Purpose: Run your own current figures down a single column, read each against the benchmark its step chapter settled on, and find the one weakest lever capping the whole chain. That lever is where the next multiplication is waiting — fix it before any other.
When to run it: Monthly for the figures-only review; quarterly for the full cascade, constraint identification, and loop audits; ad hoc whenever any step’s primary metric falls below its band for two consecutive periods.
Inputs: Current analytics for all nine levers, pulled live from your platform — not estimates, not last quarter’s numbers rationalised upward. Foundation Blueprint to hand for the cross-check.
The Dashboard
Fill Your metric from live analytics. Read it against the band. Write the gap (below / inside / above), then the single action.
| Step · Lever | Your metric | Healthy benchmark band (as settled in-chapter) | Gap · Action |
|---|---|---|---|
| HOOK · Click-through rate | __________ (your CTR by channel) | Paid social avg 1.71% (traffic) / 2.59% (leads); Google Search avg 6.42–6.66%; Google Display ~0.46%; email open 30–45% reported (Apple MPP inflates by 10–15pp; true ~20–25%) | __________ (below/in/above — and the one fix: angle, visual hook, specificity) |
| GIFT · Landing-page opt-in rate | __________ (your opt-in %) | Median ~6–7% across all pages; email-driven ~19.3%; warm top performers ~20%+; below ~6% underperforming | __________ (promise specificity · hook–gift match · credible quick win) |
| IDENTIFY · Form-completion rate | __________ (your completion %) | Warm traffic 10–30% (top 20%+); cold paid 5–15%; each extra field cuts conversion ~4.1%; avg checkout 11.3 fields vs ideal 8 | __________ (field count · button names benefit not action · trust/privacy note) |
| ENGAGE · Cart abandonment / assisted conv. | __________ (your abandonment %) | Abandonment ~68–72% (≈28–32% completion) is the baseline; below it is progress | __________ (late costs · forced account · checkout length · unanswered doubt) |
| SELL · Conversion rate | __________ (your conversion %) | Average 1.4%; global ~1.7–1.89%; above average 2–3%; top 10% 4.7%+ | __________ (traffic-quality · missing page section · unhandled objection · friction) |
| SELL · Checkout completion | __________ (your completion %) | Desktop avg ~52.5%, mobile avg ~42.4%; top-quartile desktop ~73.2%; cart abandonment 70.22% (48% extra costs; 26% forced account; 17% too long) | __________ (late costs · field friction · no guest checkout · payment trust) |
| NURTURE · Welcome / sequence engagement | __________ (your open/click %) | Open 30–45% reported (true ~20–25%); click 1.5–4% (ecommerce avg 1.74%); welcome opens ~34–36%; cross-industry up to 80%+ | __________ (subject lines · list hygiene/deliverability · delivery delay) |
| NURTURE · Abandoned-cart recovery | __________ (your recovery %) | 3.33% placed-order rate per email; 5–15% program-level recovery (full multi-step flow) | __________ (too slow · too generic · real objection unaddressed) |
| UPSELL · Post-purchase take-rate | __________ (your take-rate %) | Post-purchase upsell avg 5–15%; top performers 25–30%; in-cart order bump 10–35%; avg 30–40% for well-matched offers | __________ (offer relevance · acceptance-path friction · price vs primary order) |
| UPSELL · Average-order-value uplift | __________ (your AOV uplift %) | A well-run step adds 10–30% to mean AOV | __________ (take-rate too low · offer priced too low · measure net of returns) |
| EDUCATE · 365-day repeat-purchase rate | __________ (your repeat %) | Overall avg ~18.8%; consumables 25–40%; fashion 12–17% | __________ (activation moment · consumption gap · re-order prompt timing) |
| EDUCATE · NPS / CSAT | __________ (your NPS / CSAT) | NPS +50 strong, +20–49 solid, 0–19 mediocre, below 0 structural; CSAT acceptable 3.5–4.0 on 1–5; cross-industry avg 78% | __________ (promise-delivery gap · post-sale silence · broken first use) |
| SHARE · Referred-customer LTV uplift | __________ (your referred LTV uplift %) | ≥16% higher LTV; 18% lower churn; ~4× more likely to convert | __________ (rewarding the act not advocacy · share mechanism too effortful) |
| SHARE · Reviews → conversion lift | __________ (your measured lift %) | A measurable uplift, strongest as the first reviews appear; varies by price and category | __________ (reviews too few/generic · proof not shown at the decision) |
(Every band above is orientation drawn from each step chapter’s named source — not a precision target. Date-stamp any internal goal you derive; verify each figure against its current published source before citing publicly; refresh the whole dashboard quarterly. Read “roughly 20–40%”, never “27.4%”.)
Metrics Cascade — symptom to cause
The dashboard shows where the gap is visible. The cascade shows where the cause lives — often one lever upstream. Read a weak result backwards before fixing anything, and revisit the worksheet named.
| The symptom you see | Likely weak lever (cause often upstream) | Worksheet to revisit |
|---|---|---|
| Revenue flat despite healthy traffic | Any single weak lever multiplying the rest down | Run this whole dashboard; fix the earliest below-band figure first |
| Low conversion rate | SELL page leak — or NURTURE sending under-warmed leads — or HOOK wrong audience | SELL, then NURTURE, then HOOK |
| Low opt-in rate | Weak GIFT / high-friction IDENTIFY form — or HOOK pulling the wrong people | GIFT and IDENTIFY; re-check HOOK message-match first |
| Carts abandoning at checkout | Late costs, forced account, unanswered doubt — usually structural in SELL | ENGAGE and SELL (walk your own checkout on a phone) |
| Leads go cold, lead-to-customer low | Weak NURTURE sequence — or an unqualified list from GIFT | NURTURE; check GIFT lead quality by segment |
| Low repeat-purchase / weak LTV | Post-sale silence at EDUCATE — or a SELL page that overpromised | EDUCATE and SELL (read both back to back) |
| Few referrals, weak advocacy | Premature/effortful SHARE ask — or EDUCATE produced no successful customers | SHARE; confirm EDUCATE is producing wins |
| Referrals arrive but low-value | SHARE incentive rewarding the act over genuine advocacy | SHARE (compare referred LTV to your average) |
Instructions
- Populate from live data. Pull each step’s primary metric from your analytics platform into Your metric. No estimates; no figures older than the current measurement period.
- First pass — absolute. For each row, mark below / inside / above the band. Inside means leave it alone. A figure far above its band is not always a win — high GIFT opt-in can mean freebie-seekers, not buyers.
- Second pass — comparative. Among the below-band rows, find the largest gap that sits earliest in the chain. That row is your candidate constraint.
- Run the cascade. Use the table above to test whether the cause sits at that step or one lever upstream, then revisit the worksheet named. Form one specific hypothesis.
- Brief the AI. Feed
prompts/Optimize.mdyour Foundation recall and the full dashboard figures; let it propose the constraint and A/B tests; weigh its reading against your own. Never act on a recommendation you cannot trace to a number here. - Test one thing. Change a single variable, name the metric to move, set the minimum sample and duration, and log the baseline. Change nothing else while it runs. Read it at the predetermined time, not after a single good day.
- Refresh quarterly. Re-run the dashboard, find the new constraint the old one was hiding, and begin the next turn.
Feeds → improvements flow back into every step: the diagnosed constraint sends you back to its step worksheet; the test outcome updates that step’s baseline; the loop audits route SHARE proof into HOOK and SELL and EDUCATE feedback into the Foundation. This worksheet closes the loop — measure, diagnose, hypothesise, test — and hands a tighter chain back to the Foundation each turn.
Sources: 5-refine.md · prompts/Optimize.md · the REFINE SOP — “Measure the chain, find the constraint, improve it”.