A CRO testing roadmap: prioritization without theatre

Every optimisation team eventually adopts a prioritisation framework — ICE, PIE, a weighted spreadsheet — and most of them decay into theatre: confidence scores invented to justify the test someone already wanted. The framework isn't the problem; unanchored inputs are. A roadmap works when its inputs are evidence, arithmetic, and honesty about capacity.

Rank by evidence strength, not enthusiasm

A test idea backed by research — recordings showing the problem, survey answers naming it, funnel data locating it — deserves priority over any brainstorm output, whatever the confidence column says. Grade the evidence, and let “we have none” send ideas back to research instead of into the queue.

Let traffic arithmetic veto early

A test needs enough conversions to conclude in reasonable time — a page with a handful of weekly conversions can't support subtle tests, period. Do the sample-size maths before queueing, per honest testing practice; low-traffic pages get research-informed redesigns and micro-conversion measurement instead of fake experiments.

Weight impact by page value

A modest lift on the pricing page or quote flow is worth more than a dramatic one on a page nobody commercial visits. Impact estimates should start from what the page is worth, not how big the change feels.

Finish tests before starting tests

The commonest roadmap failure isn't order — it's abandonment: tests stopped early, results never written up, learnings evaporating. Cap concurrent experiments to what you can actually analyse, and define “done” as documented, not stopped. A finished test teaches even when it loses; an abandoned one costs traffic and teaches nothing.

Feed learnings back into the queue

Every result re-scores the neighbours: a winning trust-signal test raises the priority of trust work elsewhere; a flat headline test lowers cousins' confidence honestly. The roadmap is a learning loop, not a backlog — reviewed monthly, re-ranked by what the last cycle proved.

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