AI Content Gap: How to Find Where AI Recommends Your Competitors

• An AI Content Gap isn’t just about missing articles. The gap can also involve case studies, comparisons, data or external mentions.
• Start your analysis with the Prompt Gap: check which business-critical prompts your competitors are visible for while your brand is missing.
• Find the cause of the gap, not just its symptom: pin down exactly what you’re missing compared with the competitors AI recommends.
• Identify the type of gap: it can be a Topic, Intent, Evidence, Comparison, Data or Source Gap, among others, and each one calls for a different action.
• Measure the effect at the level of whole topic clusters: track metrics such as Mention Share, Citation Share and the AI Competitor Gap regularly, instead of judging visibility by a single prompt.

A Keyword Gap told us which keywords our competitors were visible for on Google while we weren’t. Today that’s nowhere near enough, because AI Search won’t always be tied to classic search results.

Here’s an example:

Company A and company B both have a similar article about e-commerce SEO on their blogs, covering the same points. Both companies rank for similar phrases on Google. But when a user asks ChatGPT, “Recommend an SEO agency with experience working with large international stores,” the model only recommends company A. What could be behind that?

Company A may have more case studies with large e-commerce businesses on its website, more customer reviews and clearly displayed information about the markets it serves, and it may also appear in external rankings.

The first step in comparing yourself with competitors in AI Search should be a benchmark. Above all, it helps you identify your real competitors in AI (who don’t have to be the same companies you compare yourself with on Google) and shows how big the differences are between your brand and the other companies in the industry.

You’ll find details on how to prepare this kind of benchmark here:

How to Build a Competitor Benchmark in AI Search

One of the key starting points for further analysis after the competitor benchmark is the Prompt Gap: checking brands’ visibility for prompts that matter from a business point of view.

Below are some shorter example queries that matter to a brand selling a CRM system:

In a comparison like this, we’re interested in the rows where we have no visibility and the competitor does. That’s your first set of gaps in AI Search visibility.

The competitor benchmark is the first stage of the analysis, and the extended Prompt Gap is the second. Next comes the most important part of the whole process: finding the cause of the gaps. Many companies make the mistake of oversimplifying the problem. A competitor shows up in the answer and we don’t? We need to write a new article on the topic. That’s a trap that, in most cases, not only wastes time but also risks topic cannibalization.

Instead of creating new content, think about what might justify AI’s recommendation of your competitor. To figure that out, you’ll need to check the most likely reasons with a Recommendation Evidence Map.

For each prompt where a competitor is visible and your brand isn’t, check the possible reasons for the recommendation. Taking a prompt asking about an SEO agency for an international e-commerce project as an example:

A simple check like this gives you a first idea of where the brand falls behind its competitors. Instead of “we need content about international SEO,” the AI Content Gap gives the Marketing Manager a concrete insight: AI has several independent sources confirming the competitor’s expertise in this area (case studies, external publications, experts) that we don’t have. That’s a specific, valuable diagnosis that can serve as the basis for further optimization work.

Gaps can have different causes, so the problems you identify can be grouped into several areas:

1. Topic Gap

A Topic Gap is when an entire topic area is missing from the website. For example, a competitor has plenty of material (articles, case studies) on international SEO for e-commerce, while another agency doesn’t cover the topic at all, even though it offers these services.

This is an example of a situation where creating new content really is justified. In other cases, it’s better to spend your time optimizing existing content or supporting it with link building.

2. Intent Gap

An Intent Gap appears when a topic is covered on the website but lacks the context that answers the user’s intent. For example, an agency has an article titled “What Is International SEO?”, but a potential customer typing a prompt into ChatGPT is looking for information about the agency’s experience with international SEO. The answer to that intent would be case studies, which the website doesn’t have in this case.

3. Evidence Gap

For LLMs, one of the key factors in deciding whether a brand is worth citing is evidence of its expertise and experience. Simply saying you have experience won’t be enough: you need specific data.

For example:

• The agency operates in 18 markets.
• Over a 5-year partnership with brand X, it delivered +300% growth in organic revenue.
• As part of the partnership, it implemented work in areas X and Y.

4. Comparison Gap

Comparing products, services and providers is a common user intent and also one of the stages of the purchase journey. If your competitors have comparisons, alternatives, side-by-side tables and scenarios showing who product X is right for, and your brand has no such content, you have a Comparison Gap.

Preparing this kind of content makes it easier for AI to cite you later. Learn more: Content types preferred by AI: comparisons, lists, “top X” lists, checklists.

5. Data Gap

A Data Gap, meaning missing data, is especially important for e-commerce. If your product doesn’t have complete information on its specifications, delivery times, variants and available options, you lose out to competitors who have a consistent, complete product feed. It’s also worth remembering structured data, such as Product Schema, which can make it easier for AI bots to process the information on the page.

6. Authority / Source Gap

AI visibility problems can’t always be solved with changes to your own website: authority is often built through external factors. If there are gaps in this area, we call it a Source Gap. An Ahrefs analysis of 75,000 brands found a strong correlation between a brand’s visibility in AI systems and its external mentions.

Source: Ahrefs

That’s why you should also look for gaps compared with your competitors beyond your own website. But it isn’t only about being present in places that AI systems might use as sources.

Fill the Source Gap based on data: prompt monitoring, an analysis of the sources cited for specific queries and a comparison of your brand’s presence with your competitors’. If, in a given topic cluster, competitors regularly appear on specific portals, rankings, reports or other sources and your brand doesn’t, that’s a concrete area to work on. Equally valuable are the sources you know, from your monitoring data, are often cited by AI models on the topic.

Behind a single question asked by a user, there are actually several additional sub-queries, known as fan-out queries. To answer a given prompt precisely, an LLM breaks it down into its components and looks for specific pieces of information.

For example, a user asks about an affordable CRM for a 20-person company.

That prompt can generate several more detailed queries:

• How much does a CRM for 20 users cost?
• Which CRM offers the best value for money?
• Does the price depend on the number of users?
• Does the CRM have a free plan or a trial period?
• Which features are available in the cheapest plan?
• Does the CRM include sales automation?
• Which integrations does the CRM offer?
• Do implementation and onboarding cost extra?
• Is customer support included in the price?

The main prompt is often the starting point for other informational intents, so you need to make sure your content also answers all the questions around the topic.

In Ahrefs, the Brand Radar feature shows fan-out queries for selected monitored prompts.

A Semrush study covering more than 50,000 brands shows that visibility in ChatGPT and other LLMs should be analyzed at the level of topic clusters, not individual prompts. Of the more than 1,000 categories analyzed, only 15.2% had a clear visibility leader, and in 53.7% no brand appeared consistently across most of the related prompts.

This suggests that visibility for one selected prompt doesn’t mean visibility across the whole topic category. So when you choose prompts to monitor, it’s worth picking ones that give you a broader view of the topic cluster.

Let’s use the SaaS company offering a CRM as our example again.

Selected prompt: “The best CRM for a 20-person software house operating in Poland and Germany.”

Recommendation: Companies A and B. Our company isn’t there.

Step 1: What does AI emphasize in its answer?

For company A:

• Integrations
• Price
• Support in multiple languages

For company B:

• Case studies for software houses
• Automations
• A comparison of the available service tiers (basic, advanced and premium plans)

Step 2: What information do we show on our website?

• Integrations ✓
• Pricing ✓
• Support in multiple languages ❌
• Software house case study ❌
• No comparisons within our offer.

Step 3: What gaps have we identified?

• Evidence Gap: we don’t have a published case study for a software house.
• Intent Gap: the user is looking for a CRM for several markets, and our content doesn’t answer that intent.
• Comparison Gap: there’s no comparison of the available plans.

Step 4: Setting an action plan

1. Create an expert case study.
2. Add the multilingual option to the description of the solution.
3. Publish a comparison of the available plans on the website.

To check whether the strategy is working, you’ll need a regular benchmark of your results against your competitors. It’s worth setting fixed KPIs and refreshing them, for example, once a month. Here are the metrics we suggest:

Tracked across a fixed set of prompts, these three metrics show best whether the gap you identified is actually shrinking.

Sources:

• https://ahrefs.com/blog/custom-prompt-tracking/
• https://www.semrush.com/solutions/ai-visibility/
• https://www.semrush.com/blog/chatgpt-topic-authority-study/
• https://ahrefs.com/blog/ai-brand-visibility-correlations/