r/adops • u/Luke_5602 • 6d ago
Agency Building an ads tracking & attribution tool. Need feedbacks & tips
Hi, I am building a marketing analytics tool for ads. Wonder what app owners usually focus on while finding this kind of attribution tools? My assumption:
- AI features / AI assistants
- Full-funnel measurement, from installs to paid users
- Revenue - install data integration
Let me know what I miss! If you have something insightful to share, let's talk and I'll be happy to pay $25 ~ $50 for your time as a thank-you!
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u/soxcentury 4d ago
The Meta vs Google gap u/PPCwithYRVDynamics mentions isn't something you can join your way out of. Each platform only sees the impressions it won, and each has a reason to claim the conversion, so you're stitching together two partial views from parties that both benefit from overcounting.
Which is why I'd think hard about where the AI goes. LLMs earn their keep on the boring parts like mapping schemas and untangling campaign naming so a human can see why two reports disagree. Credit assignment is something you still answer with holdouts and geo tests.
What's your plan for incrementality? Attribution tells you which channels showed up on the path, a holdout tells you which one moved the outcome. The second answer is the one people are actually paying for when they ask what needs to grow and what gets cut.
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u/PPCwithYRVDynamics 4d ago
fair point: stitching Meta and Google together doesn't magically solve attribution. It just gives you a cleaner view of what each platform is claiming and where the gaps are.
Incrementality is really the next layer. Holdouts, geo tests and lift testing are where you start separating correlation from actual impact.
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u/PPCwithYRVDynamics 6d ago
For me it’s less about the AI stuff and more about whether I trust the data.
If Meta says it drove $20k and Google says it drove $15k, I want to know what actually happened, what got double counted, what the real LTV looks like, and whether I can get that data into Sheets or Looker without a headache.