attribution
  • Scale budget in controlled, data-driven steps

Final Thoughts

Google Ads success today requires more than chasing high ROAS. It requires thinking strategically—measuring profit, understanding the customer journey, and scaling sustainably. Automation has taken care of the mechanics. Now, your job is to align data, creative, and business outcomes. When you focus on the metrics that actually drive growth, you’re not just managing campaigns—you’re building a business.

Forget vanity metrics. Focus on real profitability. Your bottom line will thank you.

How do modern AI search engines and LLMs operate and how do you optimize for them?

This isn’t 2015 anymore, yet some SEO “experts” are still clinging to tactics like they’re waiting for Windows 7 to make a comeback. Modern AI-powered search engines and large language models (LLMs) leverage Retrieval-Augmented Generation (RAG) to combine external data retrieval with text generation, ensuring answers are both current and contextually accurate. By performing a real-time search of trusted documents before crafting a response, these systems mitigate outdated training data and “hallucinations.” To optimize for them, create clear, structured content with up-to-date citations, conversational Q&A headings, and appropriate schema markup, so AI retrieval steps can easily identify and quote your material.

Key Takeaways

      • RAG enables AI to fetch and ground answers in fresh, external sources.

      • Structured Q&A headings and bullet points improve AI snippet retrieval.

      • Embedding authoritative, date-stamped references boosts trust signals.

      • Conversational phrasing and varied keywords aid vector-based matching.

      • Schema markup (FAQPage, HowTo) helps AI isolate self-contained snippets.

      • Off-page promotion can still surface in AI searches.

      • Optimizing content for RAG-driven AI results increases probability to appear in AI summaries and chatbot responses, giving you traffic that static search rankings might miss.

    Detailed Guide

    What is Retrieval-Augmented Generation (RAG) in simple terms?

    retrieval augmented generation

    Retrieval-Augmented Generation (RAG) is a hybrid AI workflow that enhances language models by letting them “look up” relevant documents at query time, rather than relying solely on what they learned during pretraining. Imagine asking a librarian to fetch the latest journal article before answering your question; RAG works similarly. Except this librarian is more like Alexa or Siri than your stereotypical Miss Finster.

    When you submit a query, the system first searches an external data source, such as a website index, a private knowledge base, or a specialized dataset of academic papers, for pertinent passages. Then, it feeds those retrieved snippets into the LLM as additional context, guiding the generative process so the answer is grounded in factual, up-to-date material. This approach addresses two major limitations of standard LLMs: information cutoff dates and the risk of “hallucinations,” where the model invents plausible-sounding but incorrect details.

    How does the retrieval phase work?

        1. User Query Submission
          You ask a question—e.g., “What are the 2025 tax deadlines for small businesses in Texas?” The RAG-enabled system takes this natural-language query as input.

        1. External Search
          Instead of directly generating an answer from pretraining data, the system performs a search against an external document collection, which could be a public web index, a company’s internal file repository, or a specialized dataset of academic papers (AWS, 2024; WEKA, 2025).

        1. Result Ranking
          Retrieved documents or text snippets are ranked by relevance using vector similarity, which transforms both the query and documents into numerical embeddings, or traditional keyword-based matching. The top N results (often broken into smaller “chunks” of text) are selected based on how closely they align with the user’s question.

        1. Outcome
          At the end of this phase, the system holds a set of highly relevant, often date-stamped passages that directly address the query.

      How does the augmentation and generation phase work?

          1. Context Assembly

        The RAG engine takes the top-ranked snippets—sometimes as short as a few sentences each—and concatenates them with the original user query. This assembled context is fed into the LLM.

            1. Guided Response Generation

          Rather than “freewriting” from its pretraining knowledge, the LLM now “reads” the assembled context and composes an answer that weaves together facts from the retrieved snippets with its own linguistic patterns. It essentially uses the retrieved passages as anchors, ensuring that every factual statement can be traced back to a specific external source.

              1. Optional Citation Insertion

            Some RAG implementations explicitly insert inline citations or footnotes, indicating which document or page each fact originates from. This enhances transparency and credibility, especially in domains like healthcare or legal research.

                1. Outcome

              The final output is a coherent, conversational response that is both fluent and verifiably sourced—reducing the likelihood of “hallucinations”.

              Why does RAG matter?

                  • Accuracy and Currency

                Because RAG fetches fresh data at query time, it can provide up-to-the-minute answers—even if the underlying LLM was last trained months or years ago. For example, a healthcare AI using RAG can retrieve the latest CDC guidelines before generating a recommendation, rather than relying on outdated training data.

                    • Reduced Hallucinations

                  By grounding responses in concrete, external sources, RAG dramatically lowers the risk of fabricated or misleading information. When users see inline citations, trust in AI-generated answers increases.

                      • Domain Specialization

                    Organizations can connect RAG systems to highly specialized knowledge bases—like a law firm’s case archives or a manufacturer’s product specs—without retraining the LLM. The AI becomes an expert in that domain simply by accessing the right repository at query time.

                        • Cost Efficiency

                      Instead of fine-tuning a massive LLM every time new information is added, you update the external datastore. This “decoupling” of model training from content updates is faster, cheaper, and more scalable—especially for companies that produce time-sensitive reports or whitepapers.

                          • Competitive Differentiation

                        As Google’s “AI Mode” is rolled out on a more massive scale, organizations that optimize for RAG-driven visibility gain a strategic edge. Their content is more likely to be surfaced in AI-generated summaries and chatbot answers, capturing traffic that might otherwise bypass static search engine results.

                        How to optimize content for RAG-driven AI search engines?

                        Google EEAT

                        Optimizing for RAG workflows means ensuring your content is structured, authoritative, and easy for retrieval algorithms to pinpoint. Below are actionable tactics:

                        1. Craft Clear, Structured, Answer-Focused Content

                        AI retrieval steps look for self-contained “snippets” that directly match user queries. Use semantic headings for primary sections so AI bots can isolate exact sections to quote. Begin each section with a concise answer.

                        For example:

                        How to File Sales Tax in California (2025 Update)

                        As of June 2025, all California small businesses must file sales tax returns by the 15th of each month. Refer to the California Department of Tax and Fee Administration website for exact forms.

                            • Use bullet lists and numbered steps for procedures to enhance snippet eligibility.

                            • Include a “TL;DR” summary at the top of long articles so RAG systems can grab that concise overview.

                          2. Embed Up-to-Date, Authoritative References

                          RAG systems ground their output in trusted documents. Pages that cite reputable, recent sources—such as government websites, peer-reviewed journals, or industry white papers—signal higher trustworthiness.

                              • Link to the latest guidelines or studies with a clear “Last Updated” date.

                              • Regularly audit and update publication dates to maintain freshness, benefiting both human readers and AI bots.

                            Example:
                            “According to the CDC’s May 2025 update on COVID-19 guidelines, mask mandates for healthcare workers in high-risk settings remain in effect (CDC, May 2025).”

                            3. Use Conversational Phrasing and Natural-Language Keywords

                            RAG retrieval often relies on vector-based similarity, matching semantic meaning rather than exact keywords. Write headings as questions users would ask—e.g., “What Are the 2025 Tax Deadlines for Freelancers in Texas?”—and follow with an immediate, concise answer.

                                • Include synonyms and related terms, such as “self-employed tax due dates” and “independent contractor tax deadlines,” to create multiple semantic entry points.

                                • Adopt a conversational tone so your content aligns with how AI systems interpret queries, boosting retrieval probability.

                              4. Leverage Schema Markup and FAQ/HowTo Blocks

                              Structured data markup—like FAQ Page or How To schema—helps AI crawlers precisely identify Q&A pairs and step-by-step instructions.

                                  • Wrap each Q&A pair in FAQ Page JSON-LD so RAG systems know these are self-contained snippets.

                                  • Use How To schema for multi-step guides, clearly delineating each step.

                                When Google’s AI Mode or other RAG-enabled platforms crawl your page, they can directly parse these structured blocks without scanning raw text.

                                5. Build Topical Authority and Maintain a Clean Technical Foundation

                                RAG systems prefer content from authoritative domains with strong topical clusters.

                                    • Publish comprehensive guides that interlink subtopics, demonstrating subject-matter depth.

                                    • Acquire backlinks from reputable industry publications—these act as trust signals in both traditional SEO and AI retrieval scoring.

                                    • Optimize technical SEO: ensure fast page load times, mobile responsiveness, secure HTTPS hosting, and accurate XML sitemaps so crawlers can index every relevant page.

                                  Tip: Use tools like Google Search Console to verify your sitemap and crawling status. If pages are excluded, AI retrieval systems won’t be able to find your snippets, regardless of content quality.

                                  6. Monitor and Adapt to AI Search Analytics

                                  Once your content is live, track AI-driven search performance via analytics platforms that show which snippets are being cited in chatbot outputs or AI summaries.

                                      • Review query logs to identify gaps and update content accordingly.

                                      • Refresh your knowledge base and schema markup periodically to keep pace with algorithmic changes.

                                    By treating optimization as an ongoing process rather than a one-time project, you ensure continual visibility in evolving RAG-driven ecosystems.

                                    7. Incorporate Off-Page SEO And PR Tactics for AI Visibility

                                    Traditional digital PR often promoted press releases, link-building or aggressive directory submissions. In certain AI search contexts, off-page tactics, like creating press releases or being cited on article directories, can cause RAG systems to index multiple instances of your content, increasing the likelihood of snippet selection.

                                    In my short YouTube video, I demonstrate how these tactics, some of which may be called “spammy”, can boost visibility in AI-based searches by flooding the retrieval index with relevant signals. While this approach carries risks in traditional SERPs, it can yield surprisingly effective results in AI-driven environments—so long as you monitor for negative user feedback or credibility issues.

                                    FAQs

                                    What is the difference between RAG and a standard LLM response?

                                    A standard LLM generates answers based solely on its pretraining data, which may be outdated if trained months ago. RAG, by contrast, performs a real-time search of external documents before generating an answer, ensuring the information is up-to-date and grounded in factual sources.

                                    Can I use RAG to search proprietary company files?

                                    Yes. By connecting a RAG-enabled system to your internal knowledge base—such as a SharePoint repository or a private document store—your organization can get highly specialized answers rooted in proprietary data without retraining the entire model.

                                    How do schema markup and structured data help AI retrieval?

                                    Schema markup like FAQ Page or How To tells AI crawlers exactly where Q&A pairs and step-by-step instructions begin and end, so retrieval engines can extract self-contained snippets without scanning the entire page. This increases the chances of your content being quoted verbatim in AI-generated summaries.

                                    Checklist

                                        • Identify and segment core Q&A snippets with clear semantic headings.

                                        • Embed date-stamped, authoritative citations (e.g., government or peer-reviewed).

                                        • Use conversational, question-style headings and varied synonyms.

                                        • Apply FAQ Page or How To schema markup around structured content.

                                        • Ensure fast load times, mobile optimization, and valid XML sitemaps.

                                        • Monitor AI search analytics to track snippet performance and update.

                                        • Experiment with off-page snippet postings; measure AI retrieval impact.

                                      Brief Summary and Conclusion

                                      Modern AI search engines and LLMs harness RAG workflows to merge external data retrieval with text generation, often producing answers that are highly accurate and current. By structuring content with clear semantic headings, embedding up-to-date citations, using natural-language Q&A phrasing, and applying FAQ Page or How To schema, you make it easier for AI retrieval to spot—and quote—your material without resorting to a virtual game of hide-and-seek. 

                                      Building topical authority, maintaining strong technical SEO, and even testing off-page snippet tactics can further boost your visibility in AI-driven searches. As AI search evolves, continually monitoring and adapting your strategy will be crucial for long-term success in the RAG-powered landscape.

                                      How do you optimize for Google’s new AI‑Mode answer summaries?

                                      Google now runs two separate generative‑AI surfaces inside Search: AI Overviews (a quick snapshot embedded in the classic results page) and AI‑Mode (a standalone, Gemini‑powered tab that behaves more like a research assistant). To earn citations in either, you still need strong ranking signals, iron‑clad E‑E‑A‑T and snippet‑ready prose, yet the tactics differ enough that you must optimise for both layers.

                                      Key Takeaways

                                      • AI OverviewsAI‑Mode. Overviews are inline snapshots; AI‑Mode is an opt‑in, dedicated search mode with deeper follow‑ups.
                                      • Overviews appear automatically when Google’s systems deem a query complex enough and safe; AI‑Mode is user‑initiated via a new AI tab.
                                      • Ranking top‑10 still matters—Overviews pull from high‑ranking, verified documents first.
                                      • Put a 60‑–80‑word hero answer under every H1 to maximise extractability.
                                      • E‑E‑A‑T + freshness remains the admission ticket for both layers.
                                      • Expect CTR to fall on Overview queries; offset with branding and lead magnets.

                                      Detailed Guide

                                      1. How do AI Overviews and AI‑Mode actually differ in 2025?

                                      Feature AI Overviews (inline) AI‑Mode (standalone)
                                      Launch timeline US rollout May 14 2024 → 100+ countries Oct 2024  US mass rollout May 20 2025 after Labs testing 
                                      Interface Appears above organic links inside standard SERP; collapsible; cites sources as chips Separate AI tab or toggle; full‑screen conversational UI; shows citations plus follow‑up prompts
                                      Use‑case Quick snapshot for moderately complex “how/why” questions Deep research, multi‑step planning, agentic tasks (e.g., buying tickets, data comparisons)
                                      Trigger Automatic—requires query to meet content‑safety + complexity thresholds Manual—user selects AI‑Mode; no popularity threshold
                                      Model Gemini 2.x tuned for latency Custom Gemini 2.5 with query fan‑out + Deep Search

                                      Why it matters: Overviews reward concise clarity; AI‑Mode rewards depth and interactivity.Optimise pages to satisfy both in one pass: lead with a distilled answer, then dive deep.

                                      How do AI Overviews and AI‑Mode actually differ in 2025

                                      2. When does Google show an AI Overview?

                                      Google has never published exact numbers, but data from SE Ranking and Search Engine Land suggest that queries need both sufficient search volume and a level of informational complexity.

                                      Guideline: Pages that already rank for queries with ≥100 monthly US impressions and 8‑plus words are far more likely to trigger an Overview.

                                      What This Means for SEO & Content Strategy

                                      SEO Moves

                                      1. Track impression‑heavy question keywords in Search Console.
                                      2. Consolidate overlapping articles—one URL per FAQ.
                                      3. Refresh answers quarterly to keep Overview eligibility.

                                      3. Crafting the hero answer—your 80‑word golden ticket

                                      A well‑formed hero paragraph can surface in both Overviews and the first AI‑Mode answer.

                                      • Length: 60–80 words, two sentences max.
                                      • Structure: statement → key fact → source cue (stat/name).
                                      • Branding: mention brand once in first clause.
                                      • Location: immediately after H1, above any images or ads.

                                      Copy hack: Draft two variants (60 w & 80 w) and alternate every 14 days to compare CTR. 

                                      4. Two‑phase summarisation still underpins both layers

                                      Google’s 2024 patent describes an espresso (fast) and slow‑brew (deep) retrieval loop Overviews rely mostly on espresso; AI‑Mode can wait for slow‑brew and even expand with Deep Search, issuing hundreds of sub‑queries.

                                      5. Verification signals—earning the invite

                                      Both systems filter the candidate set to verified documents before prompting the model. Signals include:

                                      1. Authorship credentials with professional links.
                                      2. Citations to primary research (government, peer‑reviewed, corporate filings).
                                      3. Structured dataArticle, FAQPage, HowTo, FactCheck.
                                      4. Fresh timestamps and frequent updates for YMYL topics.
                                      5. Fast Core Web Vitals (LCP < 2.5 s; INP < 200 ms).

                                      6. Snippet engineering—teaching robots to skim

                                      Robots skim like distracted humans. Help them:

                                      • ≤ 3‑sentence paragraphs; no walls of text.
                                      • Bullet or numbered lists for steps.
                                      • Definition call‑outs (> blockquote or styled div).
                                      • Question‑form headings to mirror Google’s reformulation: “How does…”

                                      7. Technical hygiene—speed still kills eligibility

                                      Even the smartest model aborts slow pages:

                                      • LCP < 2.5 s (espresso cut‑off).
                                      • INP < 200 ms.
                                      • Serve images in AVIF/WebP and lazy‑load below the fold.

                                      8. Branding inside the snippet—CTR insurance

                                      Because Overviews often satisfy intent without a click, brand recall is your safety net:

                                      1. Put brand in the first 50 characters of <title>.
                                      2. Use a distinctive favicon.
                                      3. Embed a next‑step teaser (“Download the checklist”) below the hero paragraph.

                                      9. Measuring success across both layers

                                      Metric Overviews AI‑Mode Target
                                      Impressions vs. Clicks ▼ CTR N/A* Monitor 30‑day delta
                                      Branded search volume ↑ if citations recall brand ↑ via deeper engagement +5 % YoY
                                      Scroll depth & dwell time Standard Longer sessions ≥ 90 s
                                      Assisted conversions Post‑click purchases Research assist → return Attribute multi‑touch

                                      *AI‑Mode traffic logs separately in Search Console’s AI tab (beta).

                                      10. Pitfalls to avoid

                                      • Burying answers under anecdotes
                                      • Splitting one FAQ across multiple URLs
                                      • Out‑of‑date stats (Overviews drop stale pages fast)
                                      • Ignoring long‑tail queries that still deliver clean clicks

                                      Example / Template

                                      <!– 74‑word hero snippet under H1 –>

                                      <p>Google’s AI‑Mode shows a fully cited answer in its dedicated tab, while AI Overviews

                                      surfaces a concise snapshot above organic links. Rank in the top‑10, write a

                                      60–80‑word solution here, and back it with expert citations to earn both source

                                      chips.</p>

                                      FAQs

                                      Will AI‑Mode kill my CTR?

                                      AI‑Mode sits behind a tab, so only sessions where users opt in bypass organic links entirely. AI Overviews is the bigger CTR threat, trimming clicks by 10‑25 % on affected queries. Mitigate via branded teasers and interactive assets.

                                      Is schema markup still worth the effort?

                                      Yes—FAQPage, HowTo, and FactCheck schema mirror the AI layers’ Q&A structure, accelerate verification, and can trigger rich snippets when no AI answer shows.

                                      Does AI‑Mode penalise affiliate sites?

                                      No direct penalty, but thin, boiler‑plate reviews rarely count as verified. Add first‑hand photos, test data and disclosure labels.

                                      Can I opt out of AI answers?

                                      No. Blocking Googlebot removes you from Search entirely. Instead, lean in—optimise hero snippets, strengthen branding, and turn AI citations into authority signals.

                                      Ten‑Point Action Checklist

                                      • Audit recurring FAQs and rankings.
                                      • Write 60‑80‑word hero paragraphs.
                                      • Add author credentials, citations, fact‑check schema.
                                      • Use question‑form H2/H3s.
                                      • Break answers into ≤ 3 sentences & lists.
                                      • Hit LCP < 2.5 s, INP < 200 ms.
                                      • Build expert backlinks.
                                      • Monitor AI citations and AI‑Mode sessions.
                                      • Refresh content quarterly (monthly for YMYL).
                                      • Track impressions, brand queries, conversions.

                                      The Future Is Semantic: Why Vector Embeddings Will Re-Write Your SEO Playbook

                                      From Keyword Tweaks to Content Engineering

                                      Remember when SEO success meant sprinkling the right keywords in title tags and praying for backlinks? That era is fading fast. Google’s AI Mode and its expanded AI Overviews now synthesize answers directly in the SERP, citing passages—often buried deep inside a site—rather than the traditional homepage snippets. In fact, 82 percent of citations in AI Overviews point to pages tucked two or more clicks away from the front door. 

                                      If Google is willing to dig that far beneath the fold, it’s clearly valuing topic depth and semantic relevance over surface-level keyword placement. Welcome to the age of Relevance Optimization—the discipline that treats visibility as a measurable engineering challenge instead of an “optimization” afterthought. 

                                      Why Semantic Optimization Matters

                                      Search Queries Are Now Semantics, Not Strings

                                      Google’s 2013 Hummingbird overhaul replaced purely lexical (word-matching) scoring with semantic understanding—essentially asking, “What does the query mean?” rather than “Which words appear?” That shift only intensified with every language-model upgrade since.

                                      Generative AI Needs Precise Context

                                      Large language models (LLMs) like Gemini 2.5 or GPT-4 break user prompts into sub-queries, retrieve semantically similar passages, and stitch them into coherent answers. If your content isn’t structured for easy extraction—think tight paragraphs, clear headings, and complete subject-verb-object statements—AI may skip you in favor of a competitor who writes with vectors in mind.

                                      Behavioral Metrics Still Close the Loop

                                      Click-through rates, dwell time, and “pogostick” abandonment remain crucial. But they’re now the second filter. First, you must be retrieved from vector space; only then can engagement metrics prove you deserve to stay visible.

                                      Vector Embeddings 101: Coordinates for Meaning

                                      A vector embedding is a mathematical representation of a chunk of text (or an image, or an entire site) translated into hundreds—or thousands—of numerical dimensions. Think of it as an address in “meaning space.” LLMs learn to place semantically similar pieces of content near one another; the closer two vectors are, the more alike their meaning. 

                                      How the Process Works

                                      1. Tokenize: The model breaks sentences into tokens (words or sub-words).
                                      2. Project: Each token is mapped to a high-dimensional coordinate based on training data.
                                      3. Aggregate: Tokens combine (often via averaging or attention mechanisms) into a single vector for the entire passage.
                                      4. Compare: When a user searches, their query is embedded the same way. A cosine-similarity calculation measures how close that query vector is to every document vector in the index.
                                      5. Return: The engine ranks documents whose vectors sit nearest to the query—before any traditional ranking factors kick in.

                                      Why Embeddings Trump Exact Keywords

                                      Imagine two pages:

                                      • Page A: “A marathon is 26.2 miles long.”
                                      • Page B: “How far do runners travel in a marathon?”

                                      Old-school keyword matchers might miss Page B for the query “marathon distance.” Vector embeddings recognize the semantic equivalence because both vectors converge in meaning space.

                                      EEAT in a Vector World

                                      Google’s quality framework—Experience, Expertise, Authoritativeness, Trustworthiness (EEAT)—is increasingly modeled with embeddings. Authors, pages, and entire domains are vectorized; Google can then calculate how consistently an entity writes about a given topic. Publish 60 in-depth articles on periodontics, and your author vector crowds into the “dental expertise” cluster—boosting perceived authority without a single link-building outreach email. 

                                      Conversely, scatter content across unrelated niches (sneakers one day, marine biology the next) and your site vector diffuses—diluting topical focus and relevance.

                                      Practical Steps to Optimize Relevance

                                      1. Chunk Content into “Fraggles”

                                      AI Overviews rarely quote whole articles; they lift fraggles—tiny, self-contained passages that answer a micro-question. Keep sections concise (roughly 50-150 words) and laser-focused on a single idea. Use descriptive H2/H3 headings so retrieval systems pinpoint the right paragraph instantly.

                                      2. Embrace Semantic Triples

                                      Write sentences that explicitly frame relationships: Subject → Predicate → Object.

                                      “Vector embeddings map words to high-dimensional space.”
                                      The clearer the predicate, the easier it is for retrieval algorithms to detect your answer.

                                      3. Expand Vocabulary with Contextual Entities

                                      Include synonyms and closely related entities—LLM, cosine similarity, semantic hashing—to beef up contextual signals. This isn’t keyword stuffing; it’s adding semantic scaffolding that clarifies the topic’s perimeter.

                                      4. Use Structured Data Everywhere

                                      Schema markup remains the fastest way to hand AI “feature-rich” metadata. As knowledge graphs merge with LLMs, JSON-LD becomes a lighthouse in the semantic fog, guiding both ranking and answer synthesis.

                                      5. Audit with Embedding-Based Tools

                                      Modern SEO suites now offer relevance scores based on cosine similarity to a topic vector. Treat anything below your chosen threshold as a candidate for revision or pruning. That’s Relevance Optimization in action—quantifying what used to be a gut check.

                                      Common Myths Busted

                                      MythReality
                                      “Just add more keywords; LLMs will figure it out.”Keyword density is noise in a semantic model. Quality, structure, and topical focus win.
                                      “AI Overviews kill organic traffic, so why bother?”Early data shows click-through rates drop, but the traffic that does click is highly qualified. Don’t forfeit that edge. 
                                      “Author bios satisfy EEAT.”They definitely help, but true authority comes from a body of semantically consistent work.
                                      “Vector SEO is only for big enterprise sites.”Any CMS can output structured data, and free embedding APIs let even small blogs test cosine similarity.

                                      The Road Ahead: Search Without Blue Links?

                                      As AI Mode rolls out, entire industries are bracing for fewer clicks and more zero-click answers. Some publishers see this as existential; others see opportunity. Whichever camp you’re in, one fact is clear: semantic relevance is the new table stake. The brands that engineer content for machine comprehension—vector-friendly passages, structured context, demonstrable topical depth—will surface in chatbots, voice assistants, and whatever interface comes next.

                                      Meanwhile, behavioral metrics still police quality. If users bounce from an AI answer back into the SERP—or worse, reformulate the query—that negative signal feeds the loop. Relevance Optimization thus spans both retrievability (be the right vector) and satisfaction (earn the engagement).

                                      Key Takeaways

                                      1. Vectors are the language of modern search. If your content isn’t embedding-friendly, it’s invisible to the first stage of ranking.
                                      2. Deep pages matter. Google’s AI Overviews overwhelmingly cite internal resources, not homepages. Optimize accordingly. 
                                      3. EEAT is measured mathematically. Consistent topical publishing tightens your entity vector, signaling expertise without manual “author tag” hacks.
                                      4. Structured data future-proofs visibility. As LLMs cross-pollinate with knowledge graphs, schema markup becomes non-negotiable.
                                      5. Relevance Optimization > traditional SEO. Treat visibility as an engineering problem—quantify, iterate, and scale.

                                      Ready to Engineer Your Future?

                                      Semantic search isn’t coming; it’s here. If you’d rather lead than react, start embedding-minded content workflows now. Not sure where to begin? Book a strategy call with our team, and let’s turn your site into a machine-readable, AI-ready authority—before your competitors figure out why their keyword tweaks stopped working.

                                      GEO (Generative Engine Optimization): Mastering AI Search with the G.E.O.D.A.T.A. Framework

                                      Generative Engine Optimization

                                      Remember the good days of SEO? Where you could cram in a few related keywords into your website content and Google would (maybe) reward you with top-ranking glory? 

                                      These were simpler times, and now we unfortunately find ourselves waving goodbye to the simplicity of it all. These days, AI-driven search tools like those found in ChatGPT, Claude, and Perplexity are re-writing the playbook (or just setting it on fire). 

                                      For businesses, the SEO game has changed.

                                      It’s not just businesses pulling their collective hair out over this. Searching online as a regular human being has turned into an Olympic-level patience test. You type a question into Google and rather than getting a helpful answer, you’re bombarded with ads masquerading as advice. Those of us who have recently made use of AI-driven search have discovered a little secret: AI can sometimes answer our questions better than Google ever could

                                      Welcome to the Future of Search (or How We All Lost Our Minds)

                                      So, how do we fix this? Well, we don’t. Instead, we adapt to this new wave of search technology that’s fast becoming a survival strategy for brands that need to stay relevant. 

                                      Say hello to Generative Engine Optimization (GEO) — a new lifeline for traditional SEO experts feeling the sting of AI-driven search. GEO offers more than merely surviving the noise but allows your brand to stand out where it matters the most, with visibility that actually counts. 

                                      The G.E.O.D.A.T.A Framework from SEO Rank Media is a seven-step strategy that covers everything from ensuring bots can crawl your content to dealing with those AI “hallucinations” where facts go to die. 

                                      Instead of fighting the system, make it work for you. If you’re ready to drop the SEO tricks of yesterday and learn more about GEO, let’s get started.

                                      The G.E.O.D.A.T.A. Framework

                                      AI search platforms like ChatGPT, Claude, and Perplexity have opened up a whole new world for businesses to connect with audiences. Sounds great, right? But here’s the twist—this isn’t “business as usual” SEO anymore. 

                                      If your strategy is still clinging to Google SERPs like a security blanket, you’re already behind the curve.

                                      That’s where the G.E.O.D.A.T.A. Framework comes in. Developed by SEO Rank Media, the framework gives your business a head start in the AI-driven search arena.

                                      What makes the G.E.O.D.A.T.A. Framework different?

                                      1. Practical from Day One: Each step is clear and actionable—you can actually do something with it.
                                      2. Bigger Than AI Rankings: Sharpen your overall marketing game.
                                      3. Team-Friendly: Easy enough to explain to your boss, clients, or that one coworker who still doesn’t “get” AI.

                                      Why Bother with a Framework?

                                      The field is no longer about simply “ranking in Google.” Today’s search environment demands leadership and strategy. Brands need guidance to navigate:

                                      • How to perform across multiple AI search platforms.
                                      • What kind of content to produce to engage these platforms.
                                      • Where and how to distribute content to maximize visibility.

                                      The Steps of G.E.O.D.A.T.A.

                                      The framework outlines a step-by-step process to align your content and search strategies with the AI-dominated world. Each step builds on the last to ensure your brand is positioned for success:

                                      1. Gather Intelligence – Know what’s happening in the AI search world.
                                      2. Evaluate Accessibility – Make sure bots can actually find your stuff (duh).
                                      3. Optimize Brand Presence – Be unforgettable, or at least noticeable.
                                      4. Develop Sentiment – Build a brand people (and AI) actually like.
                                      5. Analyze Competitors – See what’s working for them and learn.
                                      6. Target Data Sources – Be where the algorithms are pulling from.
                                      7. Answer Accurately – Deliver real answers, not fluff.

                                      1. Gather Intelligence

                                      Tools like ChatGPT and Claude are shaping the way people perceive your business, whether you’re aware of it or not. So, understanding how these AI platforms view your brand is a big deal. If AI gets it wrong, like misrepresenting your brand or offering answers that aren’t very accurate, you’re left with customers who are judging your offerings based on bad info. 

                                      So, how do these AI platforms know what to say about you? It all comes down to the data they have been trained on. AI pulls from all sorts of sources, including:

                                      • Websites, blogs, and forums (including user-generated forums).
                                      • Search Engine Results Pages(like Google.com)
                                      • Social media chatter
                                      • Structured datasets like Wikidata
                                      • Specialized integrations like OpenAI’s via links like Microsoft

                                      Ai synthesizes all this information and uses it to generate answers. The quality of those answers depends heavily on the data available. If your brand isn’t well-represented, or worse, represented inaccurately, the AI delivers those misleading results—with confidence.

                                      So the first step is simple: start asking questions. Fire up an AI tool like ChatGPT and test the waters with queries like:

                                      • “What is [Your Brand]?
                                      • “What does [Your Brand] offer?
                                      • Is [Your Brand] trustworthy?”

                                      Pay close attention. Does the AI accurately summarize your business? Are there outright inaccuracies? 

                                      Armed with these insights, you can identify where your messaging needs to improve and take steps to fix it. This isn’t guesswork, it’s actionable intelligence, and the very foundation of effective GEO.

                                      2. Evaluate Accessibility

                                      There’s been a lot of chatter lately about blocking AI from crawling websites—like letting bots read public information somehow equals grand theft data. Unless you’re sitting on government secrets (which shouldn’t really be public in the first place), blocking AI does more harm than good.

                                      AI platforms use bots to crawl sites to get data for their models, the same way Google does. The difference is Google relies on structured indexing, and AI pulls data from a wider range of sources. 

                                      If you want to show up in AI search results, then you need to give these bots access to your page. It’s as simple as that. 

                                      Start by checking your robots.txt, the gatekeeper for bots. This file tells crawlers what they can and can’t access. Yes, it is smart to block some bots to save resources or secure sensitive areas, just make sure you’re not accidentally excluding AI too.

                                      Tools to Test Bot Accessibility

                                      1. User Agent Switcher: This Google Chrome extension mimics different bot user agents and tests how your site responds. 
                                      2. Manually Check robots.txt: Append /robots.txt to your domain (e.g., yourdomain.com/robots.txt) to see what’s blocked and allowed.
                                      3. Known User Agents: Look for these examples to make sure your website is letting in the right bots:
                                      • GPTBot: Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko); compatible; GPTBot/1.1
                                      • ClaudeBot: Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko); compatible; ClaudeBot/1.0
                                      • Anthropic AI Bot: Mozilla/5.0 (compatible; anthropic-ai/1.0)

                                      A full and updated list of these user agent strings can be found on DataDome.

                                      3. Optimize Brand Presence

                                      It’s likely you’re no stranger to how important brand presence is when it comes to SEO. AI platforms pull all of the information they find online and use it to understand and then represent your business when a user searches for it. 

                                      If your messaging is long-winded, vague, inconsistent, or missing, you’re risking misrepresentation, or worse, being completely ignored.

                                      Your landing pages need a very frank and straightforward brand statement that answers the basics:

                                      • Who you are: “[Your brand] leads the way in sustainable home goods.”
                                      • What you do: “We create eco-friendly furniture for modern living.”
                                      • Why you’re different: “Our designs combine style, sustainability, and affordability.”

                                      Make sure this messaging is everywhere AI platforms might be looking. Put it on your website, LinkedIn, and social media, and review responses as AI will draw answers from a multitude of sources. 

                                      Consistency is what gets your brand represented the way you want, and not as some random mashup of outdated info. Set the record straight before anyone can even get the wrong idea. 

                                      4. Develop Sentiment

                                      AI platforms don’t just pull out the facts, they piece together a brand’s overall vibe from an array of sources: forums, reviews, and social media. The catch is that bad press tends to stick around like gum on a shoe. 

                                      Take AT&T, for example: ask ChatGPT about their reliability as a service provider and you’ll likely hear all about their 2024 outage alongside mentions of their reliability. Ouch.

                                      Now, compare that to CrowdStrike. Despite their infamous broken Windows update causing probably the biggest global IT outage in history, you won’t see AI harping on it.

                                      Why? They have absolutely mastered sentiment management, strategically flooding the digital space with positive content and well-managed review responses that overshadow their epic blunder.

                                      If you want AI to focus on your wins, start by testing how platforms portray your brand. Ask questions like “Is [Your Brand] reliable?” Spot the negatives and tackle them head-on with corrective content. 

                                      Strong sentiment GEO means when people search for your brand, they see your strengths and not your stumbles. 

                                      5. Analyze Competitors

                                      Keeping tabs on your competitors in the SEO world is a necessary evil, but with AI, it becomes a whole lot easier to see just where your business could sit in rankings.

                                      AI rankings heavily influence user decisions, especially for the juicy middle-of-funnel searches like “Best

                                      in [location]” or “Top providers for [service].” Having an understanding of how your business stacks up against the competition reveals where you can step up your game, be more visible, and take your place in the share of the market.

                                      Start by identifying the key competitive queries that are relevant to your industry. AI tools like ChatGPT make this quite easy, but for the best results, use a GEO service like SEO Rank Media to map out how competitors are ranking. 

                                      With this intel, it’s time to take action. Create content that answers these questions better than anyone else. Use clear, direct language, highlight your benefits, and make sure your expertise comes through in a specific way AI platforms recognize. 

                                      The goal here is to make sure your brand is the obvious choice for these searches.

                                      6. Target Data Sources

                                      Free Close-up image of the LinkedIn app update screen on a smartphone display. Stock Photo

                                      Image: Pexels

                                      AI platforms don’t just make things up (well, most of the time), they draw from trusted data sources like LinkedIn, GitHub, and even Reddit to create their responses. If you want your brand to show up in those results, you need to meet AI where it’s looking.

                                      Here are a few ways you can improve your visibility:

                                      • Publish technical content on GitHub: This platform is a favorite for technical queries, so it’s perfect for showcasing your expertise in a concrete, credible way.
                                      • Share insights on LinkedIn: As a part of Microsoft’s ecosystem, LinkedIn is practically a VIP source for professional and industry-specific content.
                                      • Have some fun on Reddit: Claude and ChatGPT crawl Subreddits to gain community-driven perspectives. Join in on relevant discussions in an informational (not sales) way to boost your authenticity. 

                                      Get strategic in the way you place content and you’ll ensure your brand’s voice is part of the AI conversation.

                                      7. Answer Accurately

                                      AI “hallucinations” aren’t as fun as they sound. These occur when AI platforms respond with incorrect or misleading information that is so confident it would give ToastMasters a run for their money. Basically, they’re not something you want to happen when someone uses AI to look up your offerings.

                                      The GEO fix for this issue is to create well-structured and relevant FAQ pages that answer critical questions like:

                                      • “Does [Brand] ship internationally?”
                                      • “How does [Brand] handle refunds?”
                                      • “What services does [Brand] Provide?”

                                      Here’s some proof in the pudding. Taking a look at Ancestry.com’s FAQ page, you can see they have answered commonly asked questions about their service, with one being what do the results tell me?

                                      Jumping onto ChatGPT and asking the question “What do my ancestry.com results tell me?” yields a result that was quite clearly taken from this FAQ page. 

                                      Understanding your audience helps here. You need to know what kind of questions they’re likely going to be typing into an AI search engine and give straightforward and simple answers to them on your website’s FAQ page. 

                                      The payoff will be fewer opportunities for hallucinations and a more accurate representation of your business in AI-generated results. 

                                      Why GEO is the Way Forward

                                      Let’s be honest: AI search has turned SEO into a wild roller coaster. One minute, you’re impressed by ChatGPT’s ability to summarize complex topics; the next, it’s confidently claiming your brand sells banana-flavored widgets (which, of course, you don’t). 

                                      Staying ahead feels like having to learn SEO all over again, but it doesn’t have to.

                                      With SEO Rank Media and the G.E.O.D.A.T.A. Framework, you’ve got a reliable roadmap to tame the chaos and put your brand back in the spotlight. It’s your chance to future-proof your digital strategy, outsmart AI’s quirks, and thrive in this unpredictable search landscape.

                                      Ready to take charge? Let SEO Rank Media help you GEO your way to success.

                                      How Digital Marketing Has Evolved: Blogging, Attribution & Omnipresence in 2025

                                      Marketing in 2025 just isn’t what it used to be. There was a time, a glorious time when hitting “publish” on a blog post was like unlocking a floodgate of traffic. A well-placed keyword here and there, a handful of backlinks, and boom! You were on page one of Google, or at least in the top five.

                                      Fast forward to 2025, and as you’re probably already painfully aware, it’s a totally different game. Consumers don’t just stumble onto blogs and convert overnight. Instead, they hop nonchalantly between Google, Instagram, AI-powered search, email, and social ads. It can also take quite a few of these hops, or “touchpoints,” before they’re ready to make a purchase.

                                      For your business, this means that you can no longer just rely on a blog post or a single ad campaign to get the lead ball rolling. Marketing success today means you need to concentrate on these three things:

                                      1. Multi-touch attribution, so you know what’s actually driving sales.
                                      2. Building up and commanding omnipresence, so your brand shows up everywhere your customers are looking.
                                      3. Creating a steady flow of good content to build trust, not just traffic.

                                      Let’s break down exactly how to do that in 2025.

                                      Blogging in 2025: No Longer Just a Traffic Magnet

                                      Blogging in 2025
                                      Source: Unsplash

                                      Blogging used to be the golden ticket to online success, and brands that leveraged it dominated search results and thrived. Now, in 2025, competition is fierce, algorithms are smarter, and consumers are bouncing around between platforms before making a move.

                                      So, is blogging dead? Not even close. It’s just playing a new role.

                                      Let’s take a quick trip down memory lane to see how blogging and digital marketing came to be and why they’re still relevant today.

                                      The 2000s: The Early Days of Blogging and SEO Goldmines

                                      In the early 2000s, blogging was like rocking up to a nearly empty street, whipping out a megaphone and shouting out to anyone in earshot. There weren’t many people around, but anyone who showed up got heard. With such little competition, a well-optimized blog could rank in Google fairly effortlessly and drive thousands of visitors to your website.

                                      Businesses could even monetize blogs, even back then. In fact, monetization occurred as early as 2003 with BlogAds, arguably the precursor to Google AdSense.

                                      Source: BlogAds

                                      But, as with all things that actually work, businesses soon caught on. Those who invested in blogging saw huge returns, and a solid blog could single-handedly fuel brand awareness and generate real organic sales.

                                      No paid ads, no complex funnels, just good quality content and strong SEO (even if we didn’t really understand what SEO was).

                                      Yes, blogging was not only a marketing tool; it was the only marketing tool that really mattered. But then, social media arrived.

                                      The 2010s: Social Media Disrupts Everything

                                      The 2010s changed everything. Platforms like Facebook, Twitter, YouTube, and Instagram utterly exploded in popularity and stole the attention away from traditional blogs.

                                      Source: DataReportal

                                      People were still searching on Google, but they were also scrolling, sharing, and consuming bite-sized content on social media.

                                      Smart brands saw the writing on the wall and used their long-form content, storytelling, and new-found expertise to provide the things social media couldn’t.

                                      Blogs became a sort of “home base” where brands could deep-dive into topics, and social media posts became the vehicle through which traffic was directed.

                                      It worked well, for a while. But today, even that strategy isn’t enough.

                                      2025: Blogging as a Relationship-Building Tool

                                      Here we are in 2025, and blogging is still alive and kicking, only now it’s no longer just about traffic, but trust. Every day, 7.5 million blog posts are published. That’s like the entire population of Hong Kong hitting the publish button on a daily basis, and Google has to catalog it all.

                                      With so many posts, needless to say, simply ranking on Google won’t cut it anymore. Instead, blogs have become engagement hubs—places where brands educate, mature, and build loyalty with their audience.

                                      The numbers back this up:

                                      • Businesses with a blog receive 55% more website visitors than those without.
                                      • Companies maintaining active blogs generate 67% more leads per month.

                                      (Source: Oberlo)

                                      So, given all these intricacies, the dominance of social media, and the sheer number of blogs out there, why do they still work? Blogs give brands a voice, credibility, and a way to stay top-of-mind.

                                      The brands winning in 2025 aren’t just writing for the clicks. They are creating blogs that:

                                      1. Answer real questions.
                                      2. Provide unique insights that AI can then pull from for user prompts.
                                      3. Keep audiences engaged through email and social distribution.

                                      In short, if you’re using your blog as just a content dump or creating content no one will realistically want to consume, you’re not building any trust. Play the game right, and your blog will not only attract visitors but also turn them into long-term customers.

                                      Why Attribution Is Still Broken (and What to Do About It)

                                      Source: Unsplash

                                      Ever taken a good look through your marketing analytics and asked yourself the quiet question, “Wait, which marketing effort actually got that sale?” Trust me when I say you’re not alone in this. Tracking customer journeys nowadays is very complicated.

                                      The days where you could simply slap a “conversion” label on a single touchpoint have gone out the window. Today’s buyers are zigzagging their way through multiple platforms before they come to that all important decision to buy. They’re watching videos, reading reviews, searching for you on social media, and even asking ChatGPT.

                                      And yet, most marketing attribution models are still stuck in the 2000s. Let’s break down where they fail and what to do about it.

                                      The Old Way: Single-Touch Attribution

                                      Back in the day, marketing attribution was super simple. You could either credit the first touch (where the customer first discovered you) or the last touch (where they finally converted).

                                      • First-touch attribution: “They found us through a blog post, so blogging gets the credit!”
                                      • Last-touch attribution: “They clicked an Instagram ad and bought it, so Instagram gets the credit!”

                                      It all sounds so neat and tidy, case closed. Only it’s not. It’s actually wildly inaccurate.

                                      These models completely ignore the journey in between. What if a customer found your site on Google, read a few blog posts, watched your YouTube video, then got retargeted through an email. Then they later clicked on an ad they saw before converting? Should that ad really get the credit? Probably not.

                                      The New Reality: Multi-Touch Attribution (MTA)

                                      Enter multi-touch attribution (MTA). This is a model that spreads the credit across multiple interactions in the buyer’s journey.

                                      For example:

                                      1. A Google search for a hair dryer over a lunch break: This finds a blog post on your website.
                                      2. The customer reads more of your content while having a coffee: They are engaging with your expertise.
                                      3. Instagram ad: They’re off their lunch break but later at home while doom scrolling an ad pops up for your product and they’re reminded they need to keep reading. They subscribe to your blog’s newsletter.
                                      4. Email newsletter: A final nudge from your campaign offering a 12% discount on hair care appliances.
                                      5. Direct visit: They decided to jump on your site and buy the hair dryer.

                                      This approach doesn’t just give all the credit to the discount offered in the newsletter or even the blog post itself. MTA assigns value to each and every step. It’s a huge improvement over single-touch, but it’s still far from perfect.

                                      Why Multi-Touch Attribution Still Fails

                                      Sorry to be the breaker of bad news, but MTA still has some massive blind spots:

                                      The dark funnel problem: Analytics can’t track word-of-mouth referrals, a private recommendation over WhatsApp, or a few colleagues at work talking over Slack.

                                      AI search: If someone found out about your product during a late-night session with ChatGPT or DeepSeek, how would you ever know it happened?

                                      External influence: What if your competitor has a flash sale or a TikTok influencer makes a viral post featuring your product? No attribution model can account for these events; you have no insight here.

                                      So, what’s the solution?

                                      • Ask your customers how they figured out you exist with a post-purchase survey.
                                      • Combine multiple tracking tools like Google Analytics, UTM tags (great for AI search), and social analytics.
                                      • Choose to accept that sometimes you just can’t keep tabs on everything. Instead focus on creating valuable touchpoints instead of chasing the “perfect” attribution model.

                                      Attribution is never going to hit 100% accuracy, but understanding how these gaps account for success makes you a smart marketer.

                                      The 2025 Marketing Playbook: Omnipresence (Without Burnout)

                                      The 2025 Marketing Playbook
                                      Source: Unsplash

                                      If you’ve been told you need to be “everywhere, all at once” online, take a deep breath, you don’t. The idea that brands need to dominate every single platform is one of the biggest marketing myths of the digital age.

                                      What Omnipresence Actually Means

                                      Being omnipresent doesn’t mean blasting your content across every channel possible, like an emergency broadcast. That’s a surefire route to burnout. Instead, the smartest brands in 2025 are strategically present where their audience already spends their time.

                                      For some that might mean Google + LinkedIn, for others, it’s Instagram + email marketing. The key here is to choose the right platform, showing up consistently, and making every single interaction count.

                                      Trying to be everywhere at once means you spread your resources way too thin. Instead, focus on being discoverable (SEO), engaging (social), and retaining (email). Nail those three, and you will be present where it actually matters.

                                      Step 1: SEO

                                      Even in 2025, Google is still the king of discovery, but now you can also add the web search capabilities of generative AI to the mix. Tools like ChatGPT, DeepSeek, and Perplexity pull much of their information straight off of search engine data, so that means if your content is optimized for search, you’re invisible across both fronts.

                                      Tactic: Invest in SEO-friendly content and the occasional press release to get visibility in AI-generated responses. We outline this approach in detail across our G.E.O.D.A.T.A framework articles.

                                      Step 2: Social

                                      Social media is the new discovery engine, with 61% of consumers discovering new products on Instagram alone. Does that mean you need to be on every single one of them? No.

                                      Tactic: Instead of trying to master TikTok, LinkedIn, and YouTube all at once, pick just one or two that align with your audience. If your customers are B2B pros, use LinkedIn. If you sell lifestyle products, Instagram is perfect. If you’re a financial institution, YouTube works wonders.

                                      A strong presence on one well-managed platform beats a scattered presence across give every single time.

                                      Step 3: Email

                                      Social gets you noticed, but email keeps you remembered. In fact, 59% of consumers say that marketing has a significant effect on their purchase influence.

                                      Unlike social media, where you’re at the mercy of algorithms, your email list is yours to keep forever. That’s why all the winning brands are still using it in 2025.

                                      Tactic: Capture every single email address you can. Get them through blog CTAs and social bios, and create irresistible lead magnets. Then, nurture those leads with a steady feed of personalized, valuable, and engaging content. That way, when those customers are ready to buy, you’ll be right there, top of mind.

                                      How Many Interactions Does It Really Take to Make a Sale?

                                      Source: Piqsels

                                      If you’ve ever heard of the old marketing “Rule of 7” (the idea that a customer needs to see your brand at least seven times before they commit to a purchase), it’s time to forget it. That rule was made for an era when people had to get up off the couch to mute their TV and still read newspapers.

                                      Rule of 7? More like 20+ Touchpoints

                                      It’s 2025, and most people don’t make snap decisions anymore. Instead, they willingly enter a maze of interactions before finally settling on a purchase. And the number of touchpoints they went through to get there? Well, it’s a lot higher than seven.

                                      • Warm leads: These are people who already know and like your brand, but even they need 5-12 touchpoints before they trust you enough to type in their credit card number.
                                      • Cold prospects: Well, they’re called cold for a reason. These potentials need 20 – 50 touches before calling a decision.
                                      • Inactive customers: Breathe a sigh of relief. Typically, they only need 1 – 3.

                                      Your brand needs to be seen, heard, remembered, and trusted across multiple channels. If someone discovers you first on Google with a search but then sees you again pop up on LinkedIn, they’re more likely to follow the trail and become a customer.

                                      How to Speed up the Buyer Journey

                                      If you wait for those 50 touchpoints to happen organically, you probably won’t be selling much in the near future. You need to give the process a gentle nudge:

                                      • Use remarketing ads: Most visitors won’t buy on their first visit, so retarget them on Google, Facebook, and Instagram as a gentle reminder.
                                      • Offer micro-commitments: Free trials, lead magnets, a newsletter—anything to nurture the lead and keep them engaged.
                                      • Keep the message consistent: If your website, ads, and social content all tell the same clear story, then people are going to recognize you fast, and remember you.

                                      The brands that win the marketing races of 2025 aren’t just going to pop up once or twice. They’re going to strategically plant themselves in front of their audience until the time is just right.

                                      The 3-Part Marketing Formula for 2025

                                      The one magic marketing trick doesn’t exist anymore, so 2025 is the year when you should stop chasing it. Instead, focus on playing a long game with a strategy that actually works. That means concentrating on the three core pillars we already discussed:

                                      1. Engaging blog content: Think of blogging as more than just luring traffic to your site. It has to be valuable and engaging. Use it to build trust, authority, and brand loyalty.
                                      2. Smart tracking: Multi-touch attribution helps, and you should use it. Just understand that it’s not perfect, know its blind spots, get surveys out there, and track what you can.
                                      3. Use strategic omnipresence: You absolutely don’t need to be everywhere all at once on a biblical scale. Just be present where it matters. Remember: SEO, social, email.

                                      Master these three, and you will no longer be chasing down customers. You’ll be attracting them.

                                      Want more insights like these? Subscribe to our YouTube channel for expert strategies that actually move the needle.

                                      Lights, Camera, Action – But Is Anyone Watching? SEO for LA Businesses

                                      Welcome to Los Angeles. It’s a city where the summers are endless, and dreams are as big as the traffic jams. You’ve got the perfect business, an absolutely killer location, and maybe even a celebrity endorsement (or at least a cousin who once saw Brad Pitt at a Starbucks).

                                      But here’s the plot twist: If your business isn’t showing up in search engines, you’re basically another tree falling silently in an empty forest.

                                      If you really want your business to be more than just another face in the LA crowd, you need to stand out. Search Engine Optimization (SEO) is the star of the show.

                                      Table of Contents

                                      The LA Business Scene: Busier Than Sunset Boulevard

                                      The scene is crowded, with over 244,000 businesses hustling in LA County. Standing out is about as easy as finding a parking spot in Santa Monica on a Saturday. While Hollywood does love to hog the spotlight, the entertainment industry only employs 4% of the population.

                                      LA Business

                                      The real star is healthcare, commanding a hefty 11.9% of the workforce followed closely by industries like retail, hospitality, and manufacturing. 

                                      Shocking right? Well, not really, LA after all is much more than just a city for making movies, so unless you’re planning on performing a few tummy-tucks or rolling out the next big thing in retail, you’re up against some stiff competition.

                                      In this bustling mix of industries, making your business shine as bright as the Hollywood sign requires a killer SEO strategy. Without it, you might just end up on page two of Google, or as I like to call it, The Bermuda Triangle of the Internet.

                                      Did you know that 93% of online experiences start with a search engine? Before customers even think about stepping into your store or clicking “Add to Cart,” they’re on Google looking at their options. If your business isn’t showing up in those results, you’re missing out on customers. 

                                      So, unless you want to stay LA’s best-kept secret, it’s time to start thinking of SEO as your agent, working tirelessly behind the scenes to get you noticed by the people who matter the most. 

                                      A Quick Flashback: SEO's Journey in the City of Angels

                                      Back in the mid to late 2000s, SEO in LA was more like an exclusive rooftop party—only the insiders were really invited. While most businesses at the time were busy splashing their logos on billboards along the 101 or cramming the airwaves with their advertisements, a quiet few were climbing their way up the Google ranks.

                                      Let’s roll out the red carpet on how SEO developed right here in LA:

                                      • 2005: Google Local Business Center made its debut and allowed LA businesses to pin their business on Google Maps. This made it possible for smaller businesses to show up right next to large chains when customers Googled “best coffee near me.”
                                      • 2009: Google Places was the next big thing, giving businesses the ability to show off their reviews, ratings, and photos. In a city that’s slightly obsessed with image, this was like a digital facelift.
                                      • 2011: Google+ Local attempted to merge with social media. While it didn’t exactly dethrone Facebook (nice try, though!) Mixing social profiles with business allowed LA businesses to engage more personally with their customers.
                                      • 2014: Google My Business consolidated all of these tools into one platform. It was able to manage multiple locations, track insights, and offer customers the chance to interact with businesses. 
                                      • 2021: Google Rebranded to become what we now know today as simply “Google Business Profile.”

                                      Throughout this evolution, technical terms like ‘local SEO”, “NAP consistency” (that’s Name, Address, Phone number), and “user-generated content” became as much of a part of the LA business lexicon as avocado on toast to locals.

                                      How to Stand Out: SEO as Your Personal Publicist

                                      Los Angeles is a city where everyone claims to be “kind of a big deal,” and using SEO is your chance to prove you actually are. Just being online isn’t enough. You need to absolutely steal the spotlight. Of course, by ‘spotlight,’ we mean ranking as high as possible on everyone’s Google search.

                                      Businesses that appear on the first page of Google search results receive 95% of web traffic, so it’s quite a prestigious position to be in.

                                      So, how do you make SEO your personal publicist? Let’s take a look at some SEO tips tailored just for the LA business crowd.

                                      1. Keyword Casting: Directing the Right Audience to Your Site

                                      Start by optimizing your website’s content with keywords your target audience is likely searching for. The key here is to be strategic. Don’t just ‘keyword stuff’ and hope for the best; focus on natural, engaging content that your customers are actually going to enjoy.

                                      Next, enhance the user experience of your website. Ensure that it loads faster than a TMZ rumor and looks consistent across all devices. No one likes sites that fail to load, and as cool as a retro party is, they don’t want to see websites that look like they’re from the 90s. 

                                      Don’t forget about quality backlinks (links from someone else’s website to yours). These are nice little endorsements from industry insiders and can be arranged between businesses as a mutually beneficial relationship.

                                      Maintain consistent business information across all online platforms. Nothing screams “unprofessional” louder than addresses that take your customers to the wrong place or phone numbers that go nowhere.

                                      2. Local SEO: Navigating LA's Neighborhoods Without a GPS

                                      Even though sometimes it feels like it, LA isn’t just one city. It’s a patchwork of vibrant neighborhoods, each with a unique vibe and customer base. Local SEO taps you right into these micro-markets like a true Angeleno.

                                      Almost half of Google searches are looking for local information, and 76% of them end up acting on that information within a day. So, if you own a taco joint in Echo Park, you want to show up on Google when someone nearby is looking for “best tacos near me,” not when someone in Anchorage does.

                                      To really master local SEO, start by claiming and optimizing your Google Business Profile. Make sure your address, hours of operation, and contact information are correct and up-to-date.

                                      Incorporate location-specific keywords into your website and its meta tags, but don’t commit the SEO sin of cramming in keywords like “xyz near me.” It looks bad, and it doesn’t work.

                                      3. Mobile SEO: Reaching Customers Stuck on the 405

                                      LA is a city on the move, except apparently for the traffic. LA traffic jams are the stuff of legends, and yes, there’s a way to take advantage of this.

                                      With over 60% of Google searches now happening from mobile devices, you need to make sure your website looks great on the smartphone.

                                      Picture it: Commuters are stuck in traffic, the exit for Signal Hill is fast approaching, and they’re hungry. If they search for “best vegan donuts Signal Hill” you want your website on page one and loading quickly on their smartphone. If your SEO game isn’t spot on, you’ve missed out on a customer with time (and hunger) and their hands.

                                      To make sure you catch those hungry drivers, implement a responsive design that looks good on any screen with mobile-friendly navigation and big, hard-to-miss, and clear CTA buttons. Test your site on multiple devices to make sure your business is only ever a tap away.

                                      4. Content Creation: Making Blockbusters, Not Box Office Bombs

                                      Content is king, but in LA, there’s a lot of it. Quality content will set you apart. Businesses that maintain a regular blog receive 97% more inbound links, so unless you want your business to be the straight-to-DVD production no one asked for, invest in content that resonates.

                                      Create engaging and relevant blogs that address your customer’s interests. If you don’t have the time to write these yourself (who does?), then hire writers to craft the content for you.

                                      This is also the chance to incorporate contextual SEO keywords into your content to snag some of those Google searches, then redirect them back to your website. Integrate the keywords naturally.

                                      Going back to our vegan food, here’s how a business might place keywords in their content:

                                      SEO keyword: “plant-based tacos Echo Park

                                      Blog content: “Los Angeles is a haven for food enthusiasts, especially those seeking vegetarian and vegan cuisine in LA. From plant-based tacos in Echo Park to gourmet vegan sushi in Downtown, LA’s diverse culinary scene caters to every single palate”.

                                      Don’t forget to keep your content fresh and share it on social media to amplify reach and encourage it to be shared far and wide.

                                      5. Social Media Signals: Your Red Carpet Moment

                                      In a city absolutely obsessed with social media (look at you, LA influencers), your online presence needs to be as polished as a celebrity’s Instagram feed.

                                      Social media works by giving your SEO a nice little nudge. Over 50% of social browsers now use social media to research products, so if your last Facebook post was from 2015, here’s your chance for a comeback tour.

                                      Start by engaging on platforms where your audience tends to hang out. Instagram, TikTok, or LinkedIn are great places to start. Share your high-quality, SEO keyword-pumped content that reflects your brand’s personality and really gets customers interacting via messaging and sharing.

                                      Use #hastags strategically and join in on conversations that are both trending and relevant to your industry. Collaborate with local influencers to further amplify your message and start collecting those backlinks—they’re as valuable as gold.

                                      Remember that every like, every share, and every comment boosts your website’s authority and gets your business close to the top of page one on Google.

                                      Final Thoughts: The Cost of Being Invisible

                                      If you’re an LA business, don’t neglect your SEO. If you do, you’ll be creating the next blockbuster and never releasing it. You invest time and resources into your business, so let it reach its full potential.

                                      Businesses that prioritize SEO experience higher revenues and traffic than those that overlook it. And in a city where everyone is vying for attention, do you really want to be the best-kept secret? Embrace effective SEO strategies and make sure your business stands out in the bustling LA market and attack the customers you deserve.

                                      Don’t just sit back and be the underdog in every business story. Take center stage and make SEO the headline act in your marketing strategy.

                                      Facts Every WordPress SEO Expert Should Know

                                      Teaming WordPress with SEO could be described as a perfect pairing. Although WordPress powers an impressive 43% of websites, simply installing a WP plugin doesn’t guarantee your site will rank on Google’s coveted first page. It’s not that straightforward, and if it were, we’d all be reigning champs of WordPress SEO.

                                      The truth is to truly excel at WordPress SEO, you need more than just technical know-how. It requires strategic thinking, hands-on experience, and yes—a bit of patience too.

                                      WordPress SEO isn’t purely methodical; there’s an element of finesse involved. From fine-tuning keywords to charm Google into favoring your structured data or enhancing image SEO and integrating breadcrumbs effectively, this article covers crucial techniques every aspiring WordPress SEO professional needs in their toolkit.

                                      Table of Contents

                                      WordPress and SEO – Why It’s So Important To Get It Right

                                      Think of WordPress as the most popular kid in school, capturing the attention of a whopping 43% of all web users. Peers like Shopify hover at a modest 4.5%.

                                      Although the basic principles of SEO are uniform across different platforms, there’s an art to harnessing WordPress’s full capability.

                                      cms platform usage
                                      Image: Created by Author

                                      Why stress over SEO? It’s your golden ticket to standing out in the digital crowd. Properly executed, it boosts your site’s visibility, draws in your target audience, and ramps up traffic—all adding up to increased authority and trustworthiness for your website.

                                      When it comes to WordPress, this means leveraging tailor-made themes, SEO-focused plugins, and robust tools that propel your site from just ‘being’ online to leading the pack in search engine standings.

                                      WordPress Plugins: The Good, the Bad, and the Ugly

                                      Plugins for WordPress are what make the platform itself so famous, but they can be your best friend or your worst enemy when it comes to SEO.

                                      With close to 60,000 free plugins available in WordPress, it’s pretty easy to get overwhelmed and inadvertently just “install all the things” until your WordPress site becomes a tangled, overlapped mess.

                                      In saying that, there are some incredibly useful plugins I do encourage you to use when dealing with WordPress. Yoast SEO with over 10 million active downloads is definitely one of them, and yes, we’ll be mentioning it quite a bit in this article.

                                      A word of warning: For every fantastic plugin, there’s always one that promises to be “the only SEO tool you’ll ever need.” That’s until the next update breaks your entire site.

                                      Here’s a quick rundown:

                                      • The Good: Yoast SEO, Rank Math, All in One SEO
                                      • The Bad: Plugins that haven’t been updated in years
                                      • The Ugly: Plugins that conflict with each other, causing site crashes

                                      Now that we’ve covered our bases, let’s take a look at the top six facts that SEO experts need to know when creating SEO content for WordPress sites.

                                      1. Keyword Optimization: Not Your Grandma’s SEO Anymore

                                      Remember the good old days when SEO just meant cramming as many “best,” “top,” and “cheap” keywords into the content as humanly possible in a vain attempt to bait Google into throwing your content to page one?

                                      Today, 68% of online experiences start with a search engine. It doesn’t matter if it’s Google, Yandex, or DuckDuckGo. SEO now drives over 1000% more traffic than organic social media.

                                      It’s no longer about playing Tetris with keywords. Today’s SEO expert must have a firm understanding of concepts like search intent and semantic search to develop content that meets the needs of users.

                                      With WordPress, you have some powerful tools at your disposal, like Yoast and Rank Math that make optimizing keywords far easier. These plugins help you use long-tail keywords and LSI (Latent Semantic Indexing) to write content that ranks and converts.

                                      This isn’t just hearsay, 60% of marketers report inbound methods like SEO as their highest source of excellent quality leads.

                                      2. Structured Data and Schema Markup: The Overlooked MVP of SEO

                                      Structured data and schema markup may not always be the first thing that springs to mind when you think of SEO, but let’s give credit where credit is due.

                                      These tools are like the understated wardrobe assistants who make sure a star shines on the screen – they set up your site to catch Google’s eye in just the right way.

                                      With structured data, search engines can glide through your content with ease, making sense of what’s essential. This is how those snazzy-looking rich snippets come about – yes, we’re talking about those highlighted boxes or dropdown answers crowning some search results that subtly scream, “Click me!”

                                      Image: Created by Author

                                      Now if you’re running a WordPress site and want these perks without feeling like you’ve stumbled into an espionage thriller trying to decipher code, plugins such as Schema Pro have got your back.

                                      It really is plug-and-play: install one of them, pick from options like ‘Article’ or ‘Product,’ input some info, and voila!

                                      For the more adventurous souls out there willing to get their hands metaphorically dirty with coding – manual insertion is also an option using JSON-LD script within your HTML canvas.

                                      In all seriousness though, engaging with schema markup could very well elevate your visibility online and potentially improve click-through rates. And isn’t being noticed by Google pretty much half the battle won?

                                      3. On-Page SEO: Crafting the Perfect Page Title and Meta Description

                                      Moving up just one slot on search engine rankings can increase your CTR by 32%, so having a compelling page title and meta description is really important to make the most of this prestigious real estate.

                                      While there are a few free SERP preview tools online, with WordPress, there are several plugins that can really make this task much more streamlined.

                                      On-Page SEO
                                      Image: Created by Author

                                      Plugins like All in One SEO and SEOPress allow you to quickly edit the meta title and descriptions while giving you all the relevant keyword suggestions and a lovely preview of what the search result looks like on both mobile and desktop.

                                      Remember that creating a meta description and well, most on-page SEO is a bit like art. You need to entice readers without turning the SERP preview into a clickbait cliché.

                                      4. Permalink Structure (Stop Using WordPress Default URLs, Please)

                                      Permalinks are the forever URLs to your WordPress pages and posts and they play a huge role in WordPress SEO.

                                      Clean and friendly URLs not only help search engines when deciding what your content actually contains but also make your links far more attractive to real users.

                                      Imagine choosing between the default “www.example.com/p=123” and “www.example.com/delicious-chocolate-cake-recipe.” The choice is pretty obvious.

                                      In WordPress, customizing your permalink structure is easy:

                                      • Post Name: “example.com/sample-post” – The best choice for SEO, making URLs clean and readable.
                                      • Day and Name: “example.com/2024/08/27/sample-post” – Good for news sites with frequent updates.
                                      • Month and Name: “example.com/2024/08/sample-post” – Similar to Day and Name but less specific.
                                      • Custom Structure: “example.com/blog/sample-post” – Great for more tailored URLs.

                                      Try avoiding the default URL settings at all costs. It’s not just bad for SEO, but for the end users,  it looks like your pages are hiding behind some hidden code.

                                      Essentially, WordPress URLs should be as clear as the content they’re linking to.

                                      5. Backlinks: The Double-Edged Sword of SEO

                                      Backlinking is the lifeblood of SEO. They act like big votes of confidence from one site to another and tell search engines “Hey, this content and website are totally worth checking out.”

                                      For WordPress SEO experts, backlinking can get tricky. Why? Along with all the genuine and well-thought-out backlinks, you’re also inundated with spammy requests from let’s say, some very “questionable websites.”

                                      Who knew your blog about artisanal bread making could attract so many offers from online casinos in Romania, right?

                                      Backlinks
                                      Image: Created by Author

                                      To build high-quality backlinks in WordPress, focus on creating amazing content and then reach out to reputable sites that are within your niche.

                                      WordPress plugins like Link Whisper can help you manage your internal links, but for the external ones, it’s all about building relationships. This is precisely why 74% of SEO experts generally end up paying for links, given that exact match anchors can get you five times more traffic.

                                      6. Content is King, But Context is Queen

                                      WordPress is all about content, and they say that content is king. But, let’s be real, context is definitely queen and she’s 100% running the show when it comes to SEO.

                                      Sure, publishing high-quality and relevant content is crucial, but if it comes without any context, you’ve pretty much got yourself an empty castle (or more accurately, no visitors).

                                      WordPress makes it super easy to create and manage SEO-optimized content with plugins like PrePostSEO, but don’t just focus on the keywords.

                                      What do I mean by this? You have to consider the user search intent and just how your content will fit into their journey. A well-placed blog or a “just-in-time” update can make a huge difference.

                                      So, let your content shine, but don’t forget who’s really calling the shots here: Queen content.

                                      Summary

                                      The internet is crowded, so mastering these WordPress SEO techniques is important for standing out.

                                      From smart keyword optimization to smart meta descriptions and building backlinks, there’s a WordPress plugin that’s there to make your SEO life easier. So, leverage what’s available to you but don’t forget the core universal tenants of SEO because they apply to WordPress the same as with any CMS.

                                      Remember, Google never sleeps, and neither should your strategy.