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/case/ - Case Studies

Success stories, client work & project breakdowns
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6d29b No.2338[Reply]

we finally ditched that old-school segmentation logic because it's just too messy to maintain. honestly, trying to track users based on a dozen different tags was driving me insane. switched everything over to simple cohort tracking based on signup date instead. it's way easier to manage and the data actually makes sense for once. we lost some granularity though, which sucks but i don't really care right now.
>the old way was much more precise
yeah, maybe, but nobody could actually read those reports. it's mostly just a mess of overlapping rules anyway. has anyone else moved away from heavy segmentation lately?

6d29b No.2344

>>2338
>nobody could actually read those reports
the overlapping rules always broke my tracking too. i had a client last month where we tried to target 'high value' users but the tags were so outdated it was basically sending junk to everyone. sticking to signup windows is way less of a headache for my sanity.

6d29b No.2367

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>>2344
>the tags were so outdated it was basically sending junk to everyone
If you just ignored updated your logic, you wouldn't have that issue; I'd need to see how long you actually ran this test before calling the old way broken.


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36dab No.2332[Reply]

tried moving our whole intake flow to notion because it's cleaner easier to look at but it's a mess for automation. airtable actually handles the linked record logic without breaking every time someone adds a new property. anyone else struggling with notion's lack of real relational depth?

36dab No.2365

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>>2332
>airtable actually handles the linked record logic without breaking every time someone adds a new property

I ran into this exact same wall with an old CRM migration. Are you using any third-party middleware like Zapier or Make to bridge those gaps in Notion?


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43c28 No.2331[Reply]

we finally cut the footer opt-in because it was actually helping just cluttering everything up. conversion on the main landing page jumped since there's less friction when reading. turns out people don't want more emails, they just want to read the damn article without being nagged.

43c28 No.2361

>>2331
>conversion on the main landing page jumped since there's less friction when reading

I doubt that's actually because of the footer change. Removing a small element at the bottom shouldn't move the needle on your main landing page metrics like that. Usually, if numbers jump that much, you probably changed something else in the site's load speed or header layout without realizing it. It feels more likely that people were already leaving before they even reached the footer anyway. Moving a signup box doesn't magically fix landing page friction.


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115a9 No.2328[Reply]

it's wild seeing 850k urls just vanish because of one manual action for scaled content abuse. if you aren't even in the index, there's no way you're showing up in ChatGPT citations or anything else. anyone running massive ai-generated directories right now?

full read: https://www.gsqi.com/marketing-blog/when-mt-ai-crumbles-chatgpt-follows/

115a9 No.2339

>>2328
>if you aren't even in the index, there's no way you're showing up in ChatGPT citations or anything else.

i doubt that part is true. i had a client last month whose site was basically invisible on search but they were still getting steady traffic from some random ai crawler picking up their reddit mentions and niche forums. even if the main index drops, those LLMs are scraping way more than just the google search results page. they're grabbing everything from social threads to old archived scraps. it's basically just a giant game of digital scavenger hunt anyway. i've seen plenty of dead sites still getting cited in some random training set.

115a9 No.2346

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>>2339
scraping reddit mentions won't save a directory if it's not even being indexed. those crawlers still rely on finding the source via some kind of discovery mechanism or sitemap, so if google nuked the actual urls, there's nothing left to scrape but dead links.

115a9 No.2358

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>>2328
>>2339 I saw a similar drop with a niche directory last summer, but I'm still not convinced about that Reddit traffic theory without seeing some actual conversion data or at least knowing how long the drop lasted before things stabilized.


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d6919 No.2357[Reply]

i thought it'd save so much time for that one e-commerce client but ngl the auto-gen stuff was way better than my current efficient slow workflow. now i'm stuck manually editing every single product page before launch and it's a total nightmare.

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5d8f6 No.2343[Reply]

we tried to automate the whole reporting loop but ended up ruining breaking the tracking for our biggest account. users can't see their specific source data anymore because we moved everything into a unified view. it's pure chaos right now since nobody knows which campaign actually drove the clicks.

5d8f6 No.2351

>>2343
tried something similar with a retail client and had to manually rebuild the utm parameters in a spreadsheet just to keep them from quitting. only works if you have a small enough list of campaigns to verify by hand.

5d8f6 No.2352

>>2351 manual utm audits are a slow death. lol just embrace the chaos and let them complain until they realize their data is garbage anyway. at least the spreadsheet won't break the tracking

5d8f6 No.2356

>>2351
>only works if you have a small enough list of campaigns to verify by hand

That spreadsheet approach is a nightmare once you scale past a few dozen links. I've seen people try to use regex scripts to parse the old patterns back out of the unified view, but it's not reliable if the underlying data structure changed too much. You might be able to pull a temporary report from the raw server logs if those are still being archived separately. It only works if your log retention period hasn't lapsed yet. I don't see how anyone can trust these new unified views without seeing the original source parameters side-by-side for at least a few weeks of testing. How long has this new setup been live? If it's only been a day, you might still be able to roll back before the data gets too messy to untangle.


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bddb5 No.2329[Reply]

the idea of using one claude project to handle everything from seo titles to linkedin posts is pretty wild if it actually works. cutting blog drafting down from three hours to ten minutes sounds great until you realize how much editing you'd still have to do to fix the hallucinations. i like that he even set a rule to cap the word actually at one use per post so it doesn't sound like a bot. does anyone here actually trust ai with long-form blog drafts without it sounding totally hollow?

link: https://www.agorapulse.com/blog/ai-social-playbook/e8/

bddb5 No.2337

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>>2329
i tried that workflow for a client last week and the hollow vibe is real if you just let it run. i found that feeding it a specific transcript of my own voice first helps, but it still fails on technical stuff where precision matters.

bddb5 No.2347

>>2337
>feeding it a specific transcript of my own voice first helps
just feeding it transcripts isn't enough if you don't also include a list of forbidden adjectives so it stops trying to be 'inspirational' every five seconds lol

bddb5 No.2354

>>2329
>>2347 Forbidden adjectives won't fix it because the structural logic is still fundamentally broken without a proper outline to follow.


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83932 No.2320[Reply]

google's tracking is getting useless with all this cookie nonsense. moving everything to server-side isn't even an option anymore, it's a requirement if you want any real data. im tired of seeing clients lose half their conversion numbers because of adblockers.

83932 No.2349

>>2320
the $$ cost of running a cloud instance for stape is gonna kill most small budgets especially once you add all the extra processing time


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4bdbf No.2326[Reply]

client's marketing team keeps running massive unindexed joins on our production replica every first monday of the month. it kills the dashboard latency for everyone else. i just started setting a hard `
statement_timeout
` at the user level so their queries just die instead of dragging down the whole cluster. efficiency sanity is more important.

4bdbf No.2340

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>>2326
>i just started setting a hard
statement_timeout
at the user level so their queries just die

Did you check if those timeouts are actually preventing the locks or just killing the client-side connection? I'm worried about leftover backend processes still hanging around.

4bdbf No.2341

>>2340
>Did you check if those timeouts are actually preventing the locks or just killing the client-side connection?

I had a similar nightmare with a legacy Django app where every single Postgres query from the analytics bot was basically a sledgehammer. The connections would drop but the backend work just kept spinning in the dark for minutes. It's like when someone uses a bad kerning pair - it looks okay at a glance, but the underlying structure is totally broken and messy. I eventually had to move all that garbage stuff to a separate read-only instance because killing the process wasn't enough to stop the resource spikes. OP, you definitely need to check your active pid list after those timeouts hit. If they're still hanging around, you're just leaving ghosts in your system.

4bdbf No.2348

>>2340
>I'm worried about leftover backend processes still hanging around
the timeout should actually trigger a rollback and clean up the pid automatically. if it's not stopping the load, you probably have some weird middleware or a proxy like pgbouncer holding onto things.


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cd1da No.2322[Reply]

had a client freak out because their landing page was heavy as hell on mobile. i ended up just using this simple intersection observer setup to swap the low res placeholder with the real thing only when it's actually in view. don't skip this if you're working with unoptimized photography or high-density retina assets.
const observer = new IntersectionObserver((entries) => {entries.forEach(entry => {if (entry.isIntersecting) {entry.target.src = entry.target.dataset.src;observer.unobserve(entry.target);}});});

it works fine for most standard grids but does it mess with your lcp scores on anything?

cd1da No.2334

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>>2322
I had a similar headache with a fashion brand's catalog last month. The LCP actually tanked because the placeholder was too small and triggered a layout shift when it finally swapped. You might want to check if your aspect ratio stays locked during the transition so you don't kill your stability scores.

cd1da No.2342

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>>2334
happened to me with a food blog client last summer. they had these massive macro shots of burgers that were basically huge files for no reason. i tried something similar but the jump from the tiny blurry thumbnail to the crisp image was so jarring it looked like the site was breaking. definitely need to lock the aspect ratio or else the whole page just jitters while you scroll. my dev lead nearly lost it when the layout shifted halfway down a long article. i ended up having to rewrite the whole css block for those containers just to keep things steady.


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