It sounds convincing. Put a file on your server, explain your site to AI systems, and improve your chances of appearing in their answers.

There is just one problem. Nobody has shown that a major consumer AI platform uses your llms.txt file to decide which store or product to recommend.

Google has gone further. Its documentation for AI Overviews and AI Mode says you do not need a new machine-readable AI file to appear in those results. John Mueller called llms.txt “purely speculative” in June.

I am not saying the file is harmful. If you already have one, leave it there.

I just would not pay someone to make it the centrepiece of an AI search strategy.

There are much more useful things to work on first.

And unlike llms.txt, several of them are documented directly by OpenAI, Google and Perplexity.

Try this before reading the rest

Open ChatGPT and ask a question the way one of your customers would.

For example:

where can I buy running shoes online in Ireland

Replace running shoes with your category and Ireland with your main market.

Look at the stores it names.

If yours is there, save the answer.

If competitors appear and you do not, save that too.

And if ChatGPT falls back to Amazon, eBay or another huge marketplace without naming specialist stores, that is useful information as well.

One answer is not a benchmark. AI answers change between runs. For now you are simply checking whether your store is even in the conversation.

Start with what OpenAI actually says

There is a useful distinction here that gets lost in most discussions about AI visibility.

ChatGPT can mention a store in a normal web answer, and it can also show products and merchants through its shopping experience.

Those are related, but they are not exactly the same thing.

For its shopping experience, OpenAI publishes more detail than most store owners realise.

ChatGPT can use structured product metadata from first-party and third-party sources. When several merchants sell the same product, OpenAI says merchant ranking can consider availability, price, quality and whether the seller is the maker or primary seller.

It also states clearly that organic product results are selected independently and are not influenced by OpenAI partnerships.

That matters.

You cannot simply buy the first organic position in ChatGPT Shopping.

You can, however, give the system better information about what you sell.

That is where I would start.

1. Make your product data easy to use

A recommendation system has a difficult job if your product information is incomplete or outdated.

Price matters. Availability matters. Product descriptions matter. Images matter. Variants matter.

If you use Shopify, there is a useful shortcut here. OpenAI says Shopify product data is already integrated into ChatGPT through Shopify Catalog and individual merchants do not need to create a separate integration for that data to be available.

For other platforms, OpenAI has its own merchant registration and product feed system.

I would not manually build a feed from scratch just because AI search is fashionable. First check what your platform already sends and whether the important fields are accurate.

Google is moving in the same direction. Merchant Center data now matters across AI-driven shopping experiences, including AI Mode, and Google has started adding product attributes specifically designed for conversational discovery.

Perplexity also has a Merchant Program. It is free, although the original programme was aimed primarily at larger retailers, so a small independent store should not build its entire strategy around being accepted.

The practical point is simpler.

Before looking for a new AI optimisation tool, make sure the product information you already publish is accurate.

A feed gets your products into the pool of information a system can use.

It does not guarantee that you will be the store it chooses.

2. Make it obvious that all of your profiles describe the same business

This one is partly SEO, partly basic brand hygiene.

Search your business name.

Then check your website, Google Business Profile if you have one, social profiles, review profiles and major directories.

Is the business name written the same way?

Does each profile point to the correct website?

Do they agree about what you sell and where you deliver?

I would fix inconsistencies before doing anything clever.

I would not worry about using an identical 20-word company description everywhere. That is too mechanical.

The goal is simply to remove ambiguity.

If your website calls the company ABC Running, Instagram calls it ABC Shoes Ireland and a review profile still uses an old company name, fix it.

This takes very little money and it also helps outside AI search.

3. Give AI systems evidence that does not come from you

This is where AI visibility becomes harder to manufacture.

Peec AI analysed 30 million cited sources across ChatGPT, Google AI Mode, Gemini, Perplexity and AI Overviews earlier this year.

The three most cited domains overall were Reddit, YouTube and LinkedIn.

The mix changes by platform. ChatGPT leaned more heavily towards sources such as Wikipedia, Reddit and editorial publications. Perplexity’s top sources included Reddit, YouTube, LinkedIn, Wikipedia and G2.

That does not mean a Reddit mention automatically makes ChatGPT recommend your store.

It does show something useful though.

AI answers use far more than the claims businesses make on their own websites.

A product page saying “fast delivery” is your claim.

Independent reviews repeatedly mentioning fast delivery are different evidence.

The wrong response is to create ten Reddit accounts and start dropping links. Apart from being obvious spam, it gives you exactly the reputation you do not want.

The better approach is slower.

Answer questions in communities where you genuinely know the subject.

Ask customers for honest reviews rather than scripting what they should say.

Publish useful product demonstrations or comparisons on YouTube when video makes sense for your category.

Give people a reason to mention you without having to manufacture the mention yourself.

4. Put useful product information in the page itself

A lot of ecommerce product pages still make the machine do unnecessary detective work.

The specifications are inside an image.

The important compatibility information is hidden in an accordion.

The description is two sentences copied from the manufacturer.

The difference between this product and the next model up is never explained.

Google’s own guidance for AI search is very ordinary here. Important information should be available in textual form, structured data should match what is visible on the page, and product information should be kept current.

That is good advice for ChatGPT and Perplexity too.

Take your bestselling product and check the page.

Can I tell what it is within a few seconds?

Are the important specifications written as text?

Does the page answer the question somebody would normally ask before buying it?

If there is an obvious alternative product, does the page explain the difference?

Last month I wrote about title tags and how one line can change which Google result somebody clicks.

This is the next layer.

A good title helps someone choose your page.

A useful page gives search systems something worth extracting, citing or summarising after they arrive.

5. Check whether you are blocking the systems you want visibility from

This is the technical check I would do before paying for anything.

But the crawler names matter.

For ChatGPT Search, the important crawler is OAI-SearchBot.

OpenAI explicitly says sites that opt out of OAI-SearchBot will not be shown in ChatGPT search answers, although a navigational link can still appear in some circumstances.

GPTBot is different.

GPTBot is used for content that may be used to train OpenAI’s foundation models. You can block GPTBot while allowing OAI-SearchBot. OpenAI treats those as separate choices.

For Perplexity, check PerplexityBot.

For Google’s AI Overviews and AI Mode, check whether normal Googlebot crawling and indexing are allowed. Google-Extended is a different control and is not what determines eligibility for AI Overviews or AI Mode in Google Search.

That distinction is easy to miss, and it is one reason I would not blindly copy a generic “AI robots.txt” template from another site.

Also check your CDN or firewall.

A perfect robots.txt file does not help much if Cloudflare or another security layer blocks the crawler before it reaches the page.

What I keep finding in real stores

I have manually reviewed 197 small and mid-sized online stores across the UK, Australia and New Zealand.

These were screening reviews rather than full client audits. I recorded one main problem per store, so the numbers I publish from that project are deliberately conservative.

One pattern is particularly relevant here.

In 62 of those stores, I found product descriptions that appeared verbatim elsewhere on the web, often because several retailers were using the same supplier copy.

Think about what that leaves an AI system to work with.

Five stores sell the same product.

Five pages contain almost identical text.

None of them explains who the product is actually for, when I should choose it, what it is better at, or what I should buy instead.

There is very little original information there to retrieve.

AI did not create that problem.

Ecommerce stores have been copying supplier descriptions for years.

AI search has simply given store owners another reason to finally fix it.

Is GEO actually different from SEO?

Less than the current marketing suggests.

Most of what I have described here was already good SEO.

Crawlability.

Useful product information.

Structured data.

Merchant feeds.

Brand consistency.

Authority outside your own website.

The difference is the interface.

Google used to make users choose between a long page of results. An AI answer can reduce that choice to a much smaller set of stores, products or cited sources.

That makes being absent more noticeable.

It also makes measurement harder because the answers are not deterministic.

How long does this take?

There is no honest universal answer.

You can check robots.txt today.

You can fix inconsistent business information today.

Product page improvements can go live this week.

That does not mean ChatGPT will mention you next Tuesday.

Crawlers have to revisit the site, indexes have to update, and the system still has to decide that your page or product is relevant to a future question.

Mentions and reviews outside your own site usually take longer because you cannot manufacture genuine reputation on demand.

Anyone giving you an exact number of days before seeing your store in AI answers is guessing.

Should you create llms.txt?

If you already have one, I would leave it.

If your CMS creates one automatically, fine.

I just would not make it a priority and I definitely would not buy an “AI optimisation package” whose main deliverable is that file.

I would rather spend the same afternoon checking product data, crawler access and the pages that actually make you money.

Do you need an AI visibility tracking tool?

Probably not on day one.

Start with a spreadsheet.

Choose five buying prompts that matter to your store.

Run each one several times because AI answers vary between runs. If possible, use a fresh or temporary conversation and keep the prompt wording the same.

Record the date, the prompt, which stores were mentioned and which sources were cited.

Repeat the test every month.

After a few months you will know whether there is enough movement to justify paying for a dedicated tracking platform.

You will also know exactly what you want that platform to measure.

How I would measure this

I would keep two separate views.

The first is your prompt log.

That answers one question:

Are AI assistants mentioning my store more often?

The second is traffic.

Google Analytics or another analytics platform can show referrals from sources such as ChatGPT and Perplexity.

Google Search Console is useful for Google, but there is an important limitation. Google currently includes traffic from AI Overviews and AI Mode inside normal Web search reporting rather than giving you a clean separate AI Search report.

So do not try to turn one metric into something it is not.

Mentions tell you about visibility.

Referral and search traffic tell you whether that visibility is producing visits.

What I would do this week

Run the buying prompt from the beginning of this post and save the result.

Then open robots.txt and check OAI-SearchBot and PerplexityBot. Make sure Googlebot can crawl and index the pages you actually want visible.

After that, open your best-selling product page.

Look at the price, availability, description, images and product specifications.

Then Google your business name and check whether the major profiles agree about who you are, what you sell and where you sell it.

You can do all of that before buying another AI SEO tool.

If you would rather have someone check the store first, send it to me.

The free store analysis I offer now includes an AI visibility check alongside the SEO review.

I will look at where your store appears, where competitors appear instead, and which of the areas in this post I would fix first.

No sales call is required.

GET YOUR FREE SEO ANALYSIS

If you are not ready for that, stay on the list.

One of the next posts will cover two settings that can quietly remove ecommerce pages from ordinary Google Search. They are much less fashionable than GEO, and in the stores I review they usually cost more.

Neven Lovreković

Ecommerce SEO Strategist and founder of Lobit

neven-lovrekovic.com · LinkedIn

P.S. If you do only one thing from this post, check crawler access. It takes a few minutes, and there is no point improving pages for an AI search system that you have accidentally told not to crawl them.

Then I said I would test it instead of assuming the pattern carried over.

So I did.

Two of my predictions were wrong.

Before getting into the numbers, one thing is worth making clear. I sell SEO strategy, not an AI visibility tool, so I have no reason to make one engine look better than another. The sample is mine, the prompts are documented, and I have included the limitations at the end.

If you disagree with the conclusions, there should be enough here to challenge them properly.

What the benchmark said, and what I expected

The original study looked at where AI engines pull citations from when people ask SaaS-related questions.

Vendor pages, meaning the software company’s own website, accounted for between 66.7 and 71.8 percent of citations.

User-generated content was around 17 percent, with Reddit responsible for most of it.

My expectation for ecommerce was that the vendor share would stay reasonably close to that level, while the UGC mix would change. I expected marketplace Q&A and YouTube to take some of the space Reddit occupies in SaaS.

Neither happened.

First thing I got wrong: brands do not own the category

Brand sites accounted for 27.0 percent of citations.

Not two thirds. Just over a quarter.

I do not think that means AI engines have some problem with ecommerce brands. The more likely explanation is structural.

In SaaS, the vendor is usually also the seller. You buy the product directly from the company that makes it, so the vendor website covers both roles.

Ecommerce often has another layer between the brand and the customer.

Retailers.

Retailer pages were actually the largest citation category in my set at 34.2 percent, ahead of brand sites.

That category does not really exist in the SaaS framework because it usually does not need to.

Even if you combine brand sites and retailer pages, you get 61.8 percent. That is still below the SaaS vendor share on its own.

The second thing I got wrong was more surprising

I expected marketplace Q&A and YouTube to absorb some of the UGC share.

Marketplace Q&A received zero citations.

YouTube and other video sources received zero citations.

Not a small share. Zero across all 348 citations.

UGC overall accounted for 5.2 percent, compared with roughly 17 percent in the SaaS benchmark. Every UGC citation in my set came from forums, mostly one very large forum.

There is an obvious limitation here.

A set of 348 citations from one market cannot tell us that video is never cited in ecommerce. It can tell us that across fifteen realistic buying questions, repeated across multiple runs, it did not appear once in this sample.

That distinction matters.

If you were considering moving budget into product video because a SaaS benchmark showed a large UGC contribution, I would want stronger ecommerce evidence first.

The average hides the most useful part

The overall brand share of 27.0 percent is interesting, but once I split the prompts by buying phase, the average became much less useful.

The share changes considerably depending on how close the buyer is to purchasing.

At the problem stage, with questions such as why pans keep failing or how to identify greenwashing, brand sites account for 40.7 percent of citations.

Retailers account for only 3.5 percent.

Regulators, standards bodies and professional associations account for another 27.9 percent. That is another source category that does not fit neatly into the original SaaS framework.

At the comparison stage, brand sites and retailers get much closer.

Brands account for 29.0 percent.

Retailers account for 26.0 percent.

Then the pattern flips at the purchase stage.

When the question becomes where to actually buy the product, retailers account for 62.6 percent of citations.

Brand sites fall to 16.0 percent.

Authority sources fall to just 1.5 percent.

So the closer someone gets to spending money, the more the cited answer shifts away from the brand website and towards the retailer.

For brands that sell through third parties, I think this changes how AI visibility should be looked at.

Your retailer’s product page is part of your visibility whether you control that page or not.

At the purchase stage in this sample, retailer pages were almost four times more likely to be cited than brand sites.

That makes retailer content much harder to treat as somebody else’s problem.

Another problem: the citations do not stay still

I ran every prompt twice to make the data more relevant and to see how much the cited sources changed between runs.

The goal was simple.

How much should I trust one run?

The answer was less than I expected.

Google AI Mode retained only 32 percent of its cited sources between the two passes.

On one prompt, the first pass returned a complete answer with no citations. The second returned 21.

Another prompt went from 15 sources to 12, with a different group of sites making up the answer.

ChatGPT was more stable in the smaller repeat sample I ran there.

Across four repeated prompts, it retained 52 percent of its cited sources.

On one of those prompts it kept every source from the first pass and added another two.

This was not something I originally set out to test, but it may be the most practical result from the whole exercise.

If an AI visibility report is based on one run of one prompt, I would be very careful about treating the resulting percentage as a benchmark.

It tells you what happened in that run.

The next run can look materially different.

What I would do with this

First, repeat the measurement.

For important prompts, I would run them more than twice before making a decision from the numbers. Ideally, those measurements should also happen on different days and at different times.

Where possible, report a range rather than one precise percentage.

I would also separate prompts by buying phase.

An average that combines problem, comparison and purchase questions hides a very important change in source behaviour. Knowing that brands receive 27 percent overall is much less useful than knowing that the share moves from 40.7 percent at the problem stage to 16.0 percent at purchase.

For brands selling through retailers, I would start tracking which retailers consistently appear for purchase-stage prompts.

That gives you something concrete to work with.

Which partners are being cited?

What information appears on their product pages?

How good is the product data you provide them?

Are your strongest retail partners also the ones AI engines are surfacing?

And I would be careful about importing recommendations from another vertical.

In this sample, the two UGC channels I expected to matter most did not receive a single citation.

The same applies to authority sources.

Regulators, standards bodies and certification organisations accounted for 27.9 percent of citations during the problem stage.

If your product carries a certification, the organisation behind that certification may already be influencing AI answers around your category, even if it is nowhere near the transaction itself.

Method and limits

I used fifteen prompts across five product categories.

The prompts were written in buyer language, contained no brand names and were divided across three buying phases.

Across the test there were two primary engines, 49 sessions and 348 recorded citations from two passes.

Each cited domain was recorded separately, including its position in the answer.

A third engine was sampled but did not cover the full prompt set, so I excluded it from every percentage reported above.

There are several limitations.

This is one market.

I recorded domains rather than individual URLs.

So I would treat this as a field measurement rather than a formal study, and any individual percentage as approximate rather than universal.

Five things I would take from it

• Brand sites accounted for 27.0 percent of ecommerce citations in this set, far below the 66.7 to 71.8 percent vendor share reported in the SaaS benchmark.

• Retailer pages were the largest individual source category at 34.2 percent, a category that has no direct equivalent in the SaaS framework.

• Brand share dropped from 40.7 percent at the problem stage to 16.0 percent at purchase, while retailers increased to 62.6 percent.

• Marketplace Q&A and video produced zero citations across the 348 citations recorded in this test.

• One engine retained only 32 percent of its cited sources between the two passes, which makes single-run AI visibility measurements difficult to trust on their own.

Want to know what AI sees when it looks at your store?

You can test this yourself. Take a set of problem, comparison and purchase prompts, run them more than once, and track which brands, retailers and other sources keep appearing.

But if you would rather have a second pair of eyes, send me your store. I will record a short video showing how your store appears across Google and AI search, the biggest visibility leak I can find, and the first thing I would fix.

No call. No pitch. Plain language.

GET YOUR FREE STORE REVIEW

Ecommerce SEO Strategist

neven-lovrekovic.com · LinkedIn

It is the twenty hours you spent fixing something that was never going to move.

I see the same sequence every few weeks. A store owner runs a crawler, gets a report with fourteen hundred issues, sorts by severity and starts working through the red section.

Three weekends later the site is technically cleaner and the traffic looks exactly the same.

The problem was not necessarily the fixes.

The problem was the order.

Severity does not tell you what a fix is worth

A crawler severity score tells you how serious an issue may be technically. On its own, it cannot tell you how much traffic or revenue fixing that issue is likely to return.

Those are different questions.

Take missing meta descriptions.

A crawler might find three hundred product pages without one and mark all of them the same way.

But imagine that two hundred and eighty of those pages received almost no Google impressions during the last three months.

The remaining twenty are already being shown thousands of times.

Writing three hundred descriptions treats those pages as equally valuable.

They are not.

This post is about finding the few that deserve your attention first.

When I would ignore this method and fix everything

There are cases where prioritising individual pages makes little sense.

If the site has twenty products, you can probably fix the whole catalogue faster than you can build a scoring system for it.

A sitewide indexing setting, broken canonical template or technical error affecting every product is also different. Fix the root cause immediately.

A migration deserves the same treatment. During a replatform you are protecting URLs, content and existing visibility. That is risk management, not opportunity scoring.

For a normal established store with hundreds or thousands of URLs, I would rather know which ten pages matter than have another export containing every problem the site has.

What I keep finding in online stores

I manually reviewed 197 small and mid sized online stores across the UK, Ireland, the United States, Canada, Australia and New Zealand.

This was screening rather than client work.

I deliberately recorded only the biggest visible issue in each store. That means the dataset cannot tell me how many smaller problems each store had, and I do not use it that way.

What it did show me repeatedly was how concentrated the biggest opportunities could be.

A store might have hundreds of indexable URLs while a small group of category pages, guides or products accounts for most of the useful search exposure.

That is the pattern behind this post.

You do not need to start with every page Google knows about.

You need to start with the pages Google already gives a chance.

Change the question

Instead of asking:

What is broken on my store?

Ask:

What is happening on pages Google already shows to people?

That wording changes the job.

A page that already receives impressions gives you evidence to work with. You know Google understands something about it. You know queries exist. You know people are seeing the result.

Now you can ask whether the page is earning what that visibility should be worth.

Low impression pages still matter. They simply belong to a different investigation.

I should also be straightforward about my interest here. Deciding where a store’s SEO effort goes is one of the things people pay me for, and there is an offer at the end of this post.

The method below is the same kind of prioritisation I use.

You can run the first version yourself this afternoon.

Start with one free report

Open Google Search Console.

Go to Performance and set the date range to the last three months.

Turn on:

• Clicks

• Impressions

• Average CTR

• Average position

Then open the Pages tab and sort by impressions, highest first.

Caption: One report, sorted one way. Store URLs blurred on purpose.

The first thing this gives you is a shortlist.

That distinction matters.

The Pages report tells you where to investigate.

It does not always tell you what to change.

A single page can rank for dozens or hundreds of queries. One query might sit at position three, another at eleven and another at thirty. Some traffic may be branded. Some may come from one country. Mobile and desktop can behave differently.

The page average compresses all of that into one row.

So do not rewrite anything yet.

Pages gives you the shortlist. Queries gives you the diagnosis.

Start with a high impression page that looks interesting.

Click the URL in Search Console so the report filters to that page.

Now switch to Queries.

This is the part I would not skip.

Look at where the impressions actually come from.

If most of them are caused by people searching your store name, the page level CTR can look far healthier than your non branded performance really is.

Filter branded searches out where possible. If your Search Console property has the branded and non branded filter available, use it. Otherwise exclude the obvious variations manually.

Then look at the queries producing most of the remaining impressions.

You are trying to understand whether one problem actually exists.

A page can have a weak overall CTR because it ranks poorly for most queries.

That is not automatically a title problem.

Another page can sit near the top for important queries and still attract almost no clicks.

That is much more interesting.

The signals I use

Once you have looked at both the page and its queries, the pattern usually falls into one of these buckets.

What you seeWhat I investigate nextStrong impressions, good rankings, weak CTRSearch result presentation, title, snippet, intent and SERP competitionStrong impressions, rankings just outside the strongest resultsContent relevance, internal links, authority and whether the page deserves to moveGood rankings and strong CTRLeave it alone unless there is another clear reason to change itVery low impressionsIndexing, demand, targeting, internal discovery or whether the page needs to exist

The point is not to force every page through the same fix.

The point is to identify the constraint before touching the page.

Turning a CTR opportunity into a number

For pages that appear to have a real click gap, I use a simple estimate.

Take the number of impressions.

Take the current CTR.

Then compare it with a rough CTR benchmark for the position where the important queries are actually sitting.

The calculation is:

Estimated additional clicks = impressions × expected CTR gap

For a quick external benchmark I use First Page Sage’s organic CTR curve.

Their current figures put position one at roughly 39.8 percent, position two at 18.7 percent and position three at 10.2 percent.

The curve then falls to about 7.2, 5.1, 4.4, 3.0, 2.1, 1.9 and 1.6 percent through position ten.

Do not treat those numbers as a promise.

They are a ruler.

Your store, industry, device mix, search intent and SERP layout can produce a very different curve.

I mainly use the benchmark to answer a simpler question.

Is this page obviously underperforming relative to the visibility it already has?

If the answer is yes, it moves up the list.

One warning matters much more in 2026

A normal organic position is no longer a normal organic position on every SERP.

Shopping results, image packs, videos, local results and AI answers can all sit above or around the standard links.

A page listed as position five in Search Console can therefore be appearing in very different environments.

Before treating a CTR benchmark seriously, search the important query yourself.

Look at what is actually between the user and your result.

If your Search Console property has the newer Generative AI performance reporting available, check that too. AI related impressions can change how you interpret the overall search numbers.

This is one reason I would never build an exact revenue forecast from a generic CTR curve.

The number is useful for prioritising.

It is not accounting.

Three real examples

The buying guide

The second row in the screenshot has 5,202 impressions over three months.

Average position is 4.4.

CTR is 1.1 percent.

That produced roughly 55 clicks.

A rough benchmark around that position would put expected CTR closer to five percent.

At 5.1 percent, 5,202 impressions would produce about 265 clicks.

The difference is around two hundred visits during the same period.

That does not prove a title rewrite will deliver two hundred extra visits.

It tells me the gap is large enough to investigate.

I would click into the page, inspect the queries, remove branded noise, check the live SERP and then decide whether the title and snippet are actually the constraint.

If they are, this page goes near the top of my list.

A crawler may never flag it because technically nothing is broken.

The page I would leave alone

Another row has 868 impressions, average position 6.0 and CTR of 16.5 percent.

The generic benchmark around position six is much lower.

Whatever is happening there, searchers clearly respond to the result.

Leave it alone.

I mean that literally.

There is a strange urge in SEO to improve everything once you notice it.

Sometimes the most profitable decision is not touching the thing that already works.

The page with eighteen thousand impressions

Another store had a page with roughly 18,000 impressions, CTR around 0.4 percent and average position 14.6.

At first glance it looks like an enormous CTR opportunity.

I would not start by rewriting the title.

I would open the Queries report first.

If the important terms are really sitting around page two, searchers are barely seeing that result in a useful position.

The low CTR is probably a symptom.

The bigger opportunity is getting the page high enough for the title to matter.

That is a different job.

Do not turn average position into a rule

I used to see people build workflows around ranges such as positions four to fifteen.

I would not do that.

A page at position two can still have a serious click problem.

A page around position twelve can sometimes have a strong snippet and simply need more ranking power.

The page average can also hide several completely different query situations.

Use position as evidence.

Do not turn it into a hard gate.

Four numbers that can mislead you

Brand searches can make weak pages look excellent

The first row in the screenshot is a good example.

The homepage reports a surprisingly strong CTR despite an average position that would normally suggest much less.

That does not automatically mean brilliant copy.

It can simply mean people are searching for the store by name.

Open Queries and remove brand terms before deciding the page is untouchable.

A three month total can hide one strange week

A page with 30,000 impressions might have earned almost all of them during one seasonal spike.

Look at the chart.

If the page had six quiet weeks and then one huge burst caused by Black Friday, Christmas, a product launch or a news event, the total is describing a very different opportunity from a page earning steady impressions every day.

SERP features change the meaning of position

If AI Overviews, shopping results or a video block sits above you, generic benchmark curves become much less useful.

Position five on one query can be highly visible.

Position five on another can feel halfway down the page.

Look at the SERP before believing the spreadsheet.

Average position is still an average

The page in the screenshot below reports an overall average position of 11.4.

Split it by country and the picture changes.

One market performs near the first page.

The United States is around 28.7.

The United Kingdom is around 31.6.

Caption: The same page, split by country. One average hiding several very different markets.

None of those individual markets behaves like the global average.

Before I make an important decision on a page serving several countries, I split the data.

Country is usually the first filter.

Device can matter too.

Add the money layer if the page is commercial

Traffic is useful.

Revenue is better.

If the page you are evaluating is a commercial page and you have reasonable conversion data, you can add one more estimate.

Estimated revenue opportunity = additional clicks × conversion rate × average order value

Imagine the click gap suggests around 200 additional visits.

If a comparable commercial page converts at 2.5 percent and your average order value is £80, the rough revenue opportunity would be:

200 × 0.025 × £80 = £400

I would never present that as a forecast.

It is a prioritisation estimate.

A buying guide, category page and product page can have completely different conversion behaviour.

Still, even a rough money estimate helps when two pages both look like good SEO opportunities and you need to choose which one gets Friday afternoon.

What happens to the other pages?

Nothing this month.

That is the part people resist.

They want a complete checklist because completeness feels safe.

I would rather have five pages with a reason behind each decision.

The rest stay in the queue.

You can set a simple impressions floor for the next review. Maybe one hundred impressions in ninety days for a small store. A larger site may need a much higher threshold.

Once a page crosses your floor, it becomes eligible for investigation.

Pages that never cross it need a different conversation.

Maybe Google does not understand them.

Maybe nobody searches for what they target.

Maybe they are buried internally.

Maybe the catalogue has twenty pages serving the same intent.

Sometimes the right question is whether that page deserves to exist at all.

How many pages should you change at once?

For a small store, I like five.

There is nothing mathematically special about the number.

It is simply small enough that you can track what happened and repeat the process without turning it into a six month project.

If you change forty titles at once and traffic rises, you learn very little.

Change five pages chosen for a clear reason and the result is easier to interpret.

What if every page has low impressions?

Then this method is not your starting point.

You probably have a visibility problem before you have a CTR problem.

That can mean indexing, weak demand, poor targeting, thin category coverage, internal linking or a site that simply has not built enough authority yet.

The fifteen minute check I published when I started this newsletter is a better place to begin.

Category pages or product pages?

In many stores, category pages become the more interesting candidates because search demand concentrates there.

One category can match a wider family of commercial searches while forty individual products split that demand between them.

That does not mean product pages are irrelevant.

It means I would let the impressions tell me where the opportunity already exists rather than deciding in advance which template deserves attention.

My audit tool already has priorities

Good.

Use them.

Just understand what the priority means.

A technical tool can tell you an issue is severe.

Some tools can also connect directly to Search Console and import performance metrics.

That still does not mean the default severity order equals business opportunity.

I want both views.

How serious is the issue?

And:

How much is happening on the affected pages?

When those lists disagree, that is where prioritisation becomes useful.

How long before you know whether a change worked?

I normally want at least four weeks.

Six is better when impression volume is low.

Google needs time to recrawl the page and you need enough new impressions for the comparison to mean something.

Before you make the change, save:

• The URLs

• The exact date range

• The country and device filters

• Whether branded searches were included

• Impressions, clicks, CTR and position

Then make the change and stop touching the page.

The important part is being able to rebuild the same view later.

Measuring the result without lying to yourself

A month later, compare the same segment.

If CTR rises while rankings stay broadly similar, the search result change is the strongest explanation.

If CTR improves and position also moves significantly, the result is good but attribution becomes messier. A page that climbed from eight to four should have earned more clicks even if the title had never changed.

If nothing happens, check the live result.

Google may have rewritten the title.

The query mix may have changed.

A new SERP feature may have appeared.

Or the title was never the real constraint.

That last outcome is useful too.

You tested the cheapest explanation and ruled it out.

Now you know where not to spend another month.

What I would do this week

Open Search Console.

Use the last three months.

Sort Pages by impressions.

Find the pages with meaningful visibility and investigate their queries.

Remove brand noise where it distorts the picture.

Check the SERP.

Estimate the click gap only when the page really looks like a CTR opportunity.

Then keep the five pages where the upside looks largest and the explanation makes sense.

Save your baseline.

Make the changes.

Come back to the same view in four to six weeks.

That is one afternoon.

At the end of it you do not have a bigger SEO list.

You have a smaller one with evidence next to every line.

If you would rather have someone do the sorting, that is the part I do.

Send me your store and I will send back a short video walking through what I find, including which pages I would put in the first five and why.

It is free.

There is no call to book.

If I cannot find anything useful, I would rather tell you that than manufacture a pitch.

Not ready for that?

GET MY FREE STORE REVIEW

Stay on the list.

P.S. Do not just save the numbers. Save the view that produced them. Four weeks from now you will remember the URLs. You probably will not remember whether you had brand searches included, which country you were looking at or whether the page was being dragged around by one query. A baseline only helps if you can reproduce it.

Ecommerce SEO Strategist

neven-lovrekovic.com · LinkedIn

That sentence sounds wrong. Most store owners believe Google traffic works like this. More visitors means better rankings, better rankings mean months of SEO or an agency retainer, so the realistic option is ads. The first part of that chain is broken, and the break is where this post lives.

Your Google traffic is two numbers multiplied, not one. How many people see your result, and what percentage of them click it. That second number is called CTR, click-through rate, and it deserves one plain sentence because everything below moves it. If 100 people see your store in the results and 4 click, your CTR is 4 percent. Position decides how many people see you. The title decides how many of them pick you.

And the title is not a ranking prize you wait for. It is a text field in your shop platform. You can edit it this afternoon.

Here is what that lever is worth in plain arithmetic. Say a category page shows up in 1,000 searches a month, Search Console calls those impressions, and it sits at position 6 with a default title, so 2 percent of people click. That is 20 visitors. Rewrite the title so it answers what the searcher typed, CTR moves to 4 percent, and the same page at the same position brings 40. Nothing else changed. One sentence did.

That is the promise in my headline made concrete. More clicks, same rankings. Going from 2 to 4 percent doubles your visitors, and on a broken title that is a realistic outcome. On a title that is already decent, the gains are smaller. Doubling is what happens when you fix something bad, not a guarantee stapled to every page.

One more piece of honesty before the how-to. A title cannot rescue a page nobody sees. If you rank on page four, this is not your first move, and if you sell something nobody searches for, no headline invents demand. This lever works where you already have impressions. Almost every store has more of those than its owner thinks, and Search Console will show you exactly where. We will get there.

How common is the problem

This summer I reviewed 197 online stores across the UK, Australia and New Zealand. 30 of them had title tags actively working against them. The brand name first on every page, one title copied across dozens of pages, or the platform default nobody ever touched. And 30 understates it. My method logged one main finding per store, the single most damaging thing I saw, so those 30 are stores where the title was the headline problem. Stores where a weak title merely hid behind a bigger one are not in that count.

Want to know which group you are in? In Google, type site: followed immediately by your own domain, with no space, and read the blue lines. If they read like labels a customer would click, you are ahead of most. If they read like an inventory list, keep reading.

Cards on the table

Titles are part of every store audit I do, and last Tuesday they were Fix 1 on my list of seven, because nothing else in SEO pays back faster. Today is the full version of that first fix. The anatomy, the formula, real rewrites, and the measurement. Everything below you can do yourself, without buying anything from me or anyone else.

What the title tag actually is

The title tag is the blue line of your Google result and the text on the browser tab. For Google, it is the strongest single sentence on the page. For the searcher, it is your shop window, the only thing they compare, side by side, against four competitors before choosing where to click.

Your platform already has a field for it on every page. Shopify calls it the SEO title, in the search engine listing section at the bottom of each page and product. WooCommerce shows it in the SEO plugin box under the editor. No code, no developer.

The formula

One page, one title, built in this order.

1. The words your customer types. Not your internal category name. Nobody searches “Our Collection”. They search “womens linen dresses”. Front load these words. Long titles get cut from the end, and searchers scan the first two or three words of each line, so the front of your title is the only part you can count on being read.

2. One specific detail that wins the click. A number, a size range, a guarantee, a shipping promise. “Sizes 6 to 24”, “3 Year Warranty”, “Ships Overnight”. Specifics beat adjectives; nobody clicks “quality products”.

3. Your brand, at the end. It belongs in the title, it builds recognition, but it earns the click only after the searcher knows you have what they typed.

For length, aim for about 55 characters and treat 60 as the ceiling, because Google starts cutting beyond that. This is not just my habit. Cyrus Shepard’s team at Zyppy studied 80,959 title tags and found that titles between 51 and 60 characters were the least likely to be rewritten by Google, while titles over 70 characters got rewritten 99.9 percent of the time. Write long, and the title Google shows is no longer the one you wrote.

Five rewrites from the 197 reviews

These are the patterns I found again and again. Store names are invented, the patterns are real.

1. The brand-first homepage. Before: “StoreName | Home”. After: “Hiking Boots and Trail Gear NZ | StoreName”. The before tells the searcher nothing they can compare. The after answers the search and still carries the brand.

2. The one-word category. Before: “Products”. After: “Garden Furniture Sets, 5 Year Frame Warranty | StoreName”. A title that could sit on any store in the world sells none of them.

3. The manufacturer copy-paste. Before: “XR200 Pro”. After: “XR200 Pro Dehumidifier for Damp Rooms | StoreName”. The model number alone reaches only people who already know the product. Adding what it is and what it solves reaches everyone else, and that text is also exactly what AI assistants quote.

4. The keyword stuffer. Before: “Work boots, buy work boots online, cheap work boots, best work boots”. After: “Mens Steel Toe Work Boots, Ships Same Day | StoreName”. Stuffing reads as spam to people and triggers rewrites from Google. One clean phrase plus one reason to click beats four repetitions.

5. The 90-character epic. Before: a title so long Google cuts it mid-sentence with three dots, usually right before the part that mattered. After: the same message trimmed to 58 characters with the selling point moved to the front. If your argument lives at the end of a long title, nobody ever sees it.

Why Google rewrites titles, and how to keep yours

In that same Zyppy study, Google rewrote 61.6 percent of all titles, and the habit is growing. Another analysis published on Search Engine Land put the figure at 76 percent by early 2025. Those numbers scare people into thinking the field does not matter. The opposite is true. Rewrites cluster around bad titles. Too long, too short, stuffed, or mismatched with the page. Three habits keep your version on screen.

1. Stay in the length window. 51 to 60 characters had the lowest rewrite rate in the study.

2. Match your H1 to your title. When the main heading on the page says the same thing as the title, Google trusts both more. In the study, numbers survived in titles 97.3 percent of the time when the H1 carried them too.

3. Skip the decoration. Square brackets got rewritten 77.6 percent of the time. And if Google swaps your pipe separator for a dash, ignore it, that swap is cosmetic and changes nothing about your clicks or rankings.

The bonus I am not counting

Everything above holds your position constant, and the headline promises exactly that, more clicks without ranking higher. But you deserve the whole picture, because a better title rarely holds position constant for long.

Two things happen after a rewrite. The first is official. The words in your title tag are a ranking signal. Google has confirmed it, and putting what your customer types at the front of the title is the cheapest statement of relevance a page can make. A modest signal, not a magic one. The second is bigger and less official, the clicks themselves. Google publicly downplays click behaviour as a ranking factor, and many experienced SEOs put it near the very top of their list anyway. I will not settle that argument in a newsletter. I will just say that in my reviews and my own work, titles that win clicks tend to be followed by better positions.

And better positions pay disproportionately, because the click curve is steep. FirstPageSage’s meta-analysis of click-through rates puts the average number one result at 39.8 percent of all clicks, number two at 18.7, number three at 10.2, and number six at 4.4. One position up near the top can roughly double your visitors. That curve also tells you why the numbers in my opening example were realistic rather than generous. The average result at position 6 earns 4.4 percent, so a default title limping at 2 percent is not a pessimistic invention.

So the math in this post deliberately counts only the first effect, more clicks at the position you already hold. When the second effect shows up a few weeks later, consider it interest on the same afternoon of work.

How to measure the change

This is the part almost nobody does, and it is the part that turns a text edit into evidence.

Open Google Search Console, Performance report. Click on a page you rewrote, then look at two numbers for that page, impressions and CTR. Note them down, with the date. Google has to recrawl the page first, so give it 2 to 4 weeks, then compare the same 28-day window before and after.

What you want to see is CTR up while average position stays roughly where it was. That is the clean signature of a better title, more clicks from the same visibility. If average position then starts creeping up over the following weeks, that is the second effect from the bonus section arriving. Take it, but keep judging the title itself by CTR. If impressions are near zero, you have learned something too. That page has a ranking problem, not a title problem, and now you know where that page stands.

Start with your 20 most important pages, sorted by impressions in Search Console, not by your own feelings about which pages matter. The page with 5,000 impressions and a default title is worth more of your afternoon than the homepage you already polished.

Quick questions, quick answers

Will Google just rewrite my title anyway?

For most pages, yes. But from what I see in store reviews, Google mostly rewrites the titles that deserve it, too long, too short, stuffed, or saying something different from the page itself. Keep yours around 55 characters, make your H1 say the same thing, put the search words first, and in my experience Google then shows exactly what you wrote.

Do I need a developer for any of this?

No. The field exists on every page of every major shop platform. This is typing, not coding. The only technical neighbour is the H1 match, and that is usually just the page name.

How much can CTR really move?

From broken to well written, doubling is realistic, which on a 2 percent page means 2 more visitors per 100 impressions, forever, for free. From decent to good, smaller single digit gains. Anyone promising an exact number before seeing your Search Console is guessing. I will not.

Does any of this matter for AI search?

More every month. Assistants like ChatGPT and Perplexity lean on the same signals when they describe and recommend stores, and a title that says what the page sells is the single easiest thing for them to quote. The 15-minute check from two weeks ago shows where you stand in AI answers; clean titles are part of how you move.

Want your titles reviewed for you?

Do the site: check today. Rewrite your top 20 this week. Note your Search Console numbers before you start. That is the whole method, and it is free.

If you would rather have a second pair of eyes first, I do a free version of exactly this. Send me your store through the button below and I will record a short video, about five minutes, showing what your titles look like in Google right now, side by side with the stores you compete against, which ones are costing you clicks, and the rewrite I would start with. No call, no obligation, plain language.

GET YOUR FREE STORE ANALYSIS

And if this post was useful, forward it to one store owner whose Google results still say “Home”. You now know exactly what that is costing them.

Neven Lovreković

Ecommerce SEO Strategist and founder of Lobit

neven-lovrekovic.com · LinkedIn

P.S. If you only remember one thing, your Google traffic is impressions times click rate, and the second number is a text field you control. Before you spend anything on ranking higher, spend an afternoon making the rankings you already have earn their keep.

---

This summer I reviewed 197 online stores across the UK, Australia and New Zealand. Among the top findings there was not a single mysterious Google penalty or algorithm curse. But 57 stores were missing meta descriptions, 52 were handing Google their filter URLs instead of their product pages, and 30 had title tags working against them.

And exactly 9 out of 197 had a real site speed problem.

Speed is the thing most owners spend money on first. It was one of the rarest problems on the list. That gap, between where the money goes and where the problems actually are, is what this post is about.

The belief that costs you the most

Most owners I talk to believe some version of this: “If my store had an SEO problem, it would be something deep and technical. Finding it takes an expert, fixing it takes a developer, and both take a budget I don’t have. So I’ll run ads instead.”

The 197 stores say otherwise. The problems I find most often sit in plain sight, in fields your shop platform already gives you, and most can be fixed in an afternoon by the same person who uploads the products.

To be fair about it: there are stores where none of this is the bottleneck. If you sell something nobody searches for, these fixes will not invent demand. And if you already pay someone who polishes this every month, today’s post is a checklist to hand them, not news. For everyone else, this list is where I would start. Every time.

In my audits I call these fixes Low Hanging Fruits: the fruit closest to the ground, where the least climbing feeds you first. (In a full audit the same name also covers keywords stranded just off page one of Google. That version needs Search Console and deserves its own post.)

Cards on the table

Finding these problems is what I do for a living. I audit online stores. The seven checks below are the opening moves of exactly what I would run on yours, written so you can do them yourself, with the real numbers from those 197 reviews next to each. Nothing here requires buying anything, from me or from anyone else.

Last Tuesday I gave you a 15-minute check that shows how much traffic you are losing to AI answers. Today is the practical sequel: what to fix first once you know you are leaking.

One note before the list. It is ordered by how fast each fix pays back for an owner working alone, not by how impressive it sounds. That is also why speed comes last.

Fix 1: Title tags that repeat themselves

The title tag is the blue line in your Google result and the label on the browser tab. For Google, it is the single strongest sentence on the page. In most stores, every page wears the same one.

The pattern I keep seeing: “Home | StoreName” on the homepage, “Products | StoreName” on every category, and product pages that lead with the brand instead of the words a customer would actually type.

Spot it in 60 seconds. In Google, type site: followed immediately by your own domain, with no space, and read the blue lines. If ten pages read almost the same, or every line starts with your store name, you found it.

The fix. One page, one title. The words your customer searches for go at the start, your brand at the end, the whole thing around 55 characters (Google usually starts cutting titles off past that point, so treat 60 as the ceiling). “Merino Base Layers for Hiking | StoreName” beats “StoreName | Products” every day of the week. Your platform already has a field for this on every page: Shopify calls it the SEO title, WooCommerce shows it in the SEO plugin box under the editor.

Numbers and effort. 30 of the 197 stores had weak or repeated titles. Time: an afternoon for your 20 most important pages. Developer: no. Payback: among the fastest in SEO, because titles feed both rankings and clicks. In my experience the first movement shows in Search Console within a few weeks.

Fix 2: The ad you never wrote (missing meta descriptions)

The meta description is the grey text under your blue link. It does not directly rank you higher. It decides how many of the people who see you actually click you. It is ad copy, shown for free, to people already searching for what you sell.

57 of the 197 stores had none at all. When it is missing, Google improvises and grabs whatever text looks related, menu fragments and cookie notices included.

Spot it in 60 seconds. Same site: search. Read the grey text under your links. Is it a sentence a human wrote on purpose, or a random scrape of the page?

The fix. For your top 20 pages, write 2 to 3 sentences, up to about 155 characters: what is on the page, plus one concrete reason to pick you. Free returns. Ships tomorrow. 30 brands in stock. Sizes up to 5XL. Specifics beat adjectives; nobody clicks “high quality products at great prices”.

Numbers and effort. Missing in 57 of 197 stores, nearly one in three. Time: about two hours for 20 pages. Developer: no. Payback: clicks can move within days to weeks once Google refreshes your snippets, and you can watch CTR change page by page in Search Console.

CTR, click-through rate, deserves one plain sentence because it is the number this whole fix moves. It is the percentage of people who saw your link in the results and actually clicked it: if 100 people see your store and 4 click, your CTR is 4 percent. A better meta description raises that percentage directly, even while your position stays exactly the same. Same ranking, more visitors, which is why this fix pays back so fast.

Fix 3: H1 chaos

Every page should have exactly one main heading, the H1, and it should say what the page sells. Google treats it as the strongest signal on the page after the title tag. What I actually find: pages with no H1, pages with five of them, and category pages whose H1 proudly says “Shop”.

Spot it in 60 seconds. Open your top category page, right click, View page source, press Ctrl+F and type “h1”. Count the hits and read what sits inside them.

The fix. One H1 per page, keyword at the start: “Women’s Trail Running Shoes”, not “Our collection”. Everything else becomes H2 or H3. In most themes the H1 is simply the page or product name, so this is renaming, not coding. Page builders are the usual troublemakers; if yours wraps banners in H1 tags, that is a 15-minute theme setting, worst case one short developer ticket.

Where it goes. Two placement rules that most stores miss. First, on a phone your H1 should sit above the fold. Above the fold means the part of the page a visitor sees immediately, before scrolling at all; the term comes from newspapers, where whatever sat above the physical fold had to sell the paper on the stand. Second, the H1 should be the most prominent element on the page. When someone lands there, the first thing their eye catches should be the line that says what the page sells, not a banner, a slogan or a popup. Check it on your own phone: open your top category page and ask what you see first.

Numbers and effort. Time: an hour to check and rename your key pages. Developer: rarely. Payback: modest on its own but it compounds with fixes 1 and 2. Clean headings are also exactly what AI assistants quote, because they read structure, not design.

Fix 4: A homepage that points the wrong way (internal linking)

Your homepage is the strongest page you own, and every link on it passes some of that strength forward. Most homepages spend it on “About us”, Instagram and whatever is on sale this week, while the categories that pay the rent sit three clicks deep.

And the classic: a featured section showing 12 discounted products instead of the 12 bestsellers. That is pointing your biggest spotlight at your lowest margin.

Spot it in 60 seconds. Open your homepage and count the links to your three most profitable categories. Then count the links to everything else.

The fix. Link your money categories directly from the homepage, with the category name in the link text: “Merino base layers”, not “Shop now”. Feature bestsellers, not clearance. If you want the audit-grade version: add a prefooter, a tidy block of your key category links sitting just above the footer on every page. It is the cheapest structural upgrade I know.

Numbers and effort. Time: an afternoon in your theme editor. Developer: no. Payback: weeks, and it lifts exactly the pages that make you money.

Fix 5: Canonical errors (the technical one, worth it)

One in four stores I reviewed, 52 of 197, were feeding Google the wrong URLs: filter combinations, sort orders, page 7 of a category, sometimes thousands of variants competing with the real page. The canonical tag is one line of code that tells Google “this is the original, ignore the copies”. When it is missing or wrong, Google splits your strength across URL junk and spends its visit crawling garbage instead of your new products.

Spot it in 60 seconds. Run that same site: search on your own domain and look at the result count. If you sell 400 products and Google lists 12,000 pages, or you see URLs with ?sort= or ?color= in the results, this is you.

The fix, in plain terms. Every real page points a canonical at itself. Filter and sort URLs are set to noindex. Pagination has its own small rule: page 1 of a category stays index,follow, and every page after it (page 2, 3 and beyond) gets noindex,follow. In plain English, those deeper pages will not appear in Google’s results, but Google still follows them and picks up every product listed on them. Nothing in your catalog gets lost; Google just stops showing near-empty list pages instead of your real ones. In Shopify and the main WooCommerce SEO plugins most of this is settings, not code. And if this paragraph reads like a foreign language, this is the one fix where a developer’s hour is genuinely well spent. Hand them this paragraph as the ticket.

Numbers and effort. Found in 52 of 197 stores. Time: from 30 minutes of plugin settings to one developer ticket. Payback: slower than titles, weeks to a couple of months, but it raises the ceiling on everything else, because Google finally sees the store you actually built.

Fix 6: Invisible images (file names and alt text)

Google cannot look at a photo. It reads what you tell it about the photo, and IMG_4823.jpg with an empty alt field tells it nothing. Alt text, the short description in your image settings, feeds Google Images, shopping results and the AI assistants that increasingly describe products to shoppers. It is also what screen readers speak, so it is basic accessibility.

Spot it in 60 seconds. Open one of your bestsellers and check the image fields. File names like IMG_ and empty alt boxes mean this fix is yours.

The fix. Product name in the file name, a plain factual alt text (”merino base layer, navy, men’s”), images at least 1200 x 1200 pixels, compressed before upload (TinyPNG is free). Start with your 20 bestsellers, not the whole catalog.

Numbers and effort. Time: about an hour per 20 products. Developer: no. Payback: the slowest on this list, but it compounds and never expires.

Fix 7: Speed (the one you probably don’t need)

Now the finding that surprises everyone. Of the 197 stores, exactly 9 had a speed problem worth spending money on. Under 5 percent. Yet speed is the first thing owners buy: plugins, optimization packages, sometimes a full replatform.

The sequence that actually makes sense costs nothing. Open PageSpeed Insights, test your busiest category page, look at the mobile score. Then open your store on your own phone, on mobile data, not wifi. If the score is orange or better and the store feels fine in your hand, close the tab. Spend the money on fixes 1 to 6 instead.

If the score is deep red, rare does not mean harmless: for the 9 stores that had it, speed was a real and expensive problem. The most common cause in my reviews is oversized images, which fix 6 already handles. The second is JavaScript: popups, trackers, sliders and store apps each loading their own scripts before the page can settle. Your hosting is rarely the villain.

One warning for the red scenario. JavaScript cleanup is not a do-it-yourself fix. Untangling which scripts can go without breaking your checkout, your tracking or an app you rely on is delicate work, so if your store is genuinely slow and images are not the reason, hand the diagnosis and the fix to a professional. It is the one item on this list where I tell owners to keep their hands off.

Numbers and effort. A real problem in 9 of 197 stores. Time: 10 minutes to measure. Developer: measure first; if the test comes back red, yes, a professional. Payback: usually the payback is the money you did not spend.

The whole list on one screen

1. Title tags. An afternoon. No developer. Fastest payback: rankings and clicks.

2. Meta descriptions. Two hours. No developer. Days to weeks: more clicks.

3. H1 cleanup. One hour. Developer rarely. Compounds with 1 and 2.

4. Internal links. An afternoon. No developer. Weeks: lifts your money pages.

5. Canonicals. Settings, or one developer ticket. Biggest ceiling raise.

6. Images and alt text. One hour per 20 products. No developer. Slow but permanent.

7. Speed. Ten minutes to measure, then decide. Usually the payback is the money you save.

One honest footnote on order. In a full audit I do not start with titles. I start with whether Google can enter the store at all and whether it is indexing the right pages (robots, redirects, canonicals), because a store Google cannot read properly gets nothing from a better headline. But sorted by payback for an owner working alone, the list above is the order I would work through. And it is the same seven I keep finding, store after store.

Quick questions, quick answers

Do I need a developer for any of this?

For five of the seven, no. The fields are already in your shop platform. Canonicals sometimes need one ticket, H1 occasionally needs a theme tweak. Speed needs nobody until you measure; if the test comes back red, that is professional territory, not a weekend project.

How fast will I see results?

In my experience: title and description changes start showing in Search Console within days to a few weeks, because Google has to recrawl the pages first. Structural fixes like canonicals and internal links take weeks to a couple of months. I will not promise numbers, and you should be suspicious of anyone who does. What I can say is that I have never seen a store fix all seven and regret it.

What if I do all seven and nothing moves?

Then you have learned something valuable: your bottleneck is not the basics. It is demand, content or competition, and you can now invest there without wondering whether a missing meta description is quietly taxing every click. Ruling things out is half of diagnostics.

Where does AI search fit into this?

The same fixes feed it. Assistants like ChatGPT, Gemini and Perplexity build answers from pages they can read and quote: clear titles, one honest heading, clean URLs. The stores that show up in AI answers are, with few exceptions, the stores that did this homework. Last week’s 15-minute check tells you where you stand; these seven fixes are how you move.

Want me to find your store’s Low Hanging Fruits?

Do the checks yourself this week. That is what they are for.

But if you would rather have a second pair of eyes first, I do a free version of exactly this: send me your store through the button below and I will record a short video, about five minutes, showing which of the seven is costing you most and the one fix I would start with. No call, no obligation, plain language.

GET YOUR FREE STORE ANALYSIS

If this post was useful, forward it to one store owner who is about to buy a speed package. You might save them real money.

Neven Lovreković
Ecommerce SEO Strategist · Founder, Lobit
neven-lovrekovic.com · LinkedIn

P.S. If you only remember one thing: the expensive problems are almost never the ones you are looking at. Before any money leaves your account for speed, spend one afternoon on titles and meta descriptions. The 197 stores are unanimous about where to start.

Try something before you read any further.

Open ChatGPT and ask it the question your store lives off. Not your brand name, the real buying question a stranger would type. Something like “best merino hiking layers in the UK” or “best eco kitchen products that ship to New Zealand”.

Read the answer. It is long, confident and specific. It names products. It names stores.

Now the uncomfortable question: is yours in it?

Most owners I talk to have never looked. Their future customers look every day.

What actually changed

AI search is the new layer between you and your customer, and it has two faces. Google now shows AI Overviews, a written answer at the top of many searches, above the first result. And assistants like ChatGPT, Gemini and Perplexity answer buying questions directly, usually by naming three to five stores and products.

The work of making sure your store is one of the names inside those answers has an industry name: GEO, generative engine optimization. That is as much jargon as you will get from me today. Think of it as SEO with a second scoreboard.

Here is why this costs you money even when your rankings look fine:

• When an AI Overview answers “what to look for in X” well enough, part of the people who used to click your buying guide simply stop clicking. Your position holds. Your clicks drop.

• When an assistant recommends stores, the shortlist forms before anyone opens a browser tab. If you are not on it, you were never in the running, and no analytics report will tell you.

This is not the end of Google traffic. It is a quiet tax on it. And it grows a little every month.

The part nobody tells store owners

Before you spend anything on this, one thing from practice.

This summer I reviewed 197 online stores across the UK, Australia and New Zealand. The finding that mattered most had nothing to do with AI: 62 of those stores were selling with the manufacturer’s product description, word for word. Dozens of sites, identical text.

Google has to pick one of those identical pages, and it is rarely the small store. An AI assistant is even stricter. It builds answers from pages that actually say something: a real comparison, a real spec, a real answer to a real question. If your page carries the same text as dozens of competitors, there is nothing left to quote. So you don’t get quoted.

That is the good news hidden in all of this. Most stores losing AI visibility are losing it for old-fashioned, fixable reasons.

The 15-minute check

You need a timer, a notebook and 15 minutes. If you use Google Search Console, keep it open too. Nothing else.

Step 1, about five minutes: ask ChatGPT.

Run these five prompts, filled in for your niche:

1. Best [your product type] for [your main customer] in [your country]

2. Where should I buy [your product type] online in [your country]?

3. [A product you sell] vs [the rival product your buyers compare it with], which should I buy?

4. Is [your store name] legit?

5. Best alternatives to [your biggest competitor]

One line per answer is enough: did my store appear, yes or no, and which stores did.

Then count. The number of answers that mention your store, 0 to 5, is your score. Write it down.

If you want the full picture later, repeat the same five prompts in Gemini and Perplexity. Useful, but optional, and not part of the 15 minutes.

Step 2, about five minutes: look at your own Google results.

Google the three searches that bring you buying customers, the ones people type when they are ready to spend. For each one: is there an AI answer at the top of the page? Does it fully answer the question? And is your site one of the small source links inside it, or is a competitor?

Step 3, about five minutes: open Google Search Console.

If you don’t use Search Console, skip this step. Steps 1 and 2 already answer the main question, and setting it up properly is a post of its own.

If you do: open Performance, then Search results, and set the date range to compare the last 6 months with the previous 6. Look at your most visited pages for one pattern: impressions holding or rising while clicks fall. An impression means your page showed up in someone’s results. A click means they actually came. A page that keeps its position but loses clicks is the signature of an answer taking your visitor before they reach you.

This step is also where “how much” gets a number. Take one page: if clicks fell from 500 to 300 a month while impressions held, that single page is losing around 200 visits a month to answers. Do the same for your top three pages and you are holding a number, not a feeling.

Whatever you found, write it down with today’s date. That is your baseline. Repeat the same 15 minutes every three months and you will know exactly which way this is moving for your store, while your competitors keep guessing.

What you will probably find

Most stores land in one of three places.

You show up in some answers. Good. Protect it, those pages deserve your attention first.

You don’t show up, but competitors do. Now you know who and where, which is more than most owners know. The fixes are concrete, and we will cover them here one per week.

Nobody from your niche shows up. That is an open market. In the answers I check, the same names keep coming back once they get in. There is something to be said for getting there first.

What happens here every Tuesday

This is the first post of a weekly series. Every Tuesday, one practical way to make your store more visible in Google and in AI answers. Written for owners and marketing managers of small and mid-size online stores, not for SEO professionals. Everything comes from real store reviews and real numbers, like the 197 above, and none of it needs a big budget.

Next Tuesday: the seven low-hanging fixes I check first in every store, ordered by how fast they pay back.

Quick questions, quick answers

Does AI search replace SEO?

No. AI assistants find and read your pages much the same way Google does. Good SEO is still the entry ticket. Getting quoted in the answers is the new prize on top of it.

My store is small. Does this matter yet?

Measured in today’s visits, less than the headlines claim. Measured in direction, a lot. The shortlists are forming now, and they are easier to enter early.

Which assistant matters most?

The one your customers use. In practice, start with ChatGPT, and watch Google’s AI answers closely because they sit inside the search you already depend on.

Want me to run this check for your store?

I do it free. Send me your store through the button below and I will record a short video, about five minutes, showing where your store is leaking Google visitors and the one fix I would start with. No call, no obligation, plain language.

Get your free store analysis

Neven Lovreković
Ecommerce SEO Strategist and founder of Lobit
neven-lovrekovic.com · LinkedIn

P.S. If you only take one thing from this post, take the five prompts. Your score, 0 to 5, written down with today’s date, is a baseline most of your competitors will never bother to get. Everything we do here in the coming weeks builds on knowing where you actually stand.