5 KPIs to Track for AI-Powered Search

Search visibility in 2026 looks very different from what marketers were optimising for just a few years ago. AI assistants now summarise answers before users ever see a traditional results page. Google AI Overviews, conversational search, and zero-click behaviour mean your brand can influence decisions without earning a visit. At the same time, many SEO dashboards are still centred on rankings, clicks, and sessions, metrics that increasingly fail to capture real visibility.

If you want to understand whether your brand is genuinely discoverable in an AI-driven search landscape, you need a new measurement framework.

In this blog we’ll explain the following 5 KPIs and how you can track them:

• AI referral traffic
• Mention rate across priority prompts
• AI-Overviews and rich result coverage
• Branded search volume trend
• MQLs from organic and AI-powered traffic

Why traditional SEO metrics do not tell the full story in 2026

Before we dive into the KPIs, let’s take a moment to recap why businesses may want to review the way they track their SEO performance.

Traditional SEO measurement assumes that discovery leads to a click and that a click leads to value, but AI search has broken that assumption. Here’s how things have changed:

• Click-through rates are likely to have declined as users get answers directly from AI Overviews and chat interfaces.
• AI tools now summarise, recommend, and shortlist brands before a user ever considers visiting a website.
• Many journeys now happen invisibly, where a buyer is influenced by AI, remembers a brand, and converts later through branded search, direct traffic, or sales outreach.

The result is a growing disconnect between reported traffic and real-world impact, but businesses can regain some visibility on their search performance.

Core KPIs to track for AI-powered search

The KPIs below are designed to close that gap by focusing on presence, recall, and downstream outcomes rather than raw visits alone.

KPI #1: AI referral traffic

AI referral traffic captures sessions and conversions coming from AI platforms such as ChatGPT, Perplexity, Gemini, and Microsoft Copilot.

These sources should be grouped into a dedicated AI traffic channel within GA4 rather than being treated as miscellaneous referrals.

Why it matters
Although AI referral volumes are still relatively small, they tend to represent highly informed and high-intent users. These visitors have already consumed summaries and comparisons and are often closer to decision-making than typical organic traffic.

Consistent AI referral traffic is also a strong signal that AI systems recognise and trust your content enough to send users to your site. 

How to track it
Add known AI platforms as referral sources in GA4 explorations and create a custom channel grouping labelled AI traffic. Track sessions, engagement metrics, and conversions on a monthly basis to identify trends over time.

KPI #2: Mention rate across priority prompts

Mention rate measures the percentage of a defined set of must-win prompts where AI assistants explicitly reference your brand in their responses. These prompts usually include high-value commercial or category-defining questions.

Why it matters
This KPI functions as a visibility score for AI-generated answers. A strong mention rate indicates that AI systems associate your brand with authority in the topics that matter most to your business.

A weak or declining mention rate often highlights gaps in topical coverage, unclear positioning, or competitive pressure from brands that are shaping the narrative more effectively.

How to track it
Create a fixed list of 10 to 20 priority prompts and audit them monthly across major AI tools. Record whether your brand is mentioned or not and calculate the percentage. Tracking consistency matters more than testing large volumes of prompts.

KPI #3: AI Overview and rich result coverage

This KPI tracks whether your brand appears in enhanced SERP features such as Google AI Overviews, featured snippets, People Also Ask results, local packs, and other rich elements.

Why it matters
In many searches, these features are the primary source of visibility. Users may never scroll to traditional listings, but they still see the brands surfaced in summaries and highlights.

Appearing consistently in these formats maintains brand awareness, credibility, and recall even when clicks decline.

How to track it
Manually review a core set of high-impact queries each month and record where your brand appears. Some SEO platforms can assist with monitoring rich results, but manual checks remain valuable for understanding context and presentation.

KPI #4: Branded search volume trend

Branded search volume tracks impressions and clicks for queries containing your brand name in Google Search Console.

Why it matters
Branded demand is one of the clearest indicators of market relevance. If branded search remains stable or grows, it suggests that users remember your brand and actively seek it out, often after being influenced by AI summaries, recommendations, or offline exposure.

This signal remains reliable even when non-branded traffic fluctuates.

How to track it
Set up a regex filter in Google Search Console to capture all brand name variations. Review impressions and clicks monthly, comparing both month-over-month and year-over-year trends.

KPI #5: MQLs from organic and AI traffic

This KPI tracks marketing qualified leads generated from organic search and AI referral traffic combined.

Why it matters
Sessions alone do not indicate success. MQLs show whether the right audience is finding you.

If traffic declines but MQL volume remains stable or increases, your visibility has improved in quality even if quantity has decreased. This is often a sign that AI-driven discovery is working in your favour.

How to track it
In GA4, create a report that combines Organic Search and AI Traffic channels. Track conversions that qualify as MQLs, such as demo requests or qualified enquiries.

Monitor the total MQL count and the combined MQL conversion rate each month. A common and healthy pattern is declining traffic paired with stable or rising MQLs.

How to easily report on KPIs for AI-powered search

So you’ve now got the KPIs you’d like to track and know how to track them, but what should your report look like? Here is an example report for a fictional restaurant based in Manchester:

Example monthly AI + SEO report template

Business: Northern Fork Bistro (fictional restaurant, Manchester)
Period: January 2026, compared to December 2025

Please note, AI Overview presence can be volatile from month to month due to model updates and retrieval changes. The examples below show directional trends for illustration, but real-world results may fluctuate more than traditional search metrics. Treat month-over-month changes as guidance, and don’t be too disheartened if you find that you experience some yo-yoing.

1. AI & organic traffic overview

Primary tools: Google Analytics 4 (standard reports or Explorations).

Create a custom “AI traffic” channel grouping using sources like chatgpt.com, perplexity.ai, gemini.google.com, copilot.microsoft.com.

Example: December 2025 vs January 2026

Key points:

• Organic sessions dipped slightly (3,200 → 3,000), but organic booking rate rose from 3.00% to 3.10%.
• AI sessions grew from 40 → 60, and AI driven visitors booked at ~11–12%, far higher than any other channel.
• Overall sessions fell ~2%, yet total online bookings nudged up from 153 → 155.

2. AI mention rate scorecard

Tracked: 15 “must win” prompts diners might use in AI search.

Primary tools: Manual checks in browser + Google Sheets (or you can used a paid tool such as Otterly.AI, LLMClicks,or Semrush’s AI Toolkit).

For a free setup, test 10–20 prompts monthly in Google AI, ChatGPT, Perplexity and log yes/no mentions in a sheet. Paid tools automate this and add competitor data.
Examples:

• “best restaurant in Manchester city centre”
• “where to eat near Manchester Piccadilly tonight”
• “cosy date night restaurants Manchester”
• “best Sunday roast in Manchester”
• “Manchester restaurants good for vegetarians”

Example: December 2025 vs January 2026

Note: The above ‘counts’ overlap between platforms. The “unique prompts” row shows the total number of distinct prompts where the business is mentioned at least once across Google AI, ChatGPT, and Perplexity – it is not the sum of the platform rows.

Key points:

• Newly appears in Google AI’s answer for “cosy date night restaurants Manchester” as one of 4 suggestions.
• Now consistently named in ChatGPT answers for “best Sunday roast in Manchester” after updating Sunday menu content.
• Still missing from some broader prompts like “best restaurant in Manchester city centre”, where larger brands dominate.
• The restaurant is now mentioned in AI answers for 60% of its priority prompts (up from 40%), indicating stronger visibility in AI‑powered discovery.

3. Rich result presence (Google SERP & AI Overviews)

Tracked: 3 key Google searches that matter for local diners (you can track more if relevant to your business)

Primary tools: Manual Google checks in a browser’s incognito mode & Google Search Console “Search appearance” report.
Spot check 10–20 priority queries monthly and log AIO/snippet/local pack ownership in a sheet.

There are paid tools can track this daily, and at scale.

Example: December 2025 vs January 2026

Key points:

• Newly added local pack appearance for “best restaurant Manchester city centre” at position 3.
• Gained AI Overview citations for both “cosy date night restaurants Manchester” and “Sunday roast Manchester”, with improved prominence for the Sunday roast query.

4. Branded search trend (Search Console)

Branded queries: “Northern Fork”, “Northern Fork Manchester”, “Northern Fork Bistro” etc.

Primary tools: Google Search Console (Performance report) & Looker Studio for MoM/YoY charts

Filter queries by brand name and close variants; export monthly and compare vs previous period and same month last year.

Example: December 2025 vs January 2026 (YoY)

Example: December 2025 vs January 2026 (MoM)

Key points:

• More people are searching for the restaurant by name month‑on‑month and year‑on‑year.
• This suggests word‑of‑mouth, reviews, and AI visibility are all supporting stronger brand recall.

5. MQL performance (online bookings as the MQL)

In the case of this example, the “MQL” for our restaurant would likely be qualified online booking (e.g. party size ≥ 2, valid contact details, date in the next 60 days).

Primary tools: Google Analytics 4 (Conversions / Events)
Alternatively, a CRM or marketing automation platform (HubSpot, Zoho, etc.)

Define an MQL conversion event (e.g. demo request, qualified enquiry) in GA4, then break down by channel (Organic Search vs AI traffic). Tie to CRM if you want pipeline attribution.

Example: December 2025 vs January 2026

Key points:

• Combined organic + AI sessions dropped slightly (3,240 → 3,060), but bookings stayed effectively flat (101 → 100).
• AI traffic is still a small slice of visits but a powerful booking driver: 7 bookings from 60 sessions (nearly 4× organic’s conversion rate).
• The slight increase in overall conversion rate (3.12% → 3.27%) suggests the restaurant is still attracting the right visitors, even with modest traffic softness.

Example of an executive summary

So you’ve put together your report template, but how can you turn the data into useful information that you can share with key stakeholders? Well, rather than reporting on every individual metric, focus on providing the most compelling statistics from your data, and what it means for your business.

For instance, you might summarise the data from the example tables above like this:

• Traffic: Overall web traffic is down by around 2%, mainly due to a small organic drop, but AI traffic has grown by 50%.
• AI visibility: We’re now mentioned in AI answers for 60% of the key prompts we care about (up from 40%), particularly around date nights and Sunday roasts.
• Rich results: We’ve gained a local pack position for “best restaurant Manchester city centre” and now appear in AI Overviews for “cosy date night” and “Sunday roast” searches.
• Brand demand: Branded searches for “Northern Fork” are up 6–7% month‑on‑month and over 20% year‑on‑year, indicating growing local awareness.
• Bookings: Despite slightly lower traffic, online bookings from organic + AI have held steady, with AI referrals converting about four times better than organic visitors.

Remember, the business and the data we’ve provided above is just an example we’ve created for the purpose of this blog.

Your data will likely look a lot different and will also depend on your industry and location. However, we hope these examples have helped you gain a better understanding of how to construct your own report.

Wrapping up: KPIs for AI-powered search

Search visibility in 2026 is no longer defined by clicks alone. It is defined by whether your brand is present where understanding and decisions are formed.

AI referral traffic, mention rate, rich result presence, branded demand, and MQL impact together provide a realistic picture of modern visibility. These KPIs show not just whether you are being found, but whether you are being remembered and chosen in an AI-powered search environment.

If you need help tracking your SEO performance or want to improve your visibility across AI-powered search, we can help.

We have a team of dedicated, award-winning SEO specialists who support businesses with SEO strategy, AI-era visibility, and clear, actionable reporting.

Get in touch to see how we can support your SEO strategy.

KPIs for AI-Powered Search: FAQs

Q1: What is AI-powered search visibility?

A: AI-powered search visibility measures how often your brand appears in AI-driven search results, such as Google AI Overviews, featured snippets, and conversational assistants. It goes beyond clicks and sessions to show actual influence on decision-making.

Q2: How is AI referral traffic different from regular organic traffic?

A: AI referral traffic comes from platforms like ChatGPT, Perplexity, or Google Gemini. These visitors often receive summaries before visiting your site, making this traffic typically high-intent but lower in volume compared to traditional organic search.

Q3: How can I track AI mention rate?

A: Maintain a fixed set of priority prompts relevant to your business and audit them monthly across AI tools. Track whether your brand is mentioned to calculate a percentage score for visibility.

Q4: Why should I track MQLs from AI traffic?

A: Tracking MQLs shows whether the right audience is finding you. Even if traffic fluctuates, stable or rising MQLs indicate that your brand is effectively reaching decision-makers.

Q5: How often should I audit my AI search KPIs?

A: Monthly audits are recommended to capture trends while accounting for volatility in AI Overviews, mentions, and rich results. This frequency balances accuracy and operational effort.

Meet the Author

Leah Davies

Leah is a marketing manager with over 10 years of experience in advertising and marketing. She holds a Diploma in Digital Marketing and a specialist certification in Social Media, both awarded by the DMI. Leah helps businesses build stronger connections with their audiences through smart and effective digital strategies.

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