Method
How we turn crash noise into a repair order
Our custom analysis path for application analytics work: define the window, cluster signatures, correlate releases, then brief the people who decide what ships next.
Built for release decisions, not spectacle
Mobile crash feeds reward charts that move. Product and engineering need something quieter: which failures still own sessions after the last patch, and whether the newest train introduced a family that did not exist before.
The method below is what we follow on Crash Trend Assessments and adapt for release checks and retainers. It assumes you already have crash reporting in place; we do not replace that stack.
Five steps we share with every client
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Frame the data window
Agree dates, releases, and campaign or OS events that should be labeled — not silently averaged away. Incomplete symbolication is noted up front.
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Cluster crash signatures
Group traces into families by shared root frames and messages. One-off device quirks stay off the primary ranking until they prove recurrence.
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Measure recurrence and reach
Compare family share of crashes and affected sessions across the window. Volume alone never sets priority.
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Correlate with releases
Map each rising family to build numbers and staged percentages. Separate regressions from traffic-driven spikes.
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Deliver a ranked brief
Hand over a written ranking with effort guidance and a live walkthrough so engineering and product leave with the same order of work.
Questions teams ask before we begin
Do you need admin access to our crash tools?
Read-only access or scheduled exports are enough. We prefer the least privilege that still includes version metadata and stack traces.
Can you analyze both iOS and Android in one assessment?
Yes. Dual-platform work uses separate family rankings with a joint executive summary so priorities stay comparable.
What if our symbolication is incomplete?
We still rank what is trustworthy and mark lower-confidence families explicitly instead of inventing precision.