Fast, powerful
self-service analytics and operations

Trace automates common calculations and metric transformations giving your data and business teams superpowers to operate the business

What Users Are Saying

"Trace is taking a novel approach to building high value metric transformations on top of business semantic concepts. We are excited to partner and leverage Trace for several applications at Convoy like composable reporting, self-service analytics and root causing."

Chad Sanderson
Head of Data, Product Manager, Data UX Champion
@ Convoy

"Trace is thoughtfully engineered to bring much needed organization and transformation functionality to our metrics. We are excited to onboard several use cases on this platform."

Daniel Dicker
Software Engineer
@ Convoy

"We use Trace to root cause segment-level drivers of key metrics before monthly exec meetings. We are also simulating metric scenarios for the growth team. Excited to leverage the growing list of "templates" for our various use cases."

Peter Muller
Head of Insights
@ Capsule

"At Airbnb, we got tremendous utility from our in-house metrics tool, Minerva. Trace's unique approach extends beyond the goals of Minerva, serving automated templates for  root-cause analysis, experimentation etc. - a next generation analytics and operations tool."

Aaron Siegel
prev. Head of Data Platform
(AirBnB and Twitter)

Product Overview

Leveraging the power of business semantics, Trace powers self-service analytics and operations - dynamic reporting, root cause analysis, experiments, simulating metric scenarios, and more.

Dynamic Reporting
Segment Root Cause Analysis
A/B and Quasi Experiment Metrics
Metric 'What-if" Scenarios
Segment Generation/Experimentation


Easily and progressively map your datasets + sql snippets to the business semantic layer

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Get desired outputs for your quarterly planning to daily analysis and operational use cases

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Easily and progressively map your datasets + sql snippets to the semantic layer; validate, review, publish.

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Generate outputs optimally shaped for reporting, experimentation metrics, root cause analysis and more.

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Executive or Operational Reporting
A/B and Quasi Experiment Metrics
Segmentation/Off Line Experiments
Weekly Business Reviews
Segment Impact/Root Cause Analysis

Increase ROI, not more datasets and reports

Trace supercharges your data and business teams to measure and propel performance


Map once, Use many

Map a metric or segment once; compose and reuse for various use cases. Save time for perpetually constrained data teams.


Data for all, All for data

Empower data savvy users in the org to run repetitive metric analysis on their own.


More connections. More insights.

Understand your connections - isolated metrics in reports don't get to the full story


Drive ROI from your own data

Demand more from your data. Run the OKR process with a strong analytical backbone.


Less clutter. More time.

Define business concepts once, reuse many.  Save precious time -  especially for  perpetually constrained data teams.


Data for all, All for data

Empower data-thirsty users in the organization to self-serve through business concepts, not code.


Fewer silos. More connections.

Break the silos of isolated metrics. Answer connected questions otherwise seemed out of reach.


Drive ROI from your own data

Run your business with confidence in the insights. Run more experiments. More shots on goal.

For data scientists or data analysts

  • Stop drowning in ad-hoc metric analysis requests like "can you look into why this went down?"  
  • Save precious cycles while executing ad-hoc analysis. Let Trace do the heavy lift for common metric transformations.
  • Reclaim your time, elevate your role  - partner with the business to set and impact OKRs.

For data-driven operators

  • Minimize the coordination games of “could you pull this or look into this?" Answer questions in minutes, not days.
  • Become one with your data: root cause metric changes, isolate impact of initiatives, run what-if scenarios etc.
  • Analytically enrich the OKR process - from setting goals to root causing impact of initiatives.

For data and analytics engineers

  • Focus on upstream data source ingestion and generating  high quality base datasets that the organization needs.
  • Spend less time optimizing SQL queries, and organizing the swamp of code and datasets
  • Elevate your role, drive the “data-as-a-product” culture - quality AND velocity.
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