Abu Talha

Abu Talha SEO Consultant | WordPress Expert | Shopify Organic Growth Specialist Blogging & Digital Marketing Blueprint

22/07/2026

I tested 15 "hidden" LLM optimization tactics circulating in AEO circles right now. Only 5 actually moved citations.

I ran them against 40 client pages tracked in Surfer AI Tracker and Profound over 60 days. Most were noise. A few weren't.

Here's what actually changed citation rates:

1. Fact density beats keyword density. Pages loaded with specific stats and quotable numbers saw 30-41% more AI visibility in my tracking window.

2. Third-party review profiles outrank backlinks now. Sites active on G2, Capterra, or Trustpilot had roughly 3x higher citation odds than sites without one.

3. Cross-platform consensus builds trust. When Reddit, YouTube, and G2 all describe a brand the same way, AI engines cite it with more confidence.

4. Freshness has a shelf life of days, not months. Pages updated in the last 30 days pulled 3.2x more citations than older ones in the same set.

5. Retrieval isn't citation. ChatGPT pulls a page in, then discards it 85% of the time. Answer-ready blocks of 40-60 words get quoted. Vague ones get skipped

The other 10 techniques on every "hidden AEO tips" list? Repackaged keyword advice with an AI label on it.

Most "fan-out query" tools just paraphrase your keyword ten times. That's not fan-out. That's a thesaurus with extra ste...
11/07/2026

Most "fan-out query" tools just paraphrase your keyword ten times. That's not fan-out. That's a thesaurus with extra steps.

I ran a client's target queries through every fan-out tool I could find last month, checking which ones actually simulate how Google AI Mode and ChatGPT break one prompt into sub-queries before answering.

Most failed. They gave me variations, not sub-intents. Here are the 10 that actually held up:

1. LLMrefs: free, simulates AI Mode, ChatGPT Search, and Perplexity fan-out in one run.

2. Profound: shows the exact sub-queries AI engines generate before they cite you.

3. Surfer AI Tracker: pairs fan-out subqueries with daily visibility scores across 5 AI platforms.

4. DataWise SEO: mirrors the reasoning chain AI Mode and Deep Research actually use.

5. Wellows: turns one seed keyword into a full semantic query set for content briefs.

6. Locomotive's tool: checks your page's "semantic fingerprint" against what AI actually asks.

7. Hyperleap: free, groups generated queries by search intent.

8. Nightwatch: cheapest tool I found with real fan-out visibility built in.

9. Rankability: free, shows how a query expands before you build content around it.

10 metehan777's open-source script (GitHub): code-level fan-out logic, built for AI Mode.

The fix isn't collecting more fan-out tools. It's picking one whose sub-queries you can actually verify against real AI answers.

Which of these have you tested, and which sub-query surprised you?

27/06/2026

Google just gave you a switch to disappear from AI Overviews. Flipping it might be the most expensive click of your year.

The AI blocking toggle went live on June 27. Site owners can now block their content from AI Overviews, AI Mode, and Discover's AI features. It's rolling out to a UK subset first. In one survey, 33% of SEOs said they'd flip it.

I get the temptation. If AI answers the question, the user never visits. Why feed the thing eating your clicks?

A publisher client asked me to flip it the day it launched. I asked them to wait one week and pull the numbers first. Here's what we found: the toggle doesn't touch organic ranking, so you keep your blue links either way. But blocking AI removes you from the surface where brand familiarity is now being built.

So the real trade isn't clicks versus no clicks. It's short-term impressions versus long-term brand presence in the place where buyers form opinions.

How I'm helping clients decide:

1. Pull your AI impression data first. Don't decide blind.
2. Separate transactional pages from informational ones. They carry different stakes.
3. Ask whether your brand survives being absent while competitors stay visible.
4. Remember, a toggle is reversible, but lost mindshare is not.

For most brands I've looked at, opting out feels like control and acts like surrender.

That's my read. What would you add to this decision before someone flips that switch?

Everyone is ripping FAQ schema off their pages right now. I'm adding it back to mine.Here's why that's not a contradicti...
26/06/2026

Everyone is ripping FAQ schema off their pages right now. I'm adding it back to mine.

Here's why that's not a contradiction.

FAQ rich results stopped showing in search on May 7. Search Console reporting for them is being phased out this month. API support ends in August. So the visible blue snippet is genuinely dead. A lot of people saw that and decided the FAQPage schema was now useless.

The data says the opposite. Pages with FAQPage schema are 3.2x more likely to appear in AI Overviews. The visual result died. The content signal got stronger.

I kept the schema on a B2B client's resource pages, even though most consultants told them to strip it. Three of those pages now get pulled into AI Overviews for question-style queries. The pages where the schema was removed are not.

What this means for your pages:

1. Don't remove FAQPage schema just because the rich result vanished.
2. Write the answers for a machine reading them aloud, not for a snippet.
3. Match the real question phrasing your audience uses, not keyword-stuffed headers.
4. Structure beats decoration. The markup still tells AI what the content is.

Losing the visual snippet made the structured data more valuable, not less.

Agree or disagree: structured data matters more in AI search than it ever did in classic search? Tell me where you land and why.

24/06/2026

The entire GEO citation-buying playbook just became a spam violation. Most agencies selling it haven't told their clients yet.

In mid-June, Google updated its search spam policies to explicitly cover AI search features. The language is direct: manipulating or buying citations for AI search breaks the guidelines. Inauthentic brand mentions seeded across forums, blogs, and social now carry real downside risk.

A client came to me last quarter after paying for a "GEO visibility package." It was 40 planted mentions across low-quality blogs and fake forum accounts. It looked like momentum for about six weeks. Then their brand mentions started being entirely ignored in AI answers.

We spent more hours cleaning it up than it would have taken to earn real citations from scratch.

What actually works, and stays safe:

1. Earn mentions through genuine expertise and original data, not paid placements.
2. Audit your existing citation sources. Remove the manufactured ones before they age badly.
3. Use tools that show real brand mention context, not vanity counts.
4. Treat citations like links in 2012. The shortcut always gets punished eventually.

Buying your way into AI answers was always going to end the same way buying links did.

What tool are you using to monitor where your brand actually gets cited across AI engines? I'm comparing options right now and want real recommendations, not affiliate pitches.

Google finally gave us the AI search data we begged for. Then it left out the part that actually matters.The new AI perf...
23/06/2026

Google finally gave us the AI search data we begged for. Then it left out the part that actually matters.

The new AI performance reports landed on June 3. Separate views for Search and Discover. Impressions, pages, countries, devices, dates. I opened it the same morning for three client properties.

Here's what's missing: no click data. No CTR. No query data. And the numbers only start from May 18. Everything before that is gone.

So I can see that a page pulled 9,000 AI impressions in two weeks. I cannot see if a single person clicked, or what they searched to trigger it.

A local services client in the UK got the report first, since it's rolling out to a UK subset before everyone else. We sat on a call staring at impression counts with no way to tie them to a single booking.

What I'm doing with it anyway:

1. Logging baseline AI impressions per page now, so I have history later.
2. Cross-referencing AI impression spikes against organic clicks in the standard report.
3. Watching which pages earn AI visibility, then reverse-engineering why.
4. Refusing to make revenue calls on impression data alone.

It's a start. It's not the answer. But the SEOs who track it from day one will read the trend before the data gets good.

Have you opened the new AI report yet? Tell me what felt most useful or most missing in yours.

A client emailed me at 6 am this month with one line: “We lost 1,200 pages overnight, and Google won’t tell us why.”They...
21/06/2026

A client emailed me at 6 am this month with one line: “We lost 1,200 pages overnight, and Google won’t tell us why.”

They weren’t exaggerating. A “site:” check showed that roughly 1,200 URLs indexed in May were simply gone in June. No manual action. No security warning. No message in Search Console. Just pages quietly dropping out of the index.

They are not alone. Through June, Glenn Gabe and a steady stream of community reports have documented Google slowly deindexing pages across a huge range of sites. It’s happening at the same time as the aftermath of the May core update, and Google has offered no public explanation. So the panic is understandable. The reaction usually isn’t.

When this lands, most site owners do one of two things. They rewrite everything, or they freeze. Both are expensive. Over the past few weeks, I’ve run the same diagnostic on four client sites hit by this, and it has saved every one of them from burning a quarter on the wrong fix. Here’s the exact order I work through.

Start with the data, not the dread
Before touching a single page, I pull the numbers. The mistake I see most is people reacting to a feeling instead of a count.

I open Search Console and go to the Pages report under Indexing. That report tells you which pages are indexed, which aren’t, and the reason Google assigned. For the 6 am client, the most common reason for missing URLs was “Crawled, currently not indexed.” That single label changes the whole investigation. It means Google saw the page and chose not to keep it, which points to quality or duplication, not a technical block.

Then I export the last 16 months of the Performance report and compare indexed-page counts week over week. In that case, the drop wasn’t actually overnight. It had been bleeding about 80 pages a week since the core update finished rolling out. The “overnight” story was just the day they noticed.

If you take one thing from this section, get the reason label and the timeline before you form a theory. A site losing pages to “Crawled, currently not indexed” needs a completely different response than one losing pages to “Server error 5xx.”

Check what your server is actually returning
The second step costs nothing and catches the most embarrassing causes. I crawl the affected URLs with Screaming Frog and look at the response codes Google is really getting.

On one e-commerce site that “mysteriously” lost 400 product pages, the answer took nine minutes. Those URLs were returning a 200 status to browsers but a 503 to the crawler during a specific window each night, when their backup job spiked server load. Googlebot kept hitting the site mid-backup, reading 503 after 503, and started dropping the pages it couldn’t reliably reach.

Here is what I checked in this pass:

Status codes for the deindexed URLs, tested as Googlebot, not just as a browser

Whether the pages carry an accidental noindex tag or a noindex in the HTTP header

Whether robots.txt started blocking a path after a recent deploy

Whether canonical tags point the deindexed pages at a different URL

Three of the four sites I looked at this month had at least one of these problems hiding underneath the scarier “Google is deindexing us” headline. Rule out the boring causes before you accept the dramatic one.

Render the page the way Google does
If the status codes are clean, I move to rendering. A page can return a perfect 200 and still be effectively empty to Google if the main content loads only via JavaScript that the renderer never completes.

I use the URL Inspection tool’s live test and look at the rendered HTML, not the raw source. On a JavaScript-heavy site that lost its blog section, the raw HTML looked full. The rendered version showed an empty content container because a third-party script had begun failing and blocking rendering. Google was indexing a shell with a headline and no body. Thin pages get dropped, and to Google, these pages had become thin overnight.

The fix there was that there wasn’t content at all. It was a single broken script reference. They restored the section in eight days once we found it. If you skip rendering and jump straight to rewriting content, you’ll spend weeks producing words for a problem that lives in your build pipeline.

Judge the content honestly against the core update
Only after the technical checks come back clean do I look at content quality, and here I’m blunt with clients. The May core update reset how Google weighs helpfulness. Pages that survived for years on thin, templated, or near-duplicate content are exactly the ones getting dropped now.

For the original 1,200-page site, after filtering out technical false alarms, about 300 pages were genuinely thin. They were location pages built from a single template, with the city name swapped in. Forty near-identical sentences, no unique information, no reason for any of them to exist separately. Google deindexing them wasn’t a glitch. It was the system working.

We didn’t rewrite all 300. We consolidated them into 40 genuinely useful regional pages, each with real local detail, and redirected the rest. Within three weeks, 31 of those 40 were reindexed and ranked better than the originals ever did. Consolidation beat replacement because it concentrated value rather than spreading it thin again.

One more thing I tell every client at this stage: deindexing is not always a punishment. Sometimes Google is doing you a favor by clearing out pages that were quietly dragging your whole site’s perceived quality down. On that same site, the 300 thin pages had been diluting the authority of the 40 that mattered. Once we removed the dead weight, the pages we kept started performing better than they had in a year. So before you fight to get every lost page back, ask a harder question: did that page deserve to be indexed in the first place? On two of the four sites I worked on, the honest answer for a chunk of the missing URLs was no, and leaving them gone was the right call.

What to do next
If your pages are dropping out of the index right now, work in this order and resist the urge to skip ahead:

Pull the Search Console Pages report and read the exact reason label for the missing URLs, then chart the indexed page count over the last 16 months to see whether this is a sudden break or a slow bleed.

Crawl the affected URLs as Googlebot in Screaming Frog and confirm the status codes, noindex tags, robots.txt rules, and canonicals are all doing what you think they are.

Run a live render test on a sample of the lost pages and confirm Google sees the actual content, not an empty JavaScript shell.

Do those three before you write a single new word. In four out of four sites I worked on this month, the real cause was found in the first three steps, and the content rewrite was either unnecessary or far smaller than the panic suggested.

The deindexing wave is real, and Google’s silence makes it worse. But “mysterious” usually just means “not yet diagnosed.” Run the checks in order, and the mystery tends to disappear faster than the pages did.

If your site is losing pages right now and you’ve run these checks but still can’t find the cause, send me the Search Console reason label and a sample URL. I’ll tell you which of these four buckets it falls into.

18/06/2026

Google quietly handed your best customers a button that controls whether they ever see you in AI Mode.

Almost no one is talking about it.

Preferred Sources went live inside AI Mode this month. Users pick the publishers they trust, and Google prioritizes those sources in its AI answers. It already existed in regular Search. Now it sits inside the AI experience too.

I checked this with a SaaS client last week. Their most loyal readers, the ones who open every newsletter, had no idea they could add the brand as a preferred source. So the brand was invisible in the exact place its warmest audience was searching.

The April rollout data showed a 2x CTR lift for sources users added. That is not a ranking trick. That is permission-based visibility.

Here is what I am doing about it:

1. Ask existing subscribers to add you as a preferred source. One email, clear steps, done.
2. Put the instructions on your high-traffic pages, not buried in a footer.
3. Map which entities your loyal users already associate with you, then reinforce them.
4. Treat your email list as an AI-visibility asset, not just a newsletter.

The brands that win AI Mode won't be the ones with the most content. They'll be the ones their audience deliberately chose.

What's your take? Is opt-in visibility the next real moat, or just another feature people ignore?

Easiest way to create a Topical Map from scratch. - Find your Central Entity- Identify the Source Context - Then detect ...
15/06/2026

Easiest way to create a Topical Map from scratch.
- Find your Central Entity
- Identify the Source Context
- Then detect Central Search Intent

Google's Universal Cart launches this summer. 8 brands. No website visit required to buy.Most e-commerce SEOs I've spoke...
14/06/2026

Google's Universal Cart launches this summer. 8 brands. No website visit required to buy.

Most e-commerce SEOs I've spoken to are treating this as a future problem. It's a new problem.

Nike, Sephora, Target, Ulta, Walmart, Wayfair, Fenty Beauty, Steve Madden. These are the launch partners.

The moment users start buying through Google's interface instead of clicking through to a product page, the behavioral pattern sets. Users who complete a Universal Cart transaction in month one tend to stay in that purchase flow.

If your Merchant Center feed isn't optimized before launch, you're not just missing early sales. You're missing the users who will habituate around a competitor's product listing.

Here's the 60-day window that matters:

Week 1–2: Audit your Merchant Center feed quality score. Every product missing a GTIN, weight, or detailed category attribute is partially invisible to Universal Cart eligibility checks.

Week 3–4: Rewrite product titles to match how buyers talk, not how your internal catalog is organized. "Women's Running Shoe — Model 4X" loses to "Nike Air Women's Lightweight Running Shoe — Breathable, Size 5–12."

Week 5–6: Add review count and rating data to your feed. Universal Cart ranking factors include social proof signals. An unreviewed product competes poorly against one with 400+ reviews surfaced in the feed.

Week 7–8: Check your price accuracy. Feed price mismatches trigger disapproval. Disapproved products don't appear in Universal Cart.

I'm working through this checklist with 4 Shopify clients right now. Those with clean feeds at launch will have a structural advantage that lasts for months.

What tool are you using to monitor Merchant Center feed health? Genuinely want to know what's working at scale.

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