TL;DR
A simple scoreboard that includes per-topic inclusion rate, share of citations, and link-in-summary count will tell you where to prioritise content and engineering work to be seen inside AI Overviews and other generative answers.
Generative answer blocks (AI Overviews) are appearing across a meaningful slice of queries and shifting where clicks land; leaders must treat this as a measurement problem, not a debate. Conductor and SISTRIX tracking put AIO prevalence in the mid-teens to high-teens for many keyword sets, with pronounced country variance. Pew Research’s log-level browsing analysis shows click-through behavior falls substantially when AI summaries are present, and clicks inside the summaries are very rare. That combination of prevalence plus low link clicks means inclusion metrics (how often your domain is cited) are now a primary visibility KPI.
Why Should Leaders Care About AEO/GEO?
AI-driven answers change who gets exposure and how users discover content. If you measure only blue-link rankings, you miss whether your brand appears inside the answer itself, where users often stop. Shifting budget and editorial priorities without topic-level evidence risks both wasted spend and lost visibility.
What Should You Track For Each Topic?
For each topic, track three key metrics: how often your domain is cited (inclusion rate), the proportion of total citations you receive (share of citations), and how frequently your URL appears as a link inside the AI summary (link-in-summary). Also log traditional SERP features (People Also Ask, featured snippets) and the content formats AIO prefers (FAQ, short stats, extractable quotes). Use that combined view to prioritise pages for rewrite or markup.
How Do You Build This Scoreboard?
1. Build a topic map with 50–150 canonical queries per topic. This gives consistent samples to measure inclusion over time and reduces noise from one-off queries. It becomes the canonical set for benchmarking and change-tracking.
2. Crawl daily and parse AI Overviews with an AIO endpoint; store each snapshot and the citations it shows. Regular sampling reveals trends and lets you compute inclusion deltas after changes.
3. Run a parallel feature inventory using a rank tracker that logs SERP features by query. That context shows whether AIOs displace or complement other features.
4. Set topic baselines and simple green/yellow/red thresholds using category norms (informational long tails vs product queries). Thresholds make prioritisation operational.
5. Implement content and technical changes: add attributable stats, named entities, extractable quotes, and schema that mirrors visible text (schema parity). Track pre/post inclusion to prove impact.
Show & Tell
Example: Consider the topic “SOC 2 checklist.” Start by validating your page with Google’s Rich Results Test, then add FAQPage and SoftwareApplication markup that exactly matches the visible content. Next, use an AI Overview parser such as SerpApi to crawl the search results daily and log which citations appear. After rewriting the page with an answer-first approach and ensuring schema parity, track how your inclusion rate and share of citations change over time. This process shows whether your updates made the content easier for AI systems to lift and highlights where further optimisation is needed.
Takeaway
Treat AEO/GEO work as engineering plus editorial: you need a repeatable scoreboard, daily sampling, and small, testable content changes. Move from opinions about “what works” to topic-level evidence you can track and report to the C-suite.
Micro-Glossary
Inclusion Rate (AIO): % of sampled queries in which your domain is cited.
Share Of Citations: Your citations ÷ all citations shown in AIO for the topic.
Schema Parity: Structured data that exactly reflects visible page content.
