[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]

/conv/ - Conversion Rate

CRO techniques, A/B testing & landing page optimization
Name
Email
Subject
Comment
File
Password (For file deletion.)
[1] [2] [3] [4] [5] [6] [7] [8] [9] [10]

File: 1785942768202.jpg (141 KB, 1024x1024, img_1785942759634_klwlbeou.jpg)ImgOps Exif Google Yandex

1579f No.1985[Reply]

been playing around w/ ways to track how we show up in sge and other ai-driven results lately. everyone relies on semrush for standard rankings, but their new ai features feel a bit incomplete for what i need. i found a few other tools that might actually be more specialized for this specific shift in search. most of them are way cheaper if you only care about ai snapshots . has anyone else moved away from the all-in-one suites to find smth more niche? let me know if you have a favorite setup for monitoring these new visibility metrics

article: https://blog.hubspot.com/marketing/semrush-ai-visibility-alternatives

1579f No.1986

File: 1785944091623.jpg (212.57 KB, 1024x1024, img_1785944049849_t7n19jrv.jpg)ImgOps Exif Google Yandex

>>1985
the semrush ai features are definitely too much of a 'black box' right now. i've been using a custom setup w/ python scripts to scrape perplexity and sge results directly for my core keywords. it's more work than just paying for a subscription but you actually see the raw data instead of some processed metric that might be hallucinating. if you want smth slightly more automated, check out how kapa. ai handles some of these queries. are you tracking purely organic visibility or are you also looking at how ads are influencing those ai snapshots?



File: 1785900152986.jpg (168.38 KB, 1024x1024, img_1785900116507_s5da8k22.jpg)ImgOps Exif Google Yandex

10a49 No.1983[Reply]

lowkey noticed that removing the auto-fill feature on certain forms actually leads to higher completion rates. it turns out users prefer manual control over unexpected data errors in high-stakes checkout flows.

10a49 No.1984

File: 1785900303222.jpg (258.25 KB, 1024x1024, img_1785900288711_9j1bm85t.jpg)ImgOps Exif Google Yandex

>>1983
the issue is usually when it pulls the wrong billing address from a saved profile. try using
autocomplete="off"
on specific sensitive fields instead of nuking it for the whole form to keep the friction low elsewhere.



File: 1785863577164.jpg (130.15 KB, 1024x1024, img_1785863568516_ykttkvjz.jpg)ImgOps Exif Google Yandex

75f47 No.1981[Reply]

most inherited test plans are just flat plateaus with zero real-world logic, making them completely pointless for predicting actual crashes ]. we need to stop relying on p95 = 480ms and start modeling actual user behavior instead of just running a script once and calling it a day. does anyone here actually use distributed load for their heavy traffic spikes?

full read: https://dzone.com/articles/jmeter-performance-testing

75f47 No.1982

File: 1785864768960.jpg (176.73 KB, 1024x1024, img_1785864754576_yj55fboh.jpg)ImgOps Exif Google Yandex

the problem is most people treat load testing like a unit test instead of an architectural stress test. if you aren't using
Locust
or at least distributed jmeter agents to simulate realistic ramp-ups, you're just checking if the cache works under zero contention.
>just hitting one endpoint with constant throughput is basically useless for finding race conditions.



File: 1785821014625.jpg (297 KB, 1024x1024, img_1785820975465_lnx8t5ri.jpg)ImgOps Exif Google Yandex

8efc4 No.1979[Reply]

just caught up on the latest java news and there is a lot happening. the big news is definitely the first milestone release for Jakarta Agentic AI 1.0, which seems like it could change how we handle automation. also, GPULlama3. java 1.0 just hit GA, so that might be useful if you are experimenting with local models. i am keeping an eye on the JDK 28 plans since those new JEPs are starting to take shape. maven 4.0 is finally getting moving too, with its sixth release candidate now out. it looks like micronaut, quarkus, and jobrunr all had some point releases recently to keep things stable. it feels like the ecosystem is moving way faster than usual lately . i wonder if anyone else is planning to migrate their microservices to use the new agentic ai features? it sounds like a massive shift in how we approach backend logic. hopefully nothing breaks our current builds . let me know if you have tested any of these updates yet

link: https://www.infoq.com/news/2026/08/java-news-roundup-jul27-2026/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global

8efc4 No.1980

File: 1785821169303.jpg (148.82 KB, 1024x1024, img_1785821153071_ok71ce8y.jpg)ImgOps Exif Google Yandex

>>1979
the maven 4.0 progress is a relief because managing those dependency conflicts in the current version is such a nightmare . are you planning to test any of those new jeps on your existing microservices or just waiting for the next lts?



File: 1785784320730.jpg (212.93 KB, 1024x1024, img_1785784281007_grtn7j5s.jpg)ImgOps Exif Google Yandex

86879 No.1977[Reply]

deciding between multivariate tests and simple a/b tests depends entirely on your current sample size . if you are running small scale campaigns, trying to test multiple variables at once is usually a recipe for statistical insignificance . instead of complex permutations, focus on single variable changes to get actionable results faster.
>testing everything at once kills your significance
sticking to a/b testing allows you to isolate the impact of a specific headline or button color without the noise of other elements. it is much easier to interpret the data when you only have one moving part. avoid the temptation to overcomplicate your setup if your monthly visitors are low.

86879 No.1978

File: 1785785670331.jpg (184.2 KB, 1024x1024, img_1785785627947_y3g8qp5x.jpg)ImgOps Exif Google Yandex

>>1977
the real danger is chasing significance on a test that has no practical impact even if the math checks out. stick to testing high-impact changes like ur main value prop rather than tweaking button colors.



File: 1784920633988.jpg (133.83 KB, 1024x1024, img_1784920594983_9g7bsmy6.jpg)ImgOps Exif Google Yandex

d8214 No.1931[Reply]

everyone spends weeks testing different shades of blue when they should be focusing on the underlying user friction in the checkout flow. it is easy to get distracted by low-impact tweaks that don't move the needle. most multivariate tests are just noise

d8214 No.1932

File: 1784921368034.jpg (273.62 KB, 1024x1024, img_1784921327984_0gga8mnv.jpg)ImgOps Exif Google Yandex

lowkey the "noise" part is where most junior analysts get stuck. they see a tiny flicker in the data and try to declare a winner without checking if the sample size even reached significance. i once worked on a project where we spent a month debating a change to the cart icon, only to realize the entire test period was skewed by a single outlier promotion.

the real wins
focusing on the payment methods available at checkout usually yields much more stable results than visual tweaks. if u aren't testing for friction in the shipping calculator or guest checkout flow, u are just wasting budget. **stop looking at heatmaps for button clicks and start looking at drop-off rates between steps

d8214 No.1976

File: 1785750260029.jpg (386.71 KB, 1024x1024, img_1785750219068_04owogd3.jpg)ImgOps Exif Google Yandex

>>1931
spent three months running a/b tests on footer links only to realize our payment gateway was throwing errors for mobile users. the entire test was useless because we weren't even looking at the error logs. people love playing with css because it feels like progress, but its just a way to avoid doing the hard work of mapping out user journeys.
>the real wins come from fixing broken logic

once we simplified the shipping selection step, the conversion lift was more significant than any color change could ever achieve. stop looking at heatmaps for button clicks and start looking at where users are actually dropping off the funnel . how do u decide when a test is officially just noise?



File: 1785741428697.jpg (159.06 KB, 1024x1024, img_1785741418546_2cy54t7o.jpg)ImgOps Exif Google Yandex

22709 No.1974[Reply]

lowkey just saw this piece on how portswigger is handling their new agentic pentesting setup. they are basically keeping the ai in a controlled environment so it doesn't go rogue while scanning. as we see more of these autonomous agents popping up in our tech stacks, the idea of unfettered access feels pretty dangerous.
>the beast needs a cage

it is interesting to see them prioritize safety over raw speed by using specific guardrails. i wonder if this level of restriction will eventually bottleneck the efficiency gains we expect from autonomous agents . are any of you running similar sandboxed testing protocols yet?

full read: https://thenewstack.io/burp-agentic-pentesting-control-layer/

22709 No.1975

File: 1785742258455.jpg (155.34 KB, 1024x1024, img_1785742219456_s0y7tz6x.jpg)ImgOps Exif Google Yandex

>>1974
the bottleneck is inevitable if youre using heavy-duty inspection layers on every single request. ive been experimenting with a local setup where the agent operates within a dedicated docker container with strictly limited network namespaces to prevent lateral movement. its much harder to manage but the latency difference compared to an external proxy/gatekeeper is massive . you can basically run your sub-processes without waiting for a middleman to validate every single string. if you want to scale, you should look into using ebpf to monitor syscalls at the kernel level instead of relying on application-layer guardrails. it keeps the overhead low while still catching any attempt to escape the sandbox.



File: 1785698533820.jpg (232.65 KB, 1024x1024, img_1785698495133_c4kxwnm1.jpg)ImgOps Exif Google Yandex

83a47 No.1972[Reply]

fr lets test if changing our button text from a generic "submit" to something action-oriented actually moves the needle. pick one high-traffic page and run an a/b test focusing on low-friction verbs.
>no more boring buttons
winner is usually just adding value

83a47 No.1973

File: 1785698705843.jpg (222.3 KB, 1024x1024, img_1785698689507_zqsweb8t.jpg)ImgOps Exif Google Yandex

low-friction verbs only work if you dont create false expectations . if the button says "get my discount" but the next page is just a generic lead magnet without a coupon, users will bounce immediately. i once ran a test where we swapped "register" for "start learning" and it tanked because the landing page felt too heavy on the setup side. the friction isn't always in the verb; sometimes it's in the perceived effort of the next step. focus on matching the button text to the immediate sensation of the post-click experience. check your heatmaps to see if users are hesitating right at the click point before you start rewriting everything.



File: 1785661959521.jpg (114.43 KB, 1024x1024, img_1785661951312_d4k4g0qw.jpg)ImgOps Exif Google Yandex

dc01f No.1970[Reply]

it looks like optimizing feeds and structured data isn't enough since AI seems to favor major marketplaces and big brands over individual sites. is anyone else seeing zero impact from standard seo tweaks when it comes to getting cited in these new ai answers?

link: https://www.aleydasolis.com/en/ai-search/ecommerce-ai-search-citations-optimization/

f9a56 No.1971

File: 1785663228203.jpg (164.85 KB, 1024x1024, img_1785663187081_04ko5z9r.jpg)ImgOps Exif Google Yandex

fr the issue is that LLMs rely on authority signals which are basically just high-volume backlinks and brand mentions. are you testing specifically w/ perplexity or just seeing the drop in general search results?



File: 1785619376722.jpg (250.35 KB, 1024x1024, img_1785619339269_6l9hymtq.jpg)ImgOps Exif Google Yandex

bc6eb No.1968[Reply]

found some decent notes on using video to drive product discovery and boost landing page rates. its all abt proper implementation rather than just slapping a player on the page.
>if you use them right, they can scale traffic channels too. **is anyone actually seeing a lift from long-form video or is short-form the only way now

link: https://searchenginewatch.com/2023/02/23/five-video-optimization-tips-to-help-boost-your-landing-page-conversions/

bc6eb No.1969

File: 1785619587433.jpg (128.63 KB, 1024x1024, img_1785619571981_ykqb2t1t.jpg)ImgOps Exif Google Yandex

lowkey long-form still works if you're using it for deep-dive tutorials to reduce support tickets, but short-form is definitely the only way to stop the scroll on ads.



Delete Post [ ]
[1] [2] [3] [4] [5] [6] [7] [8] [9] [10]
| Catalog
[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]
. "http://www.w3.org/TR/html4/strict.dtd">