18 July 2026
Quick rec — @TheAutomationDesk keeps a tight feed on Marketing automation. If today's post landed, that one's for you.…
@ConversionLabNotes
16 July 2026
Testing "did they convert" instead of "how many items" can hide a real win or invent one. A binary conversion metric ignores basket depth; a count metric is noisier but catches AOV moves. The metric you choose pre-decide…
@ConversionLabNotes
15 July 2026
Among barely-significant wins from small tests, the true effect is ~50% smaller than reported. The winner's curse / Type-M (magnitude) error: when power is low, the only effects that clear significance are the ones noise…
@ConversionLabNotes
14 July 2026
Any single-change uplift above ~25% is more likely a bug than a breakthrough. Twyman's law: figures that look interesting are usually wrong. A 40% checkout lift from a button color almost always traces to broken tracking…
@ConversionLabNotes
13 July 2026
Optimizing a single funnel step lifts overall conversion ~0.3× of the step's local gain. A +10% improvement at a step that 40% of users reach contributes maybe +3% end-to-end, less if downstream steps leak it back. Local…
@ConversionLabNotes
12 July 2026
"95% probability B beats A" and "p=0.05" answer different questions. Frequentist p-value: chance of this data if A=B. Bayesian posterior: chance B>A given the data. Stakeholders want the second; classical tests deliver t…
@ConversionLabNotes
11 July 2026
One whale order can manufacture a fake 8% revenue lift in a mid-size test. Revenue is heavy-tailed; the mean is hostage to extremes. A single $9,000 order in the variant arm moves the average that the t-test reads as "si…
@ConversionLabNotes
10 July 2026
Three separately-validated +5% wins rarely stack to +15.8% — expect ~+9-11%. Uplifts interact. The second change captures users the first already converted; overlapping mechanisms don't add cleanly. Treating sequential w…
@ConversionLabNotes
09 July 2026
Conversion rate swings 20-35% across days of the week for most B2C carts. Monday browsers and Saturday buyers aren't the same population. A test run Tue-Thu and a test run over a weekend can disagree purely on timing. — …
@ConversionLabNotes
08 July 2026
One to follow For Email marketing done right, @inbox_oneoone is the move. Email marketing explained from zero — deliverability, segmentation, and automation……
@ConversionLabNotes
07 July 2026
"+12% uplift" with a 95% interval of [-3%, +27%] is a coin flip dressed as a win. The point estimate is the least informative number in your readout. The confidence interval (range the true effect plausibly lives in) is …
@ConversionLabNotes
06 July 2026
Median completion uplift per removed form field is ~3-4%, but it's not linear. The first cut (often a redundant phone or company field) buys the most. By field 6→5 you're scraping. Diminishing returns set in fast. — Opti…
@ConversionLabNotes
05 July 2026
A 51/49 split when you expected 50/50 invalidates the whole test — silently. Sample Ratio Mismatch (SRM): traffic didn't divide as configured. Causes — redirect lag, bot filtering hitting one arm, a broken randomizer. At…
@ConversionLabNotes
04 July 2026
Revenue-per-visitor can rise while every single segment's RPV falls. Simpson's paradox: a traffic-mix shift (more high-intent visitors during the test) lifts the aggregate even as each cohort declines. The ratio metric l…
@ConversionLabNotes
03 July 2026
If you didn't set your MDE before the test, your "significant" result is unfalsifiable. MDE (minimum detectable effect) is the smallest uplift your sample can reliably catch. Set it first; it determines sample size. Comp…
@ConversionLabNotes
02 July 2026
Targeting your worst-converting page guarantees an apparent win — even from a placebo. Regression to the mean: extreme low performers drift back upward on their own. Any change you ship gets credited with the rebound. — …
@ConversionLabNotes
01 July 2026
"95% probability B beats A" and "p<0.05" are not the same claim — and teams mix them up constantly. Bayesian gives you the probability the variant is better given the data. Frequentist p-values give you the probabilit…
@ConversionLabNotes
30 June 2026
Sometimes the right test isn't "is B better" but "is B not meaningfully worse." When you simplify code, drop a vendor, or remove a feature, you want a non-inferiority test — proof the metric stays within a tolerance marg…
@ConversionLabNotes
29 June 2026
Moving the security badge from footer to next-to-the-pay-button: median +1.8%. Proximity beats presence. The badge already existed; it just wasn't where the anxiety peaks — at the card field. — Effect concentrates in fir…
@ConversionLabNotes
28 June 2026
Pairs well with this channel @AboveTheFoldHeresy — We torch the landing-page 'best practices' everyone copies blindly. If a guru told… Quietly one of the better feeds in the space.…
@ConversionLabNotes
27 June 2026
Splitting one long checkout into 3 short steps changes conversion by roughly ±0%. The step count is mostly a wash; what moves the number is perceived progress and how many fields survive, not how many pages they sit on. …
@ConversionLabNotes
26 June 2026
Counting conversions per session instead of per user can swing a result by 10%+. Users with multiple sessions get counted multiple times, and heavy users skew toward whichever arm they landed in more. — Pick the randomiz…
@ConversionLabNotes
25 June 2026
Underpowered tests don't just miss real wins — when they hit, they exaggerate by 2-3x. This is the winner's curse (Type M / magnitude error). With low power, only the luckily-large estimates clear significance, so every …
@ConversionLabNotes
24 June 2026
Running two A/B tests on the same page at once can silently corrupt both. If the button-color test and the headline test interact, each contaminates the other's control group. You read two clean wins that don't replicate…
@ConversionLabNotes
23 June 2026
Testing 20 metrics at 95% gives you a ~64% chance of at least one false win. Every extra metric you eyeball is another coin flip against you — the multiple-comparisons problem. — Declare one primary metric before launch.…
@ConversionLabNotes
22 June 2026
One in five "successful" CRO wins quietly damages a metric nobody was watching. Aggressive checkout simplification lifts conversion but raises refund and chargeback rates — the cost lands in a different team's dashboard.…
@ConversionLabNotes
21 June 2026
Average order value tests fail significance checks because the math is wrong, not the metric. AOV and revenue-per-session are ratio metrics — the denominator (sessions) is itself random. A naive t-test understates varian…
@ConversionLabNotes
20 June 2026
CUPED can cut the traffic you need by 30-50% with zero UX change. It's a variance-reduction trick: use each user's pre-experiment behavior as a covariate to strip out predictable noise from the conversion metric. — Works…
@ConversionLabNotes
19 June 2026
~35% of "winning" UI changes lose half their lift within three weeks. That's the novelty effect — returning users react to change, not to the change being better. The curve decays toward the control. — Segment new vs ret…
@ConversionLabNotes
