From clicks to quality: 12 KPIs you must track in the age of AI

For a long time, marketing teams measured their success through classic indicators: clicks, rankings, impressions… These metrics made sense in a world where each search led to a results page with links to click. But today, with the rise of generative AI, the game has changed.

Users no longer need to scroll through a list of results. Thanks to tools like ChatGPT, Perplexity or Claude, they get instant answers without clicking. So the question is: do these old KPIs still have a place?

The real challenge today is finding metrics that truly reflect the impact of our content and its usefulness to our audience.

The old-school dashboard: not everything should be thrown away, but it needs to evolve

Traditional KPIs have long been at the heart of SEO strategies. We know them well, the indicators that guided us for years:

• Organic sessions
• Click-through rate (CTR)
• Average position
• Bounce rate
• Time on site
• Pages per session
• Number of backlinks
• Domain Authority (DA)

These metrics were essential for knowing where we stood, especially when the goal was to slip into the top 10 results. But in a world where AI takes over, these old metrics are no longer sufficient. They remain useful, of course, but they must be complemented by new measures better suited to today’s challenges.

The new dashboards in the AI era

The arrival of AI has upended the way users interact with content. Gone are the days when they were content to browse result pages to find what they were looking for. Today, systems like ChatGPT or Gemini provide immediate answers integrated directly into the conversation, often without the need to click.

Faced with these changes, traditional KPIs become less relevant. It’s no longer just a question of ranking among the top results, but of knowing whether your content is actually used, cited and deemed relevant by AI. Here are the new indicators to follow to stay in the race:

• Content retrieval rate : Measure how much your content is retrieved and used by AI tools.
• Quality of integration in generated responses : Assess whether your content appears in the synthetic answers provided by AI systems.
• AI response time : Analyze how quickly your content is used in AI-generated results.
• Citation rate : How many times is your content cited in AI-generated responses or snippets?
• Contextual relevance : Measure the relevance of your content when it is used in AI-generated answers, based on users' questions.
• Perceived authority in AI : Instead of relying on backlinks, assess the perceived authority of your content by language models (LLMs).

Old KPIs don’t disappear, but it’s now essential to supplement them with indicators that take into account how AI handles, interprets and distributes information. It’s a new era, and it’s time to track what really matters.

12 emerging key performance indicators (KPIs) for the era of AI generative search

Here’s a refined version of the KPI list, where I grouped some overlapping indicators and noted KPIs that can be difficult to measure.

1. Content retrieval frequency

• What is it? The frequency with which a content block is retrieved by AIs to answer queries.
• Why is this useful? This measures the visibility of your content in AI-generated answers. A high rate shows that your content is perceived as relevant and is used by AIs to generate responses, giving you greater exposure without direct clicks.

2. Embedding relevance score

• What is it? A measure of the similarity between user queries and your content, calculated using vector embedding algorithms.
• Why is this useful? This KPI checks whether your content aligns with users' true intent, which is essential for it to be used in AI-generated answers. A high score means your content is relevant to searches.

A tool to try for that: https://gofishdigital.com/similarity-score-agital-extension/

3. Citation rate in AI-generated answers

• What is it? The number of times your content is cited or referenced in answers generated by AIs like ChatGPT or Gemini.
• Why is this useful? A high rate indicates that your content is perceived as authoritative and reliable by AI models. It helps you measure the recognition of your brand or site within the AI-generated search ecosystem.

A tool to test this: https://www.abondance.com/seo-tools/qwairy

4. Interaction rate with AI-generated content (Generative Content Interaction Rate)

• What is it? The number of user interactions with summaries, snippets, or content generated by AI.
• Why is this useful? This measures the effectiveness of your content in an AI-generated format. A high interaction rate shows that users find your content useful even before clicking a link.

5. Conversion rate of AI queries

• What is it? The conversion rate of users after interacting with AI-generated responses.
• Why is this useful? This measures how effective your content is at driving a concrete action after being used in AI responses (purchase, sign-up, etc.), which is essential for evaluating the return on investment of your content in an AI environment.

6. Content retention rate

• What is it? The percentage of users who return to view the same content again after finding it via an AI response.
• Why is this useful? This shows that your content is relevant and useful enough to be consulted repeatedly, which is a sign of sustained value in an AI-powered search environment.

7. Engagement on generative search platforms

• What is it? The level of engagement (shares, mentions, comments) generated by your content on AI platforms.
• Why is this useful? This metric measures the impact of your content within AI search environments and indicates the virality of your content without relying on traditional links.

8. Time spent on AI-generated content

• What is it? The amount of time users spend interacting with your content after it has been recommended by AI.
• Why is this useful? The more time users spend reading or interacting with the generated content, the more it indicates that your content is perceived as relevant, engaging, and useful for meeting their needs.

9. Presence of visual content in generated responses

• What is it? The frequency with which your visual content (images, products, etc.) is included in AI-generated responses.
• Why is this useful? Visual content adds value to AI responses. The more your visual assets are retrieved and incorporated into these responses, the more it demonstrates the importance and richness of your multimedia resources in AI-based searches.

10. Rate of brand mentions by AI

• What is it? The frequency with which your brand is mentioned or suggested in AI-generated responses across various platforms.
• Why is this useful? The more your brand is mentioned in AI-generated responses, the more it reflects your brand's recognition and strength within the AI ecosystem.

11. AI crawl success rate

• What is it? The percentage of pages on your site that AI bots can ingest and use.
• Why is this useful? A high rate indicates that your site is well optimized for indexing by AI systems, ensuring its visibility in AI-generated responses.

I encourage you to use log analysis tools to track hits on your content coming from LLM search bots.

12. Content freshness index

• What is it? A measure of how up-to-date and currently relevant your content is compared to AI-generated queries.
• Why is this useful? AIs favor fresh, regularly updated content. Tracking this KPI helps you keep your content relevant in an environment where speed and freshness are essential.

KPIs that are still hard to measure

On paper, these new KPIs look perfect and should allow us to closely monitor the performance of our content. In reality, some of these indicators are still difficult to measure, and sometimes almost impossible to obtain with current tools.

AI platforms don't always give us access to all the data we need, such as the exact frequency with which our content is used in their responses or how the AI assesses its authority. Some data simply aren't available, and others can be subjective—like the authority perceived by the AI, which varies with the algorithms.

In other words, while it's tempting to try to track these KPIs perfectly, it's important to keep in mind that measuring these elements remains a challenge and we'll sometimes have to accept working with partial information.

AI, a new perspective on quality?

AI is finally pushing us to measure what really matters: the quality of our content, the engagement it generates, and its ability to be cited or used, because truly visible and qualified.

After 20 years focused on metrics like clicks and impressions, it's time to follow indicators that make sense for the user. Ultimately, what matters today is knowing: Is my content good and relevant for my target audience? That's the only question that matters now.

By the way, I'd be curious to know which initial KPIs you track. Looking forward to seeing the first dashboards set up in Looker Studio and other visualization tools.

Want to get started but don't know where to begin?

The Looker Studio Training is here to guide you.

Discover Chloé's best practices for creating standout dashboards in Looker Studio for SEO — yes… but in the age of AI, of course.