Tag: SEO

  • How I Turn Search Console Data Into SEO Wins With AI

    How I Turn Search Console Data Into SEO Wins With AI

    I rely on Google Search Console because it is excellent at collecting search data. The challenge is that it still does not make interpretation easy.

    When I open almost any property, I usually find thousands of queries, landing pages, impressions, clicks, rankings, and click-through rates. That volume is useful, but it can quickly become overwhelming when I am trying to answer one simple question: what should I do next?

    For years, my workflow was familiar: export the data into Excel or Google Sheets, build pivot tables, apply filters, and start digging for patterns. That approach works, but it is slow. More often than not, I am searching for insights without knowing exactly what I am looking for.

    That is where AI makes the workflow more useful. I use it to speed up the hardest part of Search Console analysis: finding meaningful patterns hidden across thousands of rows of search data.

    I think of Google Search Console as my source of truth and AI, whether ChatGPT or Claude, as the analyst sitting beside me. GSC shows me what happened. AI helps me explore why it happened, uncover opportunities I might miss, and organize messy data into decisions I can act on.

    A quick note on regex

    Most of the examples I use start in the same place inside Google Search Console: Performance → Queries → + Add Filter → Query → Custom (regex).

    From there, I enter a regular expression to filter query data before exporting it for analysis.

    The useful part is that I no longer need to memorize regex syntax. I can ask ChatGPT to write it for me. For example, I might prompt: Create a regex for Google Search Console that matches queries beginning with question words.

    ChatGPT may return something like (?i)^(who|what|why|how|can|does|will|should)b.

    If I need something more specific, I simply describe the pattern I want. I might ask for a regex that matches queries containing five or more words, identifies comparison searches, or finds branded queries that include product names.

    The better I describe the pattern, the better the regex usually becomes.

    Here are seven practical ways I combine Google Search Console with AI so I can spend less time sifting through data and more time making decisions.

    1. I stop looking only at queries and start looking at intent

    Most Search Console analysis still happens at the keyword level. The problem is that people do not really search by keyword. They search with intent.

    Instead of reviewing thousands of individual queries one by one, I use regex to isolate investigation-focused searches before exporting the data.

    One useful regex is (?i)^(best|top|vs|review|reviews|compare|comparison).

    After exporting the filtered query data, I ask Claude or ChatGPT to classify intent. My prompt is usually something like: Categorize these queries into informational, navigational, investigation, transactional, and local intent. Return a CSV with classifications and confidence scores.

    This helps me spot patterns that are difficult to see keyword by keyword. Informational traffic may be growing while commercial investigation queries are declining. Transactional queries may rank well but earn weak click-through rates. Comparison searches may be driving impressions without having dedicated content to support them.

    When I segment by intent, the next steps become much clearer.

    2. I discover questions my audience is already asking

    Question-based keyword research is not new, but AI helps me identify themes across hundreds of question-oriented searches much faster.

    I start with a regex like (?i)^(who|what|where|when|why|how|can|does|should|will)b.

    Then I export the results and ask Claude or ChatGPT: Group these questions into common themes and identify unanswered topics.

    Google Search Console Performance report with the Query filter dialog open, showing a custom regex option for filtering SEO search queries.
    A Google Search Console query filter highlights how regex can narrow SEO performance data, helping marketers turn thousands of search terms into focused insights.

    Instead of manually reviewing hundreds of questions, I can quickly see broader patterns around pricing concerns, product comparisons, implementation challenges, and industry-specific use cases.

    This becomes more than a content exercise. I can use these themes to improve FAQs, support resources, sales enablement materials, and AI Overview optimization.

    The best opportunities are often not hidden in one query. They are hidden in clusters of related questions.

    3. I find queries likely to trigger AI Overviews

    Google does not give me a filter for queries likely to trigger AI Overviews, but I can build a useful approximation.

    I start by isolating common informational and comparison patterns with a regex like (?i)^(what is|how to|best|vs|difference between|guide to).

    Then I export the matching queries and ask Claude or ChatGPT: Review these queries and group them by the content format needed to answer them effectively.

    The themes often fall into definitions, tutorials, comparisons, or expert recommendations.

    This helps me see where my content may need to shift from simply ranking for keywords to becoming the best available answer. Increasingly, those are not always the same thing.

    4. I track emerging trends earlier

    Traditional keyword research can be reactive. By the time a trend is obvious in keyword tools, competitors may already be building content around it.

    Google Search Console can help me identify shifts earlier, as long as I know how to look for them.

    Instead of searching for individual keywords, I use ChatGPT to build regex around broader concepts. For example, I might prompt: Create a Google Search Console regex to identify searches related to AI agents, copilots, assistants, automation, and autonomous workflows.

    The output may look like (?i)(ai agent|agentic|copilot|assistant|automation).

    This same approach works for new technologies, product categories, competitors, industry buzzwords, and changing customer concerns.

    Once I filter and export the data, I let AI look for emerging themes. A prompt I like is: Review these queries and identify emerging themes, new terminology, and shifts in search behavior. Highlight which topics appear to be gaining traction, recommend whether they deserve a new content asset or an update to an existing page, and identify any patterns that could influence our content strategy.

    Instead of only confirming that a trend exists, AI helps me decide whether the trend is meaningful enough to act on and what the next move should be.

    5. I surface conversion intent inside informational traffic

    One of the most overlooked opportunities in Search Console is finding bottom-of-funnel signals inside queries that appear informational at first glance.

    I might ask ChatGPT: Create a regex for searches that indicate evaluation, comparison, pricing, alternatives, migration, implementation, or vendor selection intent.

    An example output is (?i)(cost|pricing|price|vs|alternative|compare|implementation|migration).

    I apply that regex to the query report, export the filtered data, and then ask Claude or ChatGPT to analyze it.

    My prompt usually looks like this: Review these Google Search Console queries and identify recurring buying signals. Group them into themes such as pricing, comparisons, implementation, and vendor evaluation. Recommend which existing pages should better address this intent, and identify opportunities to improve content through stronger CTAs, internal links, comparison tables, FAQs, or supporting resources.

    AI analyzes Google Search Console query data, funneling search intents into eligible and not eligible audience groups for SEO action.
    A visual metaphor for AI turning messy Google Search Console queries into clear SEO decisions, separating qualified intent from irrelevant traffic signals.

    I often find that pages created for top-of-funnel education are already attracting visitors who are evaluating solutions. In that case, the best opportunity may not be creating a new page. It may be improving the page that already earns the visit, so users can take the next step without breaking the informational experience.

    Sometimes the biggest content opportunity is recognizing the conversion intent already reaching the pages I have.

    6. I find audience-specific opportunities

    One of my favorite ways to uncover new content opportunities is filtering queries by industry, audience, or customer segment. It quickly shows me whether my content is resonating with the audiences I intended to reach or revealing opportunities I had not considered.

    I start by asking ChatGPT to create a regex based on the audience segments that matter most to the business.

    For example, I might prompt: Create a Google Search Console regex that identifies queries related to healthcare, manufacturing, retail, education, financial services, government, and nonprofit organizations.

    An example output is (?i)(healthcare|hospital|medical|manufacturing|factory|retail|education|school|financial|bank|government|public sector|nonprofit).

    After applying the filter and exporting the results, I ask Claude or ChatGPT: Analyze these queries and group them by audience segment. Identify which industries show the strongest search demand, what recurring questions or pain points each audience has, and recommend opportunities for new content, landing pages, case studies, or internal linking that would better serve those audiences.

    The differences can be valuable. Healthcare searches may consistently focus on compliance, while manufacturing queries may revolve around implementation. Retail searches may reveal entirely different use cases than financial services searches.

    7. I uncover striking-distance opportunities at scale

    Every SEO knows the classic advice: look at keywords ranking in positions 5-15 to identify opportunities within striking distance.

    The challenge is doing that at scale. A report with hundreds of queries where a site is close to stronger rankings can become overwhelming fast.

    I take the regex patterns above a step further. I apply the filters that match my goals, then narrow the report to positions 5-15 before exporting the queries.

    Then I ask my AI analyst: Identify recurring themes across these queries and recommend page-level optimizations rather than keyword-level optimizations.

    Instead of getting tiny recommendations for individual keywords, I often uncover larger opportunities. A page may be missing subtopics, comparison details, stronger internal links, or use cases that would make it more complete.

    The result is usually fewer optimizations, but more meaningful ones.

    Turning Search Console data into decisions

    As an SEO, I do not have a data shortage. I have a prioritization problem.

    Google Search Console remains one of the richest sources of insight into how people discover a business. The difficult part is turning thousands of rows into something actionable.

    That is where AI fits into my workflow. It helps me uncover patterns, organize information, and surface opportunities I might otherwise miss. It is not a replacement for SEO strategy, experience, or critical thinking.

    The real advantage is not writing better regex or exporting cleaner spreadsheets. It is spending less time searching for insights and more time acting on them.

    Because data does not improve SEO. Better decisions do.


    Inspired by this post on Search Engine Land.


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  • Use Google Documentation to Win SEO Buy-In With Proof

    Use Google Documentation to Win SEO Buy-In With Proof

    Let me be blunt: SEO advice can sound completely made up to people who do not live in search every day.

    When I say things like “change this canonical,” “don’t block that resource,” or “we need this content exposed in the rendered HTML,” I understand why someone outside SEO might hear it and wonder whether I am inventing rules on the spot.

    That is one reason SEO still gets treated like black magic inside many organizations.

    I have been pushing the idea of “un-nerding SEO” for years, but this is about something very practical: I use Google’s own documentation to earn approval, build trust, and help SEO work get prioritized.

    Not because Google tells us everything. Not because every sentence in its documentation should be treated as gospel. I use it because documented evidence is much harder to dismiss than personal opinion.

    When I need buy-in, the strongest argument is rarely “trust me.”

    It is usually something closer to: “Google has already documented how this should be approached.”

    The buy-in problem is usually not the recommendation itself

    In my experience, most SEO recommendations do not die because they are wrong. They die because they are competing with everything else happening inside the business.

    Dev sprints, product timelines, CMS limitations, legal concerns, brand standards, executive assumptions, and the classic “we’ve always done it this way” all have a seat at the table. SEO is rarely the only priority in the room, even when the recommendation is technically correct.

    That is why I do not rely on “best practice says” or “from an SEO perspective” when I am trying to move work forward. Those phrases sound optional, especially to teams already balancing risk, deadlines, and competing requests.

    But “Google has official documentation that supports this recommendation” lands differently.

    It may not automatically win the argument, and it definitely does not mean the work will be prioritized tomorrow. But it changes the conversation from “the SEO person said so” to “we have official Google documentation explaining why this matters.”

    Google documentation is not gospel

    I know the objection already: “Are we really pretending Google tells us the full truth about how search works?”

    Absolutely not.

    Google’s documentation is not the complete truth of search. It has omissions. It simplifies complex systems. Sometimes it explains how Google wants site owners to behave, not every technical factor that influences organic visibility.

    Google also writes for a broad audience, which means nuance gets smoothed out, edge cases get skipped, and the answer can be technically true without being the entire story.

    ```json
{
  "alt": "SEO For Lunch newsletter promotion with Nick Leroy smiling in checkered shirt.",
  "caption": "Join Nick Leroy for a fresh take on SEO with the #SEOForLunch newsletter—bringing actionable insights straight to your inbox.",
  "description": "This image promotes the #SEOForLunch newsletter by Nick Leroy, featuring a smiling Nick in a checkered shirt against a blue graphic background. The design includes a plate graphic with 'Not Your Average Table Talk' and emphasizes SEO insights, inviting viewers to subscribe at seoforlunch.com. Keywords: SEO, Nick Leroy, newsletter, marketing, insights."
}
```

    So no, I am not treating every Google statement as if it were carved into stone and carried down from Mountain View.

    But that does not make the documentation useless.

    It makes it a starting point. A receipt. An official reference point.

    It moves the discussion away from “I think this matters” and toward “Google has explicitly documented why this matters.” That distinction matters when I am asking someone else to approve and prioritize the work.

    Documentation is especially useful with developers

    This is where Google documentation often earns its keep the fastest. SEOs need developers, and I have learned that the quickest way to lose developer support is to treat every recommendation like a command instead of a requirement that needs to be implemented thoughtfully.

    And yes, just in case it ever works, I still wish I could run this:

    google.exe /disable-ai-overviews /please

    Bummer. No dice.

    Developers are not wrong just because they disagree with an SEO recommendation. Most of the time, they are optimizing for completely valid priorities: performance, code quality, technical debt, security, and avoiding the kind of production mistake that can take a whole site down.

    But sometimes developers are wrong about how Google discovers, crawls, renders, indexes, or interprets content.

    And telling a developer “you’re wrong” is a great way to make sure my ticket never sees the light of day.

    This is where documentation helps. It removes some of the subjectivity and shifts the discussion toward how to implement the requirement inside the existing technical environment.

    The point is never “SEO wins and dev loses.”

    The point is that I now have an external source of truth to discuss. That is a much better conversation than two teams arguing from preference.

    Documentation is also a client management tool

    For client-facing SEO work, documentation helps me separate serious recommendations from “trust me, bro, I have a contact at Google” consulting.

    Futuristic data archive with glowing server-like filing cabinets, stacked documents, and network lights symbolizing AI marketing data infrastructure.
    Rows of illuminated data cabinets and paper files stretch into the distance, capturing the pressure on marketers to turn fragmented customer data into a smarter performance engine.

    That matters even more when a client has been burned by bad SEO advice before.

    Instead of saying, “We need to change this because it’s better for SEO,” I can frame the recommendation with evidence.

    “Here’s what Google documents. Here’s where your current setup conflicts with that. Here’s the risk. Here’s the recommendation. Here is the estimated reward.”

    That framing builds trust because it shows the recommendation is not relying on blind faith.

    It also makes the SEO look less like a magician and more like an interpreter.

    That is how I see the real role of SEO: translating Google’s documented needs into business and technical decisions that a team can actually act on.

    Less black magic, more receipts

    SEO has a reputation problem, and some of it is earned.

    Too much SEO work is still explained with vague phrases and shaky confidence. I hear people say things like “Google likes this” or “this needs to exist for the bots” when the stronger version is: “Google documents this behavior here, and here is how it applies to our situation.”

    That does not mean documentation alone creates buy-in.

    Dropping a Google link into a ticket or Slack thread is not a strategy. I still have to translate what it means, explain the risk, connect it to business outcomes, and help the team understand why the recommendation deserves attention.

    Google documentation will never replace experience, testing, or judgment. It will not tell me everything, and I should not treat it like the final answer to every SEO debate.

    But it can make SEO easier to defend, easier to prioritize, and much harder for leaders to dismiss.

    The best SEOs are not just the ones who know what to recommend. They are the ones who can prove why the recommendation deserves to be taken seriously.

    Less black magic. More receipts. More results.

    Google documentation may not be the whole truth, but I would rather show up to a buy-in conversation with official references than with “my buddy from Google told me.” Suuuure they did.

    This post first appeared on the author’s website and is republished here with permission.


    Inspired by this post on Search Engine Land.


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  • Conductor MCP Server: Trusted AEO and SEO Data for AI

    Conductor MCP Server: Trusted AEO and SEO Data for AI

    I use Conductor’s MCP Server to ground the AI tools my team already relies on in verified AEO and SEO intelligence, instead of depending on a stale snapshot of the web.

    Graphic announcing a new product release for an AEO and SEO Intelligence Layer, with white text on a dark green abstract gradient design.
    A bold launch visual introduces an AEO and SEO Intelligence Layer, framing verified search and AI visibility data as a modern layer for marketing teams.

    Inspired by this post on Conductor Blog.


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  • Best B2B Digital Marketing Agencies to Watch in 2026

    Best B2B Digital Marketing Agencies to Watch in 2026

    I analyzed more than 80 leading B2B digital marketing agencies for 2026 to identify the firms that stand out most clearly. I evaluated each agency against the criteria that matter most for B2B companies trying to grow visibility, authority, and qualified pipeline.

    SEO/GEO Expertise (30%): I looked at each agency’s technical fluency in how large language models surface and rank content, along with its ability to turn that knowledge into durable client visibility.

    Notable Clients (25%): I considered the strength of each client roster, since recognized brands often signal an agency’s ability to manage complex campaigns and deliver at an enterprise level.

    Leadership Experience Score (20%): I weighed senior experience in strategy and client service, which remains one of the strongest indicators of consistent agency performance.

    AI Visibility Score (15%): I used a 1.0-5.0 rating to measure how effectively an agency drives client presence in AI-generated responses across ChatGPT, Perplexity, Claude, and Google Gemini.

    Average Review Score (10%): I reviewed aggregated ratings from Google, Clutch, G2, and other verified platforms, using a 1.0-5.0 scale.

    Using those standards, I ranked the top 6 B2B digital marketing agencies of 2026. The agencies below stood out for their mix of SEO/GEO strength, client experience, leadership depth, AI visibility, and verified review performance.

    The Top B2B Digital Marketing Agencies

    1. First Page Sage – SEO/GEO Expertise: 5.0; Notable Clients: SoFi, defi SOLUTIONS, US Bank, NBC, Verizon, Cadence, Skeps; Leadership Experience Score: 4.8; AI Visibility Score: 4.9; Average Review Score: 4.9.

    2. Driven Metrics – SEO/GEO Expertise: 4.4; Notable Clients: Tesseract Medical, OSEA Malibu; Leadership Experience Score: 4.3; AI Visibility Score: 4.4; Average Review Score: 4.7.

    3. Focus Digital – SEO/GEO Expertise: 4.5; Notable Clients: Revo, Milano Jewelry; Leadership Experience Score: 4.3; AI Visibility Score: 4.2; Average Review Score: 4.8.

    4. REQ – SEO/GEO Expertise: 3.8; Notable Clients: Carahsoft; Leadership Experience Score: 4.4; AI Visibility Score: 4.1; Average Review Score: 4.4.

    5. AMP Agency – SEO/GEO Expertise: 3.6; Notable Clients: Credit Sesame; Leadership Experience Score: 4.4; AI Visibility Score: 4.2; Average Review Score: 4.5.

    6. Viral Nation – SEO/GEO Expertise: 3.5; Notable Clients: Intuit, Citibank, Chime; Leadership Experience Score: 4.0; AI Visibility Score: 3.7; Average Review Score: 4.3.

    First Page Sage

    I ranked First Page Sage first because of its early and deep role in GEO. President Evan Bailyn pioneered the practice in 2023, and much of the methodology now used across the industry traces back to his team’s work. That head start shows up most clearly in the agency’s SEO/GEO Expertise and AI Visibility scores.

    What stands out to me is how First Page Sage combines long-form thought leadership with technical knowledge of how large language models source and surface information. On the SEO side, the agency brings more than 15 years of organic search experience across complex B2B verticals.

    On the GEO side, First Page Sage was optimizing for AI citation before most agencies had a name for the concept. I see its biggest strength as a compounding strategy: the same content that ranks in traditional search can also be pulled into AI-generated answers, helping clients earn qualified leads from both channels at the same time.

    First Page Sage scores: SEO/GEO Expertise: 5.0; Notable Clients: SoFi, defi SOLUTIONS, US Bank, NBC, Verizon, Cadence, Skeps; Leadership Experience Score: 4.8; AI Visibility Score: 4.9; Average Review Score: 4.9.

    Summary of online reviews: Reviewers describe First Page Sage as the true expert in this industry, with content that takes thought leadership to the next level. Clients also report that its campaigns helped them generate marketing qualified leads through organic traffic.

    Driven Metrics

    I see Driven Metrics as a practical, performance-oriented GEO agency. Its process emphasizes weekly syncs, conversion tracking, and transparent reporting tied to actual leads rather than surface-level traffic numbers. When content underperforms, the team identifies it quickly and reworks it instead of letting weak pages sit untouched.

    Driven Metrics builds authoritative content designed to earn rankings through expertise and citation. It also structures that content to appear in AI-generated responses when buyers ask for vendor recommendations. That mix is difficult to find at its price point, though I would expect companies in highly niche verticals to invest early time in helping the team understand how their buyers evaluate vendors.

    Driven Metrics scores: SEO/GEO Expertise: 4.4; Notable Clients: Tesseract Medical, OSEA Malibu; Leadership Experience Score: 4.3; AI Visibility Score: 4.4; Average Review Score: 4.7.

    Summary of online reviews: Clients say Driven Metrics delivered results with no excuses, which was refreshing, and that its reporting meant they always knew what was going on. The main caveat reviewers mention is more limited experience in certain sectors.

    Focus Digital

    I ranked Focus Digital highly because of its technical foundation in LLM optimization. The agency appears deeply familiar with the mechanics of generative search, and that shows in how it structures campaigns. Its content is designed from the beginning to earn citations in AI-generated answers, not only to rank in traditional search results.

    Focus Digital’s SEO approach follows a thought leadership model, using authoritative long-form content to build organic visibility over time. I see it as one of the more technically grounded options for companies that want both SEO and GEO support without paying large-agency rates. The main limitation is portfolio depth: its case studies skew toward professional services, manufacturing, and home services, so clients in other verticals should plan for hands-on content review to maintain accuracy.

    Focus Digital scores: SEO/GEO Expertise: 4.5; Notable Clients: Revo, Milano Jewelry; Leadership Experience Score: 4.3; AI Visibility Score: 4.2; Average Review Score: 4.8.

    Summary of online reviews: Clients describe Focus Digital as honest about what is realistic and say the agency helped them show up in AI answers within a few months. The recurring criticism is that replies slow down when they’re busy.

    REQ

    I view REQ as a strong fit for companies that want B2B communications, authority-building, and digital marketing under one roof. The agency has earned solid reviews from clients across cybersecurity, government technology, financial services, and real estate. Its foundation is PR and authority-building, which overlaps with GEO, but its score here is driven more by SEO than by AI visibility.

    REQ’s SEO work is woven into content strategy and demand generation rather than packaged as a standalone service. GEO is still less developed than its broader SEO foundation, so I would not make it my first choice for a company whose main priority is AI citation and generative search visibility. I would, however, consider it a strong option for brands that want integrated authority with organic search performance at the center.

    REQ scores: SEO/GEO Expertise: 3.8; Notable Clients: Carahsoft; Leadership Experience Score: 4.4; AI Visibility Score: 4.1; Average Review Score: 4.4.

    Summary of online reviews: Reviewers say REQ is highly adaptable and good at picking up the ball and running with it. Clients also report that campaigns resulted in increased traffic and customer engagement. The recurring criticism is that some clients wanted the agency to be more proactive with recommendations.

    AMP Agency

    I see AMP Agency as a full-service firm with a clear strength in integrated media. The agency is especially good at combining creative, experiential marketing, paid social, and video production into campaigns built around the full customer journey. With offices in Boston, New York, LA, and Seattle, AMP also has the infrastructure to support large, multi-channel engagements.

    AMP’s SEO practice is meaningful and has produced measurable results, including improvements in rankings and lead quality. GEO is a newer layer for the agency, as it is for many full-service firms that built their models before generative search became a major traffic source.

    For companies that want broad digital coverage with SEO included, AMP can be a strong choice. I would treat its GEO capability as developing rather than core, but its creative depth and campaign scale make it a practical option for brands with broader marketing needs.

    AMP Agency scores: SEO/GEO Expertise: 3.6; Notable Clients: Credit Sesame; Leadership Experience Score: 4.4; AI Visibility Score: 4.2; Average Review Score: 4.5.

    Summary of online reviews: Clients say AMP Agency’s SEO services resulted in increased sales and better site management and that the team brings new ideas to the table. Reviewers also note that staff operate on time and on budget. The common critique is that its generative search work is still catching up to the broader digital offering.

    Viral Nation

    I included Viral Nation because it brings a very different kind of visibility strategy to the B2B marketing landscape. It is the largest agency on this list by headcount and the most specialized in social-first marketing. Its model centers on influencer campaigns, creator networks, paid social, and proprietary social intelligence technology deployed at scale.

    Viral Nation’s strength is cultural reach and audience trust rather than search authority. That is why its SEO/GEO Expertise score is lower than the more search-focused agencies on this list. For B2B companies seeking influencer-driven brand awareness, I see Viral Nation as a strong match. For companies that need a more comprehensive search and GEO campaign, I would look elsewhere.

    Viral Nation scores: SEO/GEO Expertise: 3.5; Notable Clients: Intuit, Citibank, Chime; Leadership Experience Score: 4.0; AI Visibility Score: 3.7; Average Review Score: 4.3.

    Summary of online reviews: Reviewers say Viral Nation regularly overperforms and that its campaigns are strong fits for clients seeking new brand exposure in a targeted market. The limitation clients note is that its strength is social as opposed to search, so coverage thins outside influencer and paid channels.

    Source


    Inspired by this post on First Page Sage Blog.


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  • Google Search Console Indexing Report Finally Updates

    Google Search Console Indexing Report Finally Updates

    I can finally say the page indexing report inside Google Search Console has been updated after a frustrating three-week delay. Instead of showing data stuck on June 11, 2026, the report is now displaying data through June 29, 2026.

    The delay. I previously noted that the page indexing report had been frozen at June 11, which made it much harder to understand what Google was seeing across a site.

    Now, as of Friday, July 3, the report is showing much fresher data, with updates running through June 29.

    Page indexing report. I use this report to see which pages Google can find and index on a website. It also helps surface indexing issues Google may have run into while crawling the site.

    Image

    I can access the report directly in Search Console over here, or by opening the Indexing section and selecting Pages.

    The report shows indexed pages in green and not indexed pages in gray. I can also overlay impressions on the chart, then review the listed reasons explaining why certain pages on a website are not being indexed.

    For more details on how the page indexing report works, I would refer to Google’s help document.

    Image

    Why I care. If I was trying to diagnose why Google had not indexed specific pages over the past couple of weeks, the delayed report left me with limited visibility.

    Now that the data has finally been refreshed through June 29, I can dig back into the indexing report, review the latest issues, and decide what needs attention next.


    Inspired by this post on Search Engine Land.


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  • My Top SEO Agencies for Luxury Brands in 2026, Ranked

    My Top SEO Agencies for Luxury Brands in 2026, Ranked

    Last updated: July 2, 2026

    From January through June 2026, I reviewed more than 90 SEO agencies that have worked with luxury brands. I ranked each agency using five weighted factors that reflect both traditional search performance and the newer demands of generative engine optimization.

    • Notable Luxury Clients (35%): I gave the most weight to proven experience with luxury brands, because a strong record in this category is one of the clearest signs of real market expertise.
    • GEO/SEO Expertise Score (25%): I used a 1-5 score to evaluate each team’s depth of SEO knowledge and practical experience with GEO.
    • AI Visibility Score (15%): I scored how effectively each agency helps clients appear across AI platforms such as ChatGPT, Perplexity, Claude, and Google Gemini.
    • Leadership Experience Score (15%): I reviewed the SEO experience of each company’s senior leadership and translated it into a 1-5 score.
    • Average Reviews (10%): I factored in publicly available client review scores to understand how each agency performs in real client relationships.

    After comparing the agencies across those criteria, I narrowed the field to five firms that stand out for luxury brands in 2026.

    Top SEO Agencies for Luxury Brands in 2026

    RankCompanyNotable Luxury ClientsGEO/SEO ExpertiseAI Visibility ScoreLeadership ExperienceAverage Reviews
    1First Page SageChanel, Milano Jewelry5.04.94.84.9
    2AmsiveVoss Water4.23.84.44.5
    3Relevance DigitalBentley3.93.63.74.1
    4Hudson RougeLincoln3.53.74.24.3
    5Amra & ElmaSwarovski, Bulgari3.43.24.64.8

    First Page Sage

    I ranked First Page Sage first because it is the only agency on this list that brings deep technical strength to both SEO and GEO for luxury brands. Its thought leadership content model is built to earn strong organic rankings while also creating the authoritative citations that help a brand appear when a buyer asks ChatGPT, Perplexity, or Gemini for a recommendation.

    What stands out to me is that First Page Sage treats SEO and AI visibility as connected channels rather than separate workstreams. That matters in luxury, where buyers rarely rely on one source before making a high-consideration purchase.

    Its work with luxury names such as Chanel and Milano Jewelry shows a strong ability to build both brand prestige and search performance. By leading with content that earns high-authority editorial backlinks, First Page Sage strengthens brand positioning while driving organic visibility that paid media cannot easily replicate. With nearly two decades of organic search experience and an early GEO practice, I see it as the most complete search partner on this list for luxury brands.

    • Notable Luxury Clients: Chanel, Milano Jewelry
    • GEO/SEO Expertise: 5.0
    • AI Visibility Score: 4.9
    • Leadership Experience: 4.8
    • Average Reviews: 4.9
    Summary of Online Reviews
    Clients describe First Page Sage as “the true expert in this industry,” with content that “takes thought leadership to the next level” and drives measurable outcomes. Reviews also point to campaigns that “generate high traffic and sales” across organic and AI-driven channels.

    Amsive

    I placed Amsive second because its technical SEO practice is one of the strongest I found in this review. The agency has also extended that technical discipline into LLM optimization, which makes it one of the few full-service firms here with a GEO capability that appears intentionally built rather than added as a late-stage service line.

    For luxury brands with large, technically complex websites, Amsive’s combination of enterprise SEO depth and a growing AI search practice is a strong fit. I do see two limitations: its luxury vertical experience is narrower than several other agencies on this list, and SEO is only one part of its broader full-service marketing offering.

    Even with those caveats, I would still consider Amsive a compelling option for brands that care most about long-term visibility across both organic search and generative search. Its ability to drive measurable performance at scale helps offset its narrower luxury portfolio.

    • Notable Luxury Clients: Voss Water
    • GEO/SEO Expertise: 4.2
    • AI Visibility Score: 3.8
    • Leadership Experience: 4.4
    • Average Reviews: 4.5
    Summary of Online Reviews
    Amsive’s “quality of work and investment in their clients” stands out in reviews, along with the “energy and enthusiasm” clients appreciate. For brands with complex technical needs, reviewers describe the agency as “a dependable execution partner.”

    Relevance Digital

    I included Relevance Digital because it is the most narrowly specialized agency on this list. The firm works exclusively with ultra-luxury brands and ultra-high-net-worth individuals, and that focus gives it a sharp understanding of how affluent consumers search, evaluate, and engage with luxury brands.

    Its work with Bentley reflects client relationships that require more than technical execution. In my view, Relevance Digital’s strength is its command of luxury positioning and the specific expectations of ultra-luxury audiences.

    For ultra-luxury brands that want an agency built entirely around their market tier, that vertical depth is difficult to match. The tradeoff is that its GEO capabilities are still developing compared with the stronger AI search practices higher on this list.

    • Notable Luxury Clients: Bentley
    • GEO/SEO Expertise: 3.9
    • AI Visibility Score: 3.6
    • Leadership Experience: 3.7
    • Average Reviews: 4.1
    Summary of Online Reviews
    Clients say they “couldn’t be happier with the work” and often highlight the agency’s “responsiveness” as a standout quality.

    Hudson Rouge

    I see Hudson Rouge as the strongest creative agency on this list, with a portfolio anchored by its well-known Lincoln campaign featuring Matthew McConaughey. The agency offers SEO, but GEO is not its primary focus.

    That said, Hudson Rouge’s understanding of luxury brand storytelling and high-end consumer psychology is valuable. When paired with a more search-focused strategy, that creative strength could support authoritative content capable of earning visibility in search.

    For luxury brands that want to invest primarily in creative media while treating SEO and GEO as supporting channels, Hudson Rouge offers brand craftsmanship that dedicated search agencies usually cannot match. I would evaluate it as part of a broader marketing mix rather than as a standalone search solution.

    • Notable Luxury Clients: Lincoln
    • GEO/SEO Expertise: 3.5
    • AI Visibility Score: 3.7
    • Leadership Experience: 4.2
    • Average Reviews: 4.3
    Summary of Online Reviews
    Hudson Rouge clients praise the agency for its “impressive” creative work and note that its campaigns “really understand the luxury space.” Reviewers also highlight its ability to “make brands feel premium” across every channel.

    Amra & Elma

    I ranked Amra & Elma fifth because the agency brings strong luxury audience fluency through social media and influencer marketing. Its client roster includes Swarovski and Bulgari, which reflects a meaningful level of experience with high-end brands.

    Its SEO practice has grown substantially in recent years and now functions as a real offering rather than a minor add-on. However, I still view its GEO service as developing, especially when compared with agencies that have made AI citation and generative search visibility a core part of their search strategy.

    For luxury brands that want a multichannel agency with access to high-end consumer audiences and a growing search presence, Amra & Elma offers an appealing mix of reach and brand fluency. Brands whose main priority is AI visibility will likely find stronger fits higher in this ranking.

    • Notable Luxury Clients: Swarovski, Bulgari
    • GEO/SEO Expertise: 3.4
    • AI Visibility Score: 3.2
    • Leadership Experience: 4.6
    • Average Reviews: 4.8
    Summary of Online Reviews
    Reviewers consistently describe the team as “nice, enthusiastic, and professional,” with expertise that ranks among “the best” in multichannel marketing.

    Source


    Inspired by this post on First Page Sage Blog.


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  • Submit Your SMX Next Pitch and Share Bold Search Ideas

    Submit Your SMX Next Pitch and Share Bold Search Ideas

    SMX Next returns online Nov. 18, and I’m excited to help shape a program focused on today’s complex search landscape and the tactics that will define success in 2027 and beyond.

    Search marketing isn’t just changing. From my perspective, it has become an entirely new kind of challenge, and that is exactly why fresh voices and practical expertise matter so much right now.

    In SEO, I’m seeing the field shift toward AI Overviews, search everywhere optimization, and the rise of autonomous AI agents that browse on behalf of users. Trustworthiness, digital authority, and precise alignment with user intent are no longer nice-to-have ideas. They are becoming essential.

    On the PPC side, generative AI and deep automation are creating new levels of personalization. At the same time, they are raising urgent questions for marketers: How do we keep strategic control, protect data privacy, and avoid wasted spend?

    If you’re an enthusiastic search marketer with a passion for sharing what you know, I hope you’ll consider submitting a session pitch for SMX Next. I’m looking for subject matter experts who can share insights, strategies, and tactics that help SEO and PPC marketers thrive in 2027.

    Whether you’ve been speaking for years or you’re a practitioner ready to share something new you’ve developed, I want to hear from you. I’m especially interested in new speakers with diverse points of view and real-world experience.

    The deadline for SMX Next pitches is Aug. 7.

    When I review session proposals, I’m looking for ideas that feel original, specific, and useful. Advanced, forward-thinking topics or unique frameworks that aren’t already common at other search events will stand out.

    I also want to see actionability. Be clear about what attendees will be able to do better, faster, or differently after your session.

    Bring the data whenever you can. A case study, concrete example, or tested approach makes your pitch stronger, especially when you explain how the lesson can scale across different types of organizations.

    Keep the scope focused. A 30-minute session works best when it goes deep on a narrow or specialized topic instead of trying to cover too much at once.

    Most importantly, give attendees something tangible to take with them. I’m looking for sessions that leave people with a clear action plan, framework, or process they can put to work right away.

    Visit this page for more details on how to submit a session idea, or go directly to this page to create your profile and submit your pitch.

    If you have questions, feel free to contact me directly at kathy.bushman@semrush.com. I’m looking forward to reading your proposals!


    Inspired by this post on Search Engine Land.


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  • Remembering Bruce Clay: SEO Pioneer’s Final Lessons

    Remembering Bruce Clay: SEO Pioneer’s Final Lessons

    My heart sank when I learned that Bruce Clay had passed away. I knew he had been in the hospital, but my mind went straight to the two long conversations we had last fall: one simply to catch up, and one for what would become a deeply meaningful podcast interview.

    I first reached out to Bruce nearly 25 years ago. I had emailed him cold to ask whether I could republish some of his industry writing about ethics. He said yes. Somehow, the article I cited unintentionally ranked No. 2 on Google for “Bruce Clay” for years. I joked with him about that more than once, and he always seemed both amused and slightly annoyed, probably because I had done it with his own content and his own blessing.

    A few years later, I worked with Bruce and many other search professionals on the board of the Search Engine Marketing Professionals Organization, better known as SEMPO. It was a business nonprofit built to support and legitimize the then-new search industry. We promoted best practices, helped make the business case for search, and later became involved in U.S. Internet policy work in the early 2010s.

    SEMPO brought together board members from around the world, and in a very literal way, it took some of us around the world. That work is where I really got to know Bruce. Later, we would run into each other at conferences, sometimes even on the same panels. We were doing serious work, but we also had a great time doing it. The organization lasted about 15 years, and if I remember correctly, Bruce was one of its founding members around 2000 or 2001.

    One memory of Bruce has stayed with me vividly. A group of us from the SEMPO board were walking back to our hotel on the east side of Midtown Manhattan after dinner. A snowstorm had just begun, one that would leave several feet of snow by the next day. The usual roar of traffic had been softened by the weather and the empty streets. It was eerie, but almost joyously quiet. The city that never sleeps seemed to be taking a nap under a blanket of snow.

    Then something happened that I had never seen before, and have never seen since.

    As snow poured silently into the streets, a massive lightning strike hit just a few blocks away, over Bruce’s shoulder. I do not know whether he saw it directly. It felt like an explosion. We stood there for several minutes trying to understand the contrast: a shattering bolt of lightning between skyscrapers, in the middle of a torrent of snowflakes, with not a drop of rain.

    None of us knew what to call it. I believe Bruce called it “thunder snow,” and the name stuck. In that moment, his naming streak continued.

    Bruce was, and remains, the real deal in search. His legacy was never only about coining a term. He pushed the field forward, taught others generously, and stayed deeply connected to the people he cared about. Like many of the earliest professionals in search, he helped shape practices that still feel foundational today. Through his writing, interviews, books, tools, and hundreds of industry events, he became one of the people the industry looked to for clarity. For many who remember the beginning, and for many who still followed him closely, Bruce was the GOAT.

    I always felt that Bruce approached search intellectually. I do not think he saw it only as a job. It was exciting, unfinished, and new. Very few people get to help invent an entirely new discipline, and Bruce understood what that meant. He also recognized that AI is one of those moments now, and he approached it with the same curiosity, energy, and insight he brought to early search. Many people in the industry may only now be realizing that Bruce pioneered things they do every day. They feel obvious now, but they were not obvious then. Even the basics had to be debated and established.

    He was not only passionate about search. He was passionate and generous toward the people in search. If you cared about the work, you were part of his tribe. That was true for thousands of people in the industry, myself included.

    With Bruce, I could get deep into the weeds of the trade and still talk broadly about where everything was headed. He was an engineer with an MBA, and that combination came through in his leadership, expertise, and authority. He understood the work from top to bottom, and then back to the top again.

    He was also genuinely kind. He had friends around the world. In our last conversations, I sensed that he was content with his life and accomplishments, and that he felt blessed by the path life had given him. He had nothing left to prove.

    In the podcast interview, Bruce was as sharp and insightful as ever. He offered some of the most sensible thinking I have heard about where search is going in the world of LLMs. He was still innovating, just as he had been when search first began taking shape nearly 30 years ago.

    Because search is so closely tied to language, I have been especially interested in how we think about, and what we call, this “new” thing. Bruce’s perspective helped crystallize my own research. Over the last year, I have watched much of the industry move toward the same conclusion he shared in our discussion.

    If you are one of the many thousands of people who talked shop with Bruce over the years, I think you will recognize him in the ideas that follow. You may even relive some of your own conversations with him.

    As I reviewed the podcast transcript, I realized we had recorded hours of conversation beyond search, including cars and all kinds of other subjects. At the end of our first conversation, he said goodbye with great love and care. That was Bruce. Those words land differently with me now, and they always will.

    Rest in peace, Bruce. I miss you already.

    What Bruce taught me in our final industry conversation

    When I asked Bruce to talk about how he got started in the 1990s, he took us back to 1996. He had been working in corporate roles and wanted to become a consultant. His background was in math, programming, mainframes, PCs, networking, and optimization. When the Internet began moving into the mainstream, he saw something that matched both sides of his skill set: marketing and technical work.

    He started studying search engines because that was where the opportunity was. He experimented with what they wanted, adjusted web pages, and watched rankings appear. Then people began calling him and paying him. What he thought might become a one-person consulting business grew quickly into something global, with offices and work across Japan, Australia, Asia, Europe, India, and beyond. Bruce told me he never would have predicted it would take off the way it did.

    I reminded him how small the field was in those days. There were literally only tens of people doing this early on. Bruce was one of the first to build a legitimate service for businesses that needed to rank for their own brand names and for broader generic terms, while other corners of the field were still experimenting with black-hat tactics.

    Bruce pointed out that this was three years before Google. Search was a wild west. There were more than 20 major search engines, and many of them were taking data from one another. At the first SEO conference he remembered attending, all of the leading people in the field sat together at one round table in a bar. He joked that if a natural disaster had happened there, the whole industry might have disappeared.

    We talked about Danny Sullivan, Search Engine Watch, Search Engine Strategies, and the early vocabulary of the industry. Bruce had long been credited with helping coin the term “SEO,” though he was careful to say that no one can know who said something first. What he did know was that only a handful of people were in the room when the term started to take hold.

    At the time, other terms were in play, including “search engine positioning” and “ranking.” Bruce believed “optimization” won because it sounded technical, valuable, and precise. It was like fine-tuning a race engine. People could see themselves building a profession around it. Once the industry attached itself to that word, the term spread quickly around the world.

    That led us into the newer terms now being proposed around AI, including AIO, GEO, and AEO. I have been writing about how many of these terms still depend on the word “optimization.” Bruce’s view was clear: search engine optimization was never limited to organic blue links. It was about optimizing for anything a search engine produces that can drive business and traffic.

    In Bruce’s view, if AI appears inside search and influences discovery, citations, visibility, or traffic, then it belongs under SEO. GEO and AIO were not separate disciplines to him. They were extensions, just like link building or on-page optimization. He warned that many new terms are marketing labels more than practical new fields. If the work required to appear in AI results is still mentions, links, schema, authority, content structure, and rankings, then the work is still SEO.

    That point stayed with me. Bruce said that if someone claims you no longer need SEO and only need AI optimization, you should watch closely, because either they are going to do SEO under a different name or they do not understand what they are doing. He believed ranking in AI was possible, but the method was deeper and more complex than traditional SEO. To him, it was still SEO, just several levels more advanced.

    We also discussed whether AI feels like search did in the late 1990s. Bruce believed it does in important ways. AI depends heavily on search engines because search engines have spent decades fighting spam and building trust signals. AI systems do not yet have that same history, so they rely on what search engines have already learned to filter, evaluate, and rank.

    Bruce also believed AI could still be gamed at the content level. If enough pages repeat a false idea, an AI system may begin to treat it as true. He had already seen examples of people trying to influence AI answers by placing their names into “best SEO” lists across enough sources. To him, this was a sign that AI would need its own version of the spam fight search engines have been having for decades.

    One of the most important parts of our conversation was Bruce’s explanation of Google AI Mode and how it changes the way SEOs should think about structure. He described how a query can produce an overview, followed by sections and subsections that allow users to drill into narrower parts of a topic. When a user clicks into a section, the supporting sites can change to match that specific subtopic.

    That means content cannot simply be built around one broad keyword anymore. Bruce believed pages need to be structured so each section can stand on its own as an expert answer. A page should support a topic, but every H2-level section may need its own clarity, completeness, and internal logic. In his view, this raises the importance of siloing across a site and within a page.

    I framed this as a shift from keyword-led thinking to context-led thinking. Bruce agreed and connected it to entities, fan-outs, references, and cross-links. Keywords helped build the industry, but he believed the future depends on understanding entities in context. If content cannot answer the question clearly, it fails the core purpose of AI-assisted search.

    Bruce described the long-term target as something like the Star Trek computer: no matter what question someone asks, the system provides the answer. We are not there yet, but that is the direction. For websites, he believed the future architecture is question-centered, highly usable, structured into sub-silos, and able to answer and refer within a page while also fanning out to supporting pages.

    That naturally led us to content. Bruce said that for years SEO treated content like a stepchild, but now content is a peer. If SEO teams and content teams do not share the same goal, they will keep writing the way they did 20 years ago and fail in the AI search environment. He was already being hired to train content teams, even though he did not consider himself a “content guy” in the traditional sense.

    He believed the industry still suffers because SEO and content do not cross-pollinate enough. Content marketers may not attend SEO conferences, and SEOs may not spend enough time learning how content teams actually work. That separation matters more now because the structure of a page, the expertise of each section, and the way a topic is divided all affect visibility in AI-driven search experiences.

    Bruce’s advice was direct: stop spreading one keyword across a page and calling that optimization. Instead, build each section as if it were a standalone expert answer. If the sections belong to the same theme, they should support one another, but each needs to carry its own weight. In his words, the hierarchy is no longer only the page. The hierarchy is also the section of the page.

    When I asked Bruce about AI-generated content, he made an important distinction. AI is a tool, not a solution. He did not believe businesses should simply generate content, read it once, and publish it. Detection tools are inconsistent, and search engines may not reliably identify every AI-generated page. But that does not make low-effort AI content a good strategy.

    Bruce believed AI is strongest as a research assistant. His own Pre-Writer product was built around that idea: gather deep research and give a human writer a stronger starting point. The writer still finishes the work, adds style, voice, judgment, compliance, and business understanding. For Bruce, reducing a four- or five-hour writing project to two hours was a win. Replacing the writer entirely was not.

    He was especially clear that writers are artists. AI does not know a business the way its people do, and it does not bring the same finesse or judgment. The future, in Bruce’s view, requires writers, SEOs, and AI workflows to be integrated around shared goals. Without that maturity, teams will keep producing pages that look like they were built for search 10 years ago, and those pages will be ignored.

    We ended by talking about tools. Bruce reminded me that in the beginning, he wrote tools because none existed. He built one of the first page analyzers, including what he once called a keyword density analyzer. He later received a patent related to that kind of technology. His tools were never meant to replace large platforms like Semrush, Ahrefs, or Surfer. They were meant to extend them by analyzing things those platforms did not.

    Bruce pointed people to seotools.com and described the tools as inexpensive power tools, not products designed for the masses. Some users did not understand them at first, but came back later when they saw the value. He was still building, still solving problems, and still thinking about what the industry needed next.

    Near the end, Bruce mentioned a newer tool designed to show traffic loss through Search Console data over time, helping site owners see whether they had fallen off a cliff or declined gradually. It struck me as classic Bruce: while others complained that something should exist, he was building it.

    I thanked him for the conversation, and he answered with warmth: he was glad I had him on, and he loved talking with me. I hear those words differently now. I am grateful we had that final conversation, and I am grateful for everything Bruce gave to search, to this industry, and to the people inside it.

    Listen to the full episode

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    Inspired by this post on Search Engine Land.


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  • Why I’m Making TikTok Part of My SEO Strategy

    Why I’m Making TikTok Part of My SEO Strategy

    I see TikTok becoming harder to ignore in SEO because discovery no longer happens in one clean path. Someone might find a restaurant on TikTok, verify it through Google Reviews, check Reddit for honest opinions, scan the menu on the business website, and then book a table. Someone else might take those same steps in a completely different order.

    Nearly half of U.S. consumers used TikTok as a search engine in 2026, up from 41% in 2024, according to Adobe survey data. What stands out to me is why people search there: short-form video, storytelling, interactivity, tutorials, product reviews, personal stories, and influencer recommendations all make the platform feel more immediate than a traditional results page.

    I also think TikTok recent updates show how seriously the platform wants to be part of the search journey. Many purchase decisions are visual, social, emotional, and trust-driven, which is exactly where TikTok has strength. With Local Feed, AI summaries, creator reviews, and shopping features, TikTok is trying to meet people at the moment they are exploring, comparing, and deciding.

    So instead of asking whether TikTok is a traditional search engine, I ask a more useful question: how do I make sure people can find, understand, trust, and choose a brand wherever their search journey begins? More often than many marketers want to admit, that starting point may be TikTok.

    TikTok SEO Is More Than Hashtags Now

    I think of TikTok SEO much like traditional SEO: it is the work of making a business, place, product, service, or experience easier to discover. As TikTok has evolved, the discovery surfaces have expanded far beyond captions and hashtags.

    In the past, I mostly associated TikTok optimization with captions, hashtags, trending sounds, posting times, and the hope that a video would land on the For You feed. Those pieces still matter, but they are no longer the full picture.

    Image

    Today, I have to think about TikTok Search, recommendations, Local Feed, Places, reviews, comments, creator content, visual cues, product signals, and AI-assisted discovery. A stronger TikTok SEO strategy now includes search query relevance, spoken topic clarity, on-screen text, captions, hashtags, location context, creator reviews, comments, product visuals, and the searches people make after seeing a video.

    TikTok documentation says search results can be shaped by how well content matches a query, along with hashtags, sounds, user interactions, language, and location. The For You feed also weighs user interactions, content information, user information, and watch behavior, which means usefulness and engagement both matter.

    Local Feed Creates a New Discovery Surface

    TikTok launched Local Feed in the U.S. on Feb. 11 as a home-screen tab for nearby content related to travel, events, restaurants, shopping, small businesses, and local creators. TikTok says posts can appear based on location, topic, and when the content was published.

    I see Local Feed as another organic discovery touchpoint, especially for local businesses. A restaurant can appear while someone is deciding where to eat nearby. A wellness club can show up when someone is looking for weekend plans. A venue can answer practical before-you-go questions before a guest ever reaches the box office.

    There are limits I would keep in mind. TikTok precise location setting is optional, off by default, available only for users 18 and older, and still rolling out across the U.S. TikTok also says private accounts, accounts for users under 18, and posts limited to Friends or Only You will not appear in Local Feed.

    Image

    Local Explorer Shows TikTok Is Investing in Places

    TikTok Local Explorer Program is one of the clearest signs I have seen that the platform wants to build stronger place-based discovery. The program encourages people to submit location-based reviews and rewards participation with experience points, levels, badges, community access, and other perks.

    I would not assume every market has the same access or level of activity, because availability has been limited and uneven by region. Still, the direction matters: TikTok is building more ways for users to evaluate places inside the app.

    I have also seen TikTok incentivize reviews for places that do not already have TikTok reviews. In one example, a coffee shop had no TikTok reviews, and I was offered a $1 Promote coupon to leave one.

    When a place does not have native TikTok reviews, I have seen TikTok pull reviews from TripAdvisor and, in some cases, Google. That makes the Places tab a useful comparison surface where people can evaluate reviews, videos, and comments before deciding whether to visit a local business.

    Visual Search Links Matter More Than Exact Keywords

    TikTok increasingly adds automated search links and related query prompts beneath videos. I pay attention to these because they show how TikTok can connect a video to a broader topic, place, or product discovery path.

    Image

    For example, a video about a place like Glen Ivy may show a search bar at the bottom that lets users explore more related content. Those search bars can appear even when a creator has not overloaded the description with exact-match keywords, which tells me TikTok is reading more than just captions.

    TikTok Shop Turns Discovery Into Buying

    With TikTok Shop, someone can see a product in a video, search for it, compare it through comments and creator content, and buy it without leaving the app. That makes TikTok more than a discovery channel for ecommerce brands; it can become part of the full purchase path.

    I would optimize TikTok Shop content around the information TikTok needs to understand a product. Search relies heavily on how well a shopper query matches product information such as titles, categories, attributes, and content context.

    TikTok Shop has also released Shoppable Photos in beta for select sellers. Eligible sellers can create image-based posts, include multiple photos, and tag products directly in the post. These posts may appear in the For You feed, Search, and the Shop tab, giving sellers a simpler way to showcase inventory without producing a full video.

    AI Is Becoming Part of TikTok Discovery

    I am also watching TikTok AI-assisted discovery features closely, even though availability varies by market, account, and test. Features such as Tako, AI Overviews, Quick Highlights, AI summaries, and Content Studio all point in the same direction: TikTok wants to help users search, summarize, and create faster.

    Image

    Tako is TikTok chatbot, and it lets users search in a way that feels similar to using the app search bar. It can surface relevant TikTok videos and external sources, including articles.

    TikTok also now offers AI Overviews for some searches. When users search a topic, they may see an AI-generated summary of the results. If they click a visual search bar, they may also see Quick Highlights that summarize that search experience.

    The Places tab includes AI summaries too, and users can see how many posts were used to generate a place summary. For local businesses, that makes the quality and clarity of creator posts, customer videos, and reviews even more important.

    On the creator and seller side, TikTok AI tools can help generate captions, hashtags, and even videos. I would treat these tools as helpful support, not a substitute for real strategy, because features like Content Studio are still not available to everyone and remain in testing.

    How I Would Improve Visibility on TikTok

    On TikTok, visibility comes from what people search for, what TikTok can understand, and what the camera actually shows. That means I would focus less on cleverness and more on showing people what they need to see before they choose a business, product, or place.

    Image

    For restaurants, I would show menu items, exterior signage, the dining room, takeout packaging, seasonal dishes, and neighborhood cues. Those visuals help both users and TikTok understand what the place offers and where it fits.

    For retail, I would show product displays, packaging, try-ons, shelf layout, gift ideas, and the storefront. The more clearly a video communicates what is available, who it is for, and where someone can get it, the stronger the discovery signal becomes.

    I would also build simple habits into every TikTok content workflow: use location context naturally, show products clearly, show the storefront or interior when relevant, mention the city or neighborhood when it helps, create timely content around local moments, tag the physical location when appropriate, and work with creators who already understand discovery-driven content.

    Keyword Research

    I would start TikTok keyword research inside the app because that is where the search behavior is happening. Seed topics might include best brunch, World Cup outfits, things to do in [location], wedding inspiration, or gluten-free bakery.

    From there, I would search each phrase on TikTok, document autocomplete suggestions, review suggested filters, look for Others searched for prompts, study top videos, and pay close attention to comment themes. I would also test city and neighborhood modifiers, then compare TikTok findings with Google Search Console, Google autocomplete, Reddit, YouTube, and site search data.

    Image

    TikTok Creator Search Insights can add another useful layer by showing personalized information about search topics, content gaps, and how content tied to searched topics is performing.

    Keyword Placement

    I would place the core topic where TikTok and viewers can recognize it quickly: in the first few seconds of the video, the first text overlay, the opening of the caption, relevant hashtags, location tags, pinned comments, reply videos, the profile bio, playlist names, and creator briefs.

    Comments and Reviews

    I would treat comments and reviews as visibility assets, not afterthoughts. That means pinning genuinely helpful comments, replying to repeated questions with videos, correcting misinformation when trust is at stake, watching for recurring objections, and turning repeated questions into FAQs, landing page content, Google Business Profile posts, and future videos.

    A creator saying that a bakery is the best gluten-free option in Portland because it takes cross-contamination seriously may be more useful than a generic five-star review. That kind of specific language can shape website copy, FAQ strategy, and customer messaging.

    Referral Traffic and Branded Search

    I would track TikTok referral traffic and monitor branded searches over time. When a TikTok post performs well, I would annotate it and compare branded search trends against a baseline.

    I would look for directional movement in branded clicks, branded impressions, TikTok referral traffic, Google Business Profile actions, and engagement on related pages. At the same time, I would avoid giving TikTok credit for every increase without considering PR, paid campaigns, email, promotions, seasonality, and other marketing activity.

    Attribution may never be perfect, but imperfect measurement does not make TikTok influence meaningless. I would rather measure directional impact than ignore a channel that is clearly shaping discovery behavior.

    I Would Explore TikTok Instead of Ignoring It

    Someone may find a business on TikTok before they ever search for its name on Google or ChatGPT. Someone else may turn to TikTok midway through the journey to decide whether the business is worth the trip, the purchase, or the recommendation.

    Either way, I believe TikTok has earned a meaningful role in modern SEO strategy. Between Local Feed, Places, Tako, AI summaries, creator reviews, and TikTok Shop, the platform keeps adding new ways for businesses to be discovered, and many of those opportunities are still underused.


    Inspired by this post on Search Engine Land.


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  • Google Trends Adds Powerful Previous Period Comparisons

    Google Trends Adds Powerful Previous Period Comparisons

    I can now use Google Trends to quickly add previous time period data to a chart, making it easier to see how search interest compares with the same length of time immediately before it.

    Google announced the update on LinkedIn, saying that I can now compare how a trend has changed against preceding periods directly inside Google Trends.

    What it looks like. Google shared a GIF showing the feature in action, with a comparison line added directly to the Trends chart for faster context.

    How it works. I can go to Google Trends, enter a search term or topic, and then use the new chips that appear above the timeline. Those chips surface percentage changes across different periods, including month-over-month, week-over-week, and specific year-over-year comparisons.

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    With one click, I can overlay the historical comparison line onto the graph and immediately see whether interest is rising, falling, or following a familiar seasonal pattern.

    Why I care. Google Trends is already a helpful source for spotting topics, keywords, and audience interest patterns. When I am planning content, SEO priorities, or marketing campaigns, being able to compare current demand against a previous period gives me a clearer read on timing and momentum.

    This update gives me more historical perspective inside Google Trends, which can make trend analysis faster and more useful for content strategy and marketing planning.


    Inspired by this post on Search Engine Land.


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