What’s the Average Lift in Search Impressions from AEO?
There isn’t a universal “average.” Lift depends on baseline authority, topic selection, page count, internal linking, and schema quality. Here’s how to measure your own result correctly.
How to Calculate Impressions Lift
Metric | Formula | Window | Notes |
---|---|---|---|
Cluster Impressions | Sum(GSC impressions for pillar + all Q&A URLs) | Daily; aggregate weekly | Use a URL regex or GSC page filter |
Baseline | Avg weekly cluster impressions (pre-launch) | 4–8 weeks prior | Exclude outliers and sitewide spikes |
Post-launch | Avg weekly cluster impressions (post) | Weeks 5–12 after first ship | Allow for crawling/indexing lag |
Lift % | ((Post − Baseline) ÷ Baseline) × 100 | Report monthly | Repeat per cluster; compare cohorts |
Complement impressions with queries answered (appearance in People Also Ask/AI answers), non-brand clicks, and assisted conversions to confirm commercial impact.
What Drives Higher (or Lower) Lift
Topic selection
Choose questions closest to revenue (pricing, implementation, comparisons). Demand-rich topics lift faster.
Page volume & depth
Clusters with ~100 interlinked Q&A pages send a stronger expertise signal than partial builds.
Answer clarity & structure
Direct answers near the top, scannable headings, lists/tables, and consistent terminology.
Technical hygiene
Clean canonicals, fast pages, accurate schema (FAQ/QAPage/Article), and internal links from pillar to children.
Reporting Template (What to Share Monthly)
Section | What to include | Owner | Decision |
---|---|---|---|
Impressions Lift | Baseline vs. post; % change; top 10 queries | SEO/Content | Scale or fix |
Answer Surface | Featured snippets, PAA nodes, AI answer cites | SEO | Prioritize gaps |
Engagement | CTR, time on page, bounce for Q&A pages | Web Analytics | Refine intros & links |
Pipeline impact | Assisted conversions, first-touch pipeline | RevOps | Expand to next cluster |
For architecture and examples, see the AEO Overview and the Complete AEO Guide.