The Metrics
Conversion rate is a lagging indicator. Below are the eight leading ones — the metrics that tell you whether your real-time activation layer actually exists, runs fast enough, and drives revenue.
The Hierarchy
Identity feeds Decisioning feeds Outcome. If identity capture is broken, decisioning has nothing to act on. If decisioning is slow, outcome never moves. Read the stack top-down to find the bottleneck.
Identity
KPI 01
How much of your traffic do you ever know? Most stores sit at 2–8%. Every percentage point unlocks owned-channel reach.
How to instrument
Count sessions where email, phone, or known login attaches before exit. Divide by total sessions. Track daily.
KPI 02
The faster you capture identity, the more session left for personalization. Late capture is half a CDP.
How to instrument
Log timestamp of first event vs identity event. Bucket by intent score and source. P50 and P95.
KPI 03
The Identity Signal Heatmap. Shows where the funnel leaks identity — exit intent popup, checkout, loyalty signup, etc. Reveals the highest-leverage capture moment.
How to instrument
Define funnel: landing → engaged → cart → identify → checkout. Plot identification at each step.
Decisioning
KPI 01
Anything slower and the bounce wins. Latency is the single most under-measured KPI in personalization stacks.
How to instrument
Tag event ingest timestamp. Tag DOM render timestamp. Diff. Pipe to time-series dashboard.
KPI 02
The decisioning brain has a job: pick the action that converts. Holdout-aware lift quantifies whether it does.
How to instrument
Run 10–20% holdout group on each campaign. Compare conversion rate of NBA-selected vs random or rule-default.
KPI 03
You cannot influence sessions you have no action for. Coverage is the ceiling on revenue impact. Below 60% means most visitors get no intervention.
How to instrument
Count sessions where at least one campaign / journey is eligible. Divide by total. Bucket by intent.
Outcome
KPI 01
The headline KPI. Did real-time intervention move conversion vs doing nothing? Without a holdout, you are guessing.
How to instrument
Run platform-level holdout (5–10% of sessions see no Convertive action). Compare CR weekly. Statistical significance over 4 weeks.
KPI 02
Identification only matters if it converts. Tracks the second leg of the funnel: did capturing identity actually pay off?
How to instrument
Cohort by identification source (popup, checkout, loyalty). Track 7-day and 30-day purchase rate.
KPI 03
Revenue language. Translates lift into a per-session unit so you can compare against ad spend and CAC. The number that gets the CFO nodding.
How to instrument
Revenue from treated cohort − revenue from holdout, divided by treated session count. Roll up monthly.
Reading the dashboard
If lift is flat or negative, latency is too high or the NBA ranker is picking weak actions. Pull P95 latency and selection-vs-random lift first.
If action coverage is below 40%, you do not know enough about the visitor to act. Identification rate and identity drop-off explain why.
The Identity Signal Heatmap shows which step bleeds the most. Most teams find one step that loses 50%+ — fix that, double identification.
Per-session lift is real but only on covered sessions. If coverage is 30%, total revenue impact is capped at 30% × per-session lift. Expand action library.
Conversion rate is a lagging, multi-causal metric. It moves on traffic mix, seasonality, promo cycles, and stack changes — drowning the signal from any one intervention. The KPIs on this page are leading indicators that isolate the in-session revenue infrastructure.
No. Start with three: identification rate, decision latency P95, and in-session lift (with a holdout). Those three tell you whether the infrastructure exists, runs in real time, and drives revenue. The rest are diagnostics that explain why.
Standard ecommerce KPIs (CR, AOV, sessions, revenue) measure store performance. These measure infrastructure performance — whether your real-time activation layer is doing its job. They sit upstream of CR and AOV and explain movement in those numbers.
Latency and coverage metrics are visible in 24 hours. Identification rate and time-to-identify stabilize in a week. In-session lift requires 2–4 weeks of holdout data depending on traffic volume to reach statistical significance.
Free 12-hr ROI audit benchmarks your store on identification rate, leakage, and recoverable revenue.