>I use BuySellAds/Carbon Ads on my blog and wanted more visibility than just revenue numbers. So I started tracking ad impressions and clicks in GA4 and built a Looker Studio dashboard to analyze performance by page, placement, and creative.
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>Read here.
Recently, I experimented with a different way of explaining my web tracking service.
Let me be honest: I am a developer, and reaching out to customers is not something I am good at or feel comfortable with. On top of that, business owners were not able to connect with the service I offer, and they were asking questions that were not easy to answer in a few messages.
What I did was write a blog post in which I documented the journey of implementation, but it was quite long and more suited to educating someone already interested in the topic.
So I turned it into an AI-generated video podcast: an AI version of me as the guest, with a fictional host asking questions business owners asked me during the calls, plus others they might ask.
The answers came from my own content and implementation experience.
At an agency I previously worked with, clients would request podcast scripts and arrange studio recordings, which involved considerable time and expense. That experience made me curious about whether this format could be useful for smaller businesses, especially when AI tools are getting insanely good at doing such things.
I haven’t measured whether it generates inquiries yet. Producing something convincing and getting someone to trust it enough to contact you are different things.
Curious whether anyone has tested this and seen actual inquiries or sales.
I'm building a Looker Studio dashboard using GA4 data and want a table showing Ad Creative Image | Impressions | Clicks. The creative image URL is stored in a GA4 custom dimension (ad_image_url), and the impressions/clicks are combined using a blended data source.
The issue: IMAGE(Ad Image URL) works and displays correctly when I use the original GA4 data source, but the image stays blank when the table uses the blended data source. Even IMAGE("hard-coded-image-url") doesn't render in the blended table, although the same hard-coded image works in a normal GA4 table.
Has anyone encountered this limitation with IMAGE() + blended data in Looker Studio? Is there a workaround that still lets me show creative image + impression count + click count in the same table?
I'm building a Looker Studio dashboard using GA4 data and want a table showing Ad Creative Image | Impressions | Clicks. The creative image URL is stored in a GA4 custom dimension (ad_image_url), and the impressions/clicks are combined using a blended data source.
The issue: IMAGE(Ad Image URL) works and displays correctly when I use the original GA4 data source, but the image stays blank when the table uses the blended data source. Even IMAGE("hard-coded-image-url") doesn't render in the blended table, although the same hard-coded image works in a normal GA4 table.
Has anyone encountered this limitation with IMAGE() + blended data in Looker Studio? Is there a workaround that still lets me show creative image + impression count + click count in the same table?
If you're spending money on Meta Ads, it's worth making sure Meta is actually receiving accurate conversion data.
Recently, I audited the tracking setup of an e-commerce store running Meta Ads.
Meta's Data Quality Score was just 2.8/10 — Poor compared to similar advertisers.
I improved the tracking setup and implemented server-side tracking alongside the existing browser tracking.
After the changes: 2.8/10 → 8.0/10
I can help with:
Rate: $25/hour. For complete tracking implementations, I can also quote a fixed project price once I understand your current setup.
If you're running an e-commerce store and Meta Ads, DM me your store URL + a screenshot from Meta Events Manager.
I'll take a quick look and tell you if I spot anything that could be improved.
No strings attached.
Last I used it on Sept 2 around 11 PM local time, I still see this. I am on a free plan
A couple of weeks back, someone approached me to implement tracking on his OpenCart-based ecommerce store to send proper event data back to GA4 and Meta for better tracking and, ultimately, better ROAS.
I had never worked with OpenCart before. Most of my ecommerce tracking work has been with Shopify or WooCommerce.
I thought it would be an easy task: find a free plugin, install it, configure GTM, and move on.
To my surprise, there are very few OpenCart extensions (the OpenCart version of plugins) for this. Secondly, pretty much everything I found was paid. The minimum was around $30, with some going close to $100.
Initially, I thought of simply buying one. But there were no trial versions, and I wasn't even sure whether they'd give me the flexibility I wanted.
Then the developer in me whispered:
"Hey, why don't you make one?"
Hmm... not a bad idea.
Especially because I wanted control over exactly how the tracking data was generated.
So I started exploring the OpenCart documentation and, with the help of docs + AI, started building my own extension.
Instead of relying on DOM scraping or modifying the theme, the extension hooks into OpenCart's built-in event architecture and generates the tracking data itself.
So far, I've implemented:
→ GTM injection directly through the extension
→ Persistent visitor ID
→ GA4 tracking
→ Meta Pixel tracking
→ Ecommerce `view_item` / `ViewContent` event
→ Visitor ID being passed to Meta as `external_id`
I'm now working through the remaining ecommerce events one by one: Add to Cart, Checkout, Purchase, and eventually the server-side implementation with Meta CAPI.
Sharing a few screenshots of the work in progress.
Still building. Let's see where this goes.
P.S. I'm also thinking of releasing a free, limited version of this extension on the OpenCart Marketplace.
Say I run a campaign, and someone visits the product page that was being advertised. He found the WhatApp icon and clicked on it.
Now, if he sends a message, how can I figure out he came via a campaign?
What happened at EFERT? Why is it in decline?
Lately I have been getting queries like this. I do feel they are LLMs, but why are they excluding Social media platforms?
"<keyWord>" -site:reddit.com -site:twitter.com -site:x.com -site:wykop.pl -site:tripadvisor.com -site:youtube.com -site:yelp.com -site:booking.com -site:facebook.com -site:instagram.com -site:tiktok.com
A friend called me because his Shopify store wasn't getting enough sales.
His first instinct was to spend more on ads.
Mine wasn't.
A year ago, I probably would have agreed with him.
Let's test new creatives. Or let's change the audience. Or maybe increase the budget.
Instead, I asked for access to his Shopify store, Meta Business Manager, and Google Tag Manager(GTM).
I wasn't looking for a problem with the ads.
I was looking for a problem with the data.
Meta's Event Match Quality was only 3/10. The store was relying on the default integrations; there was no GTM implementation, and the data being sent back to Meta was far from complete.
So I rebuilt the tracking from the ground up:
• Moved tracking into Google Tag Manager.
• Implemented the key ecommerce events.
• Added a persistent visitor ID to understand the customer journey.
• Implemented Meta Conversion API with server-side tracking to improve event reliability and matching.
The result wasn't just cleaner tracking.
Meta showed a much healthier Event Match Quality, meaning it was receiving richer data to optimize campaigns.
So many testers joined but they are complaining about unable to install app due to the error "App not available". How to fix?
Hi friends!
I'm looking for respected testers like you to help test my new app and meet the Google Play closed testing requirement. This is the first time I have built an Android app, and only with your support can it go into production
App: MassIndex: BMI Calculator
It features:
If you're also looking for testers, reply with your app links, and I'll gladly test yours in return.
PS: Please use it once a day daily for smooth approval.
Thanks and Happy Testing! 😊
Recently, I set up tracking on both the client and server sides for my friend's Shopify website, using tools such as GTM, GA4, Meta Pixel, and Meta CAPI.
The biggest surprise for me is not the implementation, but rather the sheer volume of testing required to achieve clean events with high Event Match Quality.
I documented the entire implementation while I was working through it. If anyone is interested, I'm happy to share it with you.
How did you implement tracking to increase ROAS? Or did you not implement it at all?
A friend asked me to audit his Shopify store before increasing his ad budget. What looked like a working setup turned out to have several tracking issues that could affect attribution and ad optimization.
I've shared the complete walkthrough here. If you'd like to read it, click here
How did you implement tracking to get more ROAS?
A friend asked me to look at his Shopify store because his Meta ads weren't producing the results he expected.
I assumed I'd find a simple tracking issue, but after digging in, I found several things that surprised me:
It made me wonder how many stores are making advertising decisions based on incomplete tracking data.
For those managing Shopify stores:
Are you using Shopify's built-in integrations?
Looking forward!
A friend asked me to look at his Shopify store because his Meta ads weren't producing the results he expected.
I assumed I'd find a simple tracking issue, but after digging in, I found several things that surprised me:
It made me wonder how many stores are making advertising decisions based on incomplete tracking data.
For those managing Shopify stores:
Are you using Shopify's built-in integrations?
Have you ever audited your tracking and found something unexpected?
Will you guys suggest an Ollama-based image model to generate realistic images? Something like what Ideogram offers.
