How Do You Test Which Clusters Drive the Most Revenue?
Compare content clusters with controlled experiments and account-level attribution: run geo/page holdouts or sequential rollouts, apply multi-touch models, and read lift in influenced pipeline and won revenue.
The Short Version
Pick two or more AEO clusters, instrument them as content groups, and run a fair test: either hold out a region/page set or roll out clusters sequentially. Stitch users to accounts, apply position-based and time-decay models, and compare influenced pipeline, win rate, and revenue per view to identify the highest-ROI cluster.
Keep the creative pattern identical across clusters so differences reflect topic value—not page templates.
Recommended Test Designs
| Option | Best For | How It Works | Pros | Cons |
|---|---|---|---|---|
| Geo Holdout | Large traffic, multi-region | Launch Cluster A in Regions 1–3; hold Region 4 as control | Causal read; clean ops | Needs sizable volumes |
| Page Holdout | Single-region sites | Publish 70–80% of pages; hold 20–30% back as control | Fast to run; granular | Risk of spillover |
| Sequential Rollout | Limited resources | Ship Cluster A in Q1, Cluster B in Q2; compare pre/post | Operationally simple | Seasonality effects |
| Budget Split | Paid amplification | Even ad budget to each cluster’s pages | Quick signal | Less causal than holdouts |
Run the Test Correctly
Tag every page with Cluster ID; sync to analytics and CRM.
User → account via email capture, SSO, or reverse-IP.
Position-based + time-decay; compare with last-click.
Track “next question” clicks as assists between pages.
Log citations (SGE, Copilot, ChatGPT) as exposure events.
Freeze templates during tests; log any material changes.
4–8 Week Experiment Timeline
Choose 2–3 clusters; define control; implement tags, UTMs, and events (pageview, internal-link, form, meeting).
Publish pages; validate schema and link hygiene; verify account stitching and dashboards.
Hold steady; track exposure, engagement, pipeline; note anomalies and external spend.
Compare lift vs. control; analyze revenue per view; green-light the winner for scale.
Revenue Metrics & Targets
| Metric | Formula | Target/Range | Stage | Notes |
|---|---|---|---|---|
| Influenced pipeline | Opps with ≥1 cluster touch | Top cluster 20–40% higher | Pipeline | Account-level dedupe |
| Revenue per view | Won revenue ÷ page views | Rank clusters by RPV | Outcome | Controls for traffic |
| Win-rate delta | Test win% − control win% | +2–6 pts | Sales | Read by segment |
| Internal-link CTR | Next-question clicks ÷ views | 15–40% | Engagement | Journey strength |
| Assistant inclusion | Citations/mentions per cluster | Upward trend | Reach | Log surface type |
How to Read Results—and Act
Rank clusters by revenue per view and influenced pipeline. Use multi-touch models to see where a cluster contributes—discovery, mid-funnel education, or late-stage objection handling. If a cluster wins on RPV but trails on impressions, expand coverage and paid support. If impressions are high but RPV is low, improve internal links to move visitors into higher-intent questions and add stronger micro-CTAs.
Keep tests honest: freeze page templates, record any off-site spend, and maintain a change log. After each readout, roll winners site-wide and queue fresh questions for the next test cycle.
Further Reading
Frequently Asked Questions
Cluster tags, UTMs, pageview and internal-link events, form/meeting events, and opportunity influence reports. Identity stitching improves accuracy.
Typically 4–8 weeks, depending on cycle length and traffic. Holdouts need enough time for opportunities to form.
Yes—AEO pages work for paid and organic. Track spend to interpret lift fairly.
Show position-based in the roll-up for clarity; keep time-decay in the analyst view. Always pair with holdout results.
Use distinct internal link paths during the test window, or choose geo/page holdouts where audiences don’t overlap.