"How many leads did webmaster X deliver yesterday?" — a simple question, 5 minutes in the tracker. "Compare nutra conversions over two weeks broken down by geo and show me which partners' approval rates dropped" — and now the manager is filing a ticket for the analyst, with an answer coming in one to three days.
Let's be honest about what can be automated with the standard tools in Keitaro and Affise — and where their capabilities end.
What the trackers themselves can do
Built-in reporting in modern trackers is strong, and it shouldn't be underestimated:
- Keitaro offers custom reports with dozens of metrics and filters, exports to CSV, HTML and JSON, plus an Admin API that can programmatically fetch any report. With a script and a scheduler, a report can be generated on a schedule and pushed, say, into a CRM.
- Affise provides dashboards, statistics by offer, partner and geo, exports, and an API for integrations.
If your questions are standard and repetitive — "daily conversion summary", "weekly top-offer report" — that's enough. Set it up once and it works.
Where built-in reports end
Problems start in three cases:
Non-standard questions
Every new question means new filters, a new report configuration or a new API script. Someone has to do it: either the manager knows how (rare), or it's a ticket to the analyst and a wait.
Data from multiple sources
The tracker knows about clicks and conversions. But "why did partner X drop?" often also requires the chat history (what they were promised), the rate registry (what changed) and the wiki. No tracker will join those into one answer.
You need a developer
The Admin API is a powerful tool, but the scripts for it are written by a developer. For a team without its own tech resource, "automation via API" remains theoretical.
In our experience, a typical CPA team uses 10–20% of its tracker's reporting capabilities — precisely because every non-standard report takes separate effort.
The AI approach: queries in natural language
An AI assistant changes the interface to your data: instead of filters and configurations — a plain sentence. "Build a dashboard of conversions for the last 30 days, broken down by vertical" — and in a minute you get an interactive report that refreshes every time it's opened.
The key difference: the assistant sees more than the tracker. It can combine tracker data with the rate registry and the partner conversation in a single answer — not just "conversions dropped" but "conversions dropped after the rate change on the 15th; here's the agreement from the chat".
The honest conclusion
If all you need is standard recurring reports, your tracker's built-ins are enough — and free. An AI assistant pays off when the team regularly asks non-standard questions, data is scattered across several systems, and you don't have your own analyst or developer — or their time costs more than the automation.
Want to see how this works in your business?
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