How Leading Retailers Choose a Prioritisation Framework

Comparison graphic showing four test prioritisation frameworks on a spectrum from subjective to evidence-based: PIE and ICE (subjective sliders, 3 subjective factors), PXL (mostly binary, yes/no questions), and REO's own model (evidence-based, weighted by evidence).

How leading retailers decide what to test Ask most CRO teams how they choose what to test next, and you’ll hear some version of “we look at the analytics and pick what seems broken.” It sounds reasonable. It’s also how most testing programmes end up with a backlog full of button-colour experiments and homepage banner […]

The Hidden Cost of Low Testing Velocity

Bar chart showing the number of test winners found per year at different testing volumes, at a 36.3% win rate: about 1 winner from 4 tests, 5 winners from 14 tests, and 9 winners from 24 tests a year — winners rise with testing volume, not win rate.

The real cost of low testing velocity The standard pitch for testing velocity goes: run more tests, find more winners, grow revenue faster. It’s true, but it’s also the least interesting reason to care about velocity, and it’s not the argument that actually gets budget approved. If you want the tactical how-to on running the […]

Why experimentation programmes lose momentum

Line graph illustration showing momentum rising, flattening during 'the stall,' then breaking upward again into 'recovery,' in REO's cerise red and green brand colours on a dark navy background.

Why your CRO programme stalls (and how to fix it). Most teams assume their CRO programme dies from a lack of ideas. You run out of hypotheses, the backlog goes quiet, testing slows down. Fix the ideation problem and the programme comes back to life. Actually, that’s rarely what kills a programme. In over a […]

Sign up

Worried we'll send you crap? Don't. No crap. No spam. Only the best insights.

This field is for validation purposes and should be left unchanged.
Name(Required)