Root Cause Analysis: GitHub + Shopify
Why did this metric change?
The problem
Conversions dropped 23%. Everyone has a theory. Was it the ad creative? The landing page? A pricing change? Without cross-platform data, you're just guessing.
GitHub tracks commits and pull requests, deployment events, release tags. Shopify tracks orders and revenue, product performance, customer profiles and segments. Neither sees the other. That blind spot costs you money every day.
How askotter fixes this
askotter pulls GitHub and Shopify into one data lake. With both data sets unified, it can test hypotheses against data from every tool and isolate the real cause. Self-healing agents adapt as your data shifts, so the analysis stays accurate without manual tuning.
A ranked list of causes with confidence scores. Not theories. Evidence.
What feeds root cause analysis
What happens when they're connected
Separately, each tool answers its own questions. Together in one lake, askotter can answer the questions that matter: the ones that span both. Train these agents like your best employee and they become tireless assistants that scale your team's knowledge to everyone.
Correlates deployment timing with changes in customer behavior
Connects revenue anomalies to specific deployments
Traces every Shopify sale back through the full customer journey
Before and after
| Capability | Without askotter | With askotter |
|---|---|---|
| Root Cause Analysis | Manual, delayed | Automatic, real-time |
| Cross-platform data | Copy-paste between tabs | One data lake |
| Change detection | Weekly report | Minutes |
| Next steps | Figure it out yourself | Ranked actions, human-approved |
| Querying | SQL or export to CSV | Ask in plain English |
| Team knowledge | Tribal knowledge, lost in Slack | Saved notes, shared across teams |
Root Cause Analysis in action
Ask your data lake anything. Save what matters.
Other analyses: GitHub + Shopify
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