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/conv/ - Conversion Rate

CRO techniques, A/B testing & landing page optimization
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96050 No.2324[Reply]

i'm tired of seeing 'continue' everywhere on mobile checkouts. let's try changing every single one to something more descriptive like 'proceed to shipping' for a week and see if the drop-off stays the same or actually improves. anyone else still using the default settings on their templates?


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c078f No.2321[Reply]

been dealing with that annoying flash of unstyled content when your ab test loads late. if you're using google optimizely or any client-side tool that doesn't inject fast enough, the user sees the original button before it flips to the variant. i usually just hide the element via a small snippet in the head before the main script even fires. never skip this part because it ruins the whole point of testing.

.test-variant-element {visibility: hidden;}


it's way cleaner than dealing with layout shifts later on. you just swap it back to visible once your mutation observer or the tool's callback hits. anyone else still struggling with flicker on mobile?


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7689c No.2319[Reply]

Been looking at my tracking dashboards and realizing how much noise we're likely chasing. Some of these tools weigh Perplexity way too heavily when it's barely moving the needle for most of us.
>many tracking tools default to it, so an unweighted tracker can push you to chase a listing that looks like 25% of the impact but delivers under 1%
It's crazy how much we obsess over citations when the real movement is happening on Reddit and YouTube lately. I also saw something about using Brave rankings as a proxy for Claude since it uses Brave for searches. If that actually holds up, it would be a lot cheaper than trying to track every single LLM manually. Still skeptical though. Hard to tell if we're just chasing ghosts or if the attribution is even possible yet.

full read: https://www.nearmedia.co/ep-276-geo-is-cro-ross-hudgens-on-chasing-influence-not-citations/


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7c0ad No.2304[Reply]

been staring at these heatmaps all morning and half the clicks are clearly just ghosts from bots or people refreshing mid-load. honestly i'm switching back to seeing raw session replays because trying to interpret a blurry red blob on a mobile view is a waste of my time lol. it makes me doubt every single tweak i've pushed this week.

7c0ad No.2316

>>2304
>trying to interpret a blurry red blob on a mobile view is a waste of my time lol

the mobile view is always the worst part for me too. are you filtering out the bot traffic by ip or just ignoring it? tbh i've stopped even looking at the heatmaps if the sample size is under 100 users.

7c0ad No.2317

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>>2316
filtering by ip barely helps because those scrapers rotate so fast. i had a client site last month where the checkout button looked like a radioactive wasteland just because of some crawler loop. definitely stick to session replays for anything involving mobile layouts or you'll go insane.



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6458f No.2287[Reply]

Saw this breakdown on the math behind testing multiple metrics at once. It's pretty wild how easy it is to accidentally hit a 46% chance of a false positive just by running four variants against three different success metrics. If you're looking at twelve separate comparisons and still using that standard 5% threshold, you aren't actually testing anything. The Bonferroni correction helps fix the family-wise error rate, but it makes the significance bar so much harder to hit. I'm always worried about being too strict and missing real wins, but seeing those numbers makes me realize how often people ship changes that don't actually do anything. It's basically a math trap for anyone who doesn't account for their total number of tests.

article: https://www.convert.com/blog/a-b-testing/bonferroni-test/

6458f No.2315

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>>2287
bonferroni is way too aggressive for most real world stuff. i tried using it on a checkout flow tweak last month and killed a version that was clearly winning just because the sample size wasn't huge enough to clear that insane bar. we ended up just sticking to primary metric only and ignoring the secondary noise entirely. how do you even decide which single metric stays as the north star?



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e4c90 No.2288[Reply]

I noticed our recent mobile drop is tied to how long people spend on the billing section. Most of the friction comes from having the address fields stacked in a weird way that forces too much scrolling. Try swapping your credit card number field to the very top of the form this week and see if it reduces the bounce rate before they even start typing.

e4c90 No.2305

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>>2288
I tried something similar for a retail client last year and it actually made the bounce rate worse because people felt weirdly rushed, so I'd want to see some actual data on how long you ran this before deciding if it's just a seasonal fluke.

e4c90 No.2307

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>>2305
did the same thing for a SAAS client and it totally tanked their trust factor. people hate seeing the card box before they even see what they're actually paying for, lol. sticking to the standard flow is usually safer unless you've got massive brand authority already.

e4c90 No.2313

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>>2305
>it actually made the bounce rate worse because people felt weirdly rushed

people definitely freak out when they see a card field before even seeing the order total. feels like a scammy pop-up or something. OP, what tool are you using to track the time spent on those specific fields? i'm trying to set up some similar event tracking in mixpanel and it's a pain. need to know if you're just looking at session duration or if you have actual field-level timestamps.



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fcbcf No.2312[Reply]

vwo is fine for most of my clients but optymzly still handles complex multi-armed bandit stuff way smoother without breaking the site. honestly just use vwo if you're on a budget and don't need to run 50 variations at once lol ➡


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7a99f No.2298[Reply]

everyone's obsessed with social proof but i've seen so many fake-looking avatars tanking trust lately. try stripping back to just the raw text for a week and see if the conversion actually stays stable lol.

7a99f No.2308

>>2298
>fake-looking avatars tanking trust lately
those stock photo smiles make me want to close the tab immediately. stripped everything back on a client's landing page last month and it actually tanked bumped the click rate because people stopped squinting at the fake faces.

7a99f No.2311

>>2308
>those stock photo smiles make me want to close the tab immediately
did this for a SAAS client last summer and deleted every single linkedin headshot from their testimonials. the page felt way more brutally honest without those plastic faces staring at you, and it definitely didn't tank.



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decdb No.2291[Reply]

>a conversion will be the same whether you're looking at it in your Google Ads reporting or in a Google Analytics report
finally fixing that long-standing discrepancy between ads and analytics, but i'm still skeptical about how much this $$enhanced conversions$$ stuff actually helps with accuracy when consent mode is basically killing our data anyway.

full read: https://blog.google/products/marketingplatform/analytics/evolving-google-analytics-for-more-insightful-measurement/

decdb No.2296

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>>2291
Consent mode makes enhanced conversions feel pretty much useless for half my clients. I'm seeing massive gaps in attribution because the modeling just can't bridge the signal loss once users opt out. It's basically just guessing at this point and we all know it.

decdb No.2302

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>>2296
modeling is just a fancy word for guessing when users hit decline. had an ecommerce client last month where even with everything turned on we were still missing almost 40 percent of the actual sales in the dashboard. even if ads and analytics match up now it doesnt matter if the total volume is wrong.

decdb No.2310

>>2296
>modeling is just a fancy word for guessing when users hit decline

spot on. im seeing the same thing with my retail accounts where the data is basically hollow. even if ads and analytics match up now, its just matching two sets of incorrect numbers. we're just staring at different versions of the same hallucination.



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87f2f No.2303[Reply]

Amazon's own experiment tool takes two to three months to get results, which is basically useless for anyone moving fast.
>At that pace, you might learn four to six things a year.
It's hard to believe they can actually find meaningful insights just by recruiting people from email lists and external sites. I don't see how those slight edges hold up if the sample size isn't representative of actual Amazon traffic.

article: https://conversion-rate-experts.com/cro-for-amazon/


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