GA-Slack Bot
Slack bot that posts Google Analytics anomaly alerts and scheduled reports.
A Slack bot that watches a website’s Google Analytics for unusual patterns and pushes both anomaly alerts and scheduled summaries directly into a team’s Slack channel. The point is to remove the daily ritual of opening GA at all. If something matters, the bot says so; otherwise the channel stays quiet and nobody has to go looking for a problem that isn’t there.
Anomaly alerts in Slack, not another GA login
Traffic and conversion anomalies get flagged the moment the deviation appears, posted straight into the channel the team already has open. That’s a deliberately different default from most analytics tooling, which assumes someone will log in and check. This one assumes nobody will, most days, and is built so that’s fine.
Scheduled GA reports on your cadence
Beyond anomaly alerts, the bot posts scheduled summaries at whatever cadence a team picks (daily, weekly, or monthly) and it’s configurable per channel, since different teams inside the same company usually care about different metrics. A paid-acquisition channel and a content channel don’t need the same report shape, and shouldn’t have to filter one shared digest to find their numbers.
Why a statistical baseline beats ML here
Most marketing teams don’t have the traffic volume to make a machine-learned anomaly model reliable: thin data makes for noisy, overconfident predictions that cry wolf as often as they catch anything real. A simple statistical baseline, flagging deviation from a rolling average, is honest about what the signal actually supports at typical marketing-team traffic levels. It’s also transparent in a way a trained model isn’t: a marketer can see exactly why something got flagged, which matters for trusting the alert enough to act on it.
Stack
Python runs the core logic. The GA Reporting API pulls the underlying data, and Slack’s incoming webhooks push the alerts and summaries back out. Anomaly detection stays a simple statistical baseline rather than a trained model: the right level of sophistication for the signal density most marketing teams actually have, not the level a vendor demo would show off.
Related projects
- Daily Reporting Automation runs a parallel scheduled reporting workflow over email.
- Autonomous RevOps AI Agent expands automated reporting into executive analysis and rebudgeting scenarios.