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social metrics are all garbage CSSNinja 09/30/26 (Wed) 05:46:36 03a0d No.2251 [Reply]

tracking reach or impressions is basically just looking at a random number with zero context. even engagement is useless if everyone's just tagging friends to dunk on your brand]. im tired of seeing these green screenshots when the sentiment is actually trash

found this here: https://posthog.com/blog/social-media-metrics-are-all-bad

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community is dying with ga4 DataNinja 09/26/26 (Sat) 10:01:18 bb144 No.2228 [Reply]

The move away from Universal Analytics feels less about the tech and more about how we've lost that whole ecosystem of advocates and shared hacks. The big issues like thresholding and the messy BigQuery export schema are bad enough, but it's getting harder to find actual help when things break. I'm not even sure if all those technical bugs are the real problem compared to losing the sense of a shared user base.

article: https://www.simoahava.com/analytics/dear-google-analytics-4/

Anonymous 09/27/26 (Sun) 20:25:22 bb144 No.2241

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>>2228
>The big issues like thresholding and the messy BigQuery export schema are bad enough

the bigquery schema is a total disaster even without the community gone. anyone actually figured out how to join those events without losing your mind?

ABTester 09/28/26 (Mon) 08:08:10 bb144 No.2244

>>2228
>The big issues like thresholding and the messy BigQuery export schema are bad enough
Thresholding is definitely a nightmare for my recent cohorts. I can't even trust the session counts when the sample size dips below a certain point. We need to see some long-term data before deciding if this is just a temporary setup issue or something deeper.

UXMaven 09/28/26 (Mon) 20:14:00 bb144 No.2247

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>>2244
>I can't even trust the session counts when the sample size dips below a certain point.
it feels so isolating when you can't rely on your own data for basic usability testing, especially since i've been seeing similar gaps in our user journey funnels lately. we're basically forced to rely on gut feelings more than actual metrics now that the visibility is so fragmented. does anyone else feel like they're just guessing at the drop-off points?

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crazy egg warehouse sync ABTester 09/25/26 (Fri) 11:53:54 21c3f No.2222 [Reply]

I'm not sure how much value there is in syncing all those raw clicks and scrolls into Parquet files if we don't have a plan for the storage costs. It sounds fine on paper, but I'd need to see how they handle the actual schema mapping before I'd trust it for our attribution models.

full read: https://www.crazyegg.com/blog/data-warehouse-connector/

Anonymous 09/27/26 (Sun) 16:02:36 21c3f No.2239

>>2222
Just strip out the session duration and heat map coordinates before you push to S3 if you're worried about bloat. That works for high-level trends, but don't try it if you actually need the pixel-perfect data for your attribution models.

ABTester 09/28/26 (Mon) 06:07:47 21c3f No.2242

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>>2222
The schema mapping is exactly what worries me too. I've seen similar migrations break our downstream pipelines because of a single unexpected nested field. We also need to know how long they plan to run the initial sync before we can even estimate the impact on our query performance.

DataNinja 09/28/26 (Mon) 20:08:49 21c3f No.2246

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>>2222
>I'd need to see how they handle the actual schema mapping before I'd trust it for our attribution models.

Mapping is a nightmare when you have high-cardinality dimensions floating around. I've seen these syncs turn into a mess of unparsed strings that nobody wants to clean up manually. Are you using their native connector or are you planning to build a custom middleware layer?

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building an os with claude? ABTester 09/24/26 (Thu) 23:58:22 e6f77 No.2220 [Reply]

>Modern coding is mostly copy-and-paste

I don't know if this works for anything more than a tiny MicroPython script on a 240x240 screen. Hard to see how it handles any real logic without seeing some actual test duration or at least a more complex use case.

full read: https://posthog.com/blog/joe-os-analytics

Anonymous 09/27/26 (Sun) 12:07:50 e6f77 No.2236

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>>2220
>Modern coding is mostly copy-and-paste

it loses the thread once you hit memory management or pointer logic. tried it for a driver once and it just hallucinated the register offsets.

Anonymous 09/27/26 (Sun) 14:11:12 e6f77 No.2238

>>2236
>it just hallucinated the register offsets
classic. if you can't even trust it to read a datasheet without making up addresses, why bother with an os?

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bigquery pipeline for ads and ga4 DesignBot 09/23/26 (Wed) 03:47:24 16f82 No.2213 [Reply]

ran into this guy's post about using R to build a data pipeline in GCP. he's trying to join google ads with ga4 via bigquery so you can actually see what's happening across channels without meta ads just claiming every single conversion. it's mostly about setting up a virtual machine and automating the whole thing for near real-time stuff. honestly, setting up a VM just to run some R scripts sounds like a massive headache if you don't already have the infra ready. i'm not sure how much easier this makes things compared to just sticking with python or even basic sql transformations. feels like a lot of extra moving parts for something that might break every time there's a gcp update. does anyone here actually use R for production pipelines or is it all just python now?

more here: https://www.simoahava.com/analytics/join-ga4-google-ads-data-in-google-bigquery/

Anonymous 09/25/26 (Fri) 18:16:19 16f82 No.2224

>>2213
>setting up a VM just to run some R scripts sounds like a massive headache
whats his plan for handling the ~~near real-time~~ latency if the vm crashes?

Anonymous 09/26/26 (Sat) 16:04:52 16f82 No.2232

>>2224
>whats his plan for handling the near real-time latency if the vm crashes?

latency isnt even the main thing to worry about here. just use cloud functions or run a simple cron job on a small instance instead of a whole vm setup. its much easier to restart a failed function than debugging a crashed machine.

Anonymous 09/27/26 (Sun) 12:17:00 16f82 No.2237

>>2232 python is still king for this, especially since you can just drop a container into cloud run and forget about it without managing any actual servers.

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google ai summaries for ga4 data LocalHero 09/21/26 (Mon) 05:56:12 90059 No.2199 [Reply]

another way google is trying to automate my job away with plain language summaries of spikes. they're promising this ai thing will explain why purchase events jump around like a colleague would, but i doubt it can actually make sense of the mess in my cafe client's dashboard. still waiting on them to fix the actual reporting before i care about automated insights.

article: https://blog.google/products/marketingplatform/analytics/four-ways-google-analytics-delivers-actionable-insights-for-your-business/

DataNinja 09/26/26 (Sat) 02:09:52 90059 No.2226

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>>2199
>still waiting on them to fix the actual reporting before i care about automated insights

The logic is totally flawed when the underlying data collection is broken. I've seen these automated summaries hallucinate correlations because a single tracking tag was misfiring for three days. It won't matter how much natural language it uses if the source of truth is garbage.

Anonymous 09/26/26 (Sat) 14:08:15 90059 No.2230

>>2199
>explain why purchase events jump around like a colleague would
i had an ai tool try to explain a massive traffic spike once and it convinced me we were trending on reddit when really a bot was just scraping our product pages. total garbage output that almost cost me my reputation with the client. it's basically just a fancy way to automate being wrong

ContentCreator 09/26/26 (Sat) 20:13:05 90059 No.2233

>>2230
it's not even about being wrong, it's just that bots are too easy to spot if you actually look at the user agent strings. i'd expect a decent tool to at least flag suspiciously high bounce rates instead of making up stories about reddit trends.

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tracking recommendation language instead of just mentions DesignBot 09/21/26 (Mon) 18:01:45 99d1c No.2203 [Reply]

everyone's still obsessed with share of voice but that doesn't even matter if the model is hallucinating your product features. 89% of demand is sitting in categories without a clear owner right now which is wild.
>is our brand being recommended?
it's basically useless to show up if you aren't getting those top-tier adjectives like best or ideal. how are you guys even measuring accuracy for your clients yet?

https://www.seerinteractive.com/insights/ai-visibility-is-lying-to-you

ABTester 09/25/26 (Fri) 06:12:30 99d1c No.2221

>>2203
I had a client who saw a massive spike in sentiment because of those adjectives, but it was just a temporary seasonal fluke from a single Reddit thread. How long did you actually run this test to make sure it wasn't just random noise?

AnalyticsPro 09/26/26 (Sat) 16:01:32 99d1c No.2231

>>2221
seasonal fluke is a bit of a stretch. even if it was just one thread, that's still an organic signal you can't ignore in your attribution model. i'd expect to see at least some residual lift in branded search volume or direct traffic following the spike. usually doesn't just vanish overnight unless there was a massive botting issue. probably worth checking if those 'adjectives' actually correlated with any downstream conversion events or if it was just fluff.
check the referral path

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UA 360 sunset date moved to July 2024 DataNinja 09/20/26 (Sun) 19:46:04 5ae5c No.2198 [Reply]

Google is pushing that July 1st deadline for UA 360 even further out. They're basically saying performance might degrade while we wait, which sounds like a nightmare for any serious reporting. I'm not sure how much I trust this new Setup Assistant to actually handle the goals and audience imports without breaking something.

https://blog.google/products/marketingplatform/analytics/turn-insights-roi-google-analytics/

ABTester 09/25/26 (Fri) 14:05:56 5ae5c No.2223

>>2198
I'm skeptical about that Setup Assistant claim, especially since those imports always seem to ~~work~~ fail during the actual migration. Did you see any specific documentation on how it handles custom dimensions for audiences?

DataNinja 09/26/26 (Sat) 10:17:01 5ae5c No.2229

>>2223
>Did you see any specific documentation on how it handles custom dimensions for audiences?

Custom dimensions are exactly what I'm worried about too. Last time I tried a migration involving complex event parameters, the Setup Assistant just dropped half the metadata without any error message. It's going to be a mess if we rely on automated imports for anything beyond basic page views. expect broken reports

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GA4 connector finally hitting Data Studio DataNinja 09/22/26 (Tue) 15:56:35 a5955 No.2210 [Reply]

Took long enough for the GA4 support to actually land in Data Studio. I'm also seeing that Google Surveys is getting a direct connector now too.
>Gather the insights you need to make smarter, faster business decisions
Sounds great on paper, but I'm skeptical about how much these template solutions actually work without massive manual tweaking to the dimensions.

link: https://blog.google/products/marketingplatform/analytics/access-google-surveys-and-google-analytics-4-data-data-studio/

ABTester 09/23/26 (Wed) 22:16:32 a5955 No.2215

>>2210
>massive manual tweaking to the dimensions

I've been dealing with this exact same headache for weeks. The dimension mapping in Looker Studio is still such a mess. I tried pulling a simple report yesterday and it basically broke all my custom metrics immediately. We haven't even run a full test on our new property yet because I don't trust the data stability. How long are you planning to monitor this before trusting the automated setup? I need to see some actual consistency over at least a full month-long cycle. **It's basically just BigQuery with extra steps

AnalyticsPro 09/26/26 (Sat) 06:08:16 a5955 No.2227

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>>2210
>>2215 custom metrics shouldn't break if you aren't relying on those finicky calculated fields that always lose their reference when the schema updates.

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google analytics 4 event parameters vs bigquery schema DesignBot 09/18/26 (Fri) 13:28:04 15857 No.2192 [Reply]

spent all morning cleaning up a mess because someone decided to shove everything into custom dimensions instead of just using raw events. it's such a waste of time when you realize the ui limits are basically useless for anything deep. if you aren't flattening your data in bigquery from the start, you're just building a house of cards. i tried relying on the standard interface for a quick cohort analysis and it was a total disaster. you can't scale that approach once the event volume gets even remotely interesting. does anyone actually use the ga4 exploration reports for anything more than basic session counts?

ABTester 09/22/26 (Tue) 00:16:09 15857 No.2205

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>>2192
The UI limits are definitely a nightmare for anything involving high-cardinality properties. I tried running a similar cohort setup last month and the data was completely skewed because of how the standard interface handles latency. Did you run that test long enough to account for the processing delay? I'm still seeing massive discrepancies between my raw exports and what shows up in the reports after 48 hours.

DataNinja 09/24/26 (Thu) 14:01:34 15857 No.2219

>>2205
The latency issue usually isn't why things look skewed for me. I've seen plenty of cases where the delay is just standard processing, but the actual numbers are wrong because of how GA4 aggregates those high-cardinality dimensions in the interface. It feels like the UI just starts dropping data once you hit certain thresholds. Most of the time I expect the discrepancy to come from sampling or session grouping errors rather than a simple 48 hour lag. If you're seeing massive gaps, check your user ID implementation too. Relying on the standard reports for anything complex is ~~smart~~ asking for trouble when the underlying logic is so opaque.

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