How It Works

Trace reads from your data platform, and operationalizes "metric trees" to empower consumers across data, business and executive teams

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Metric
Trees
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Utilize,  
Operate

Modeling the business inputs and outputs via metric trees, Trace streamlines strategic and operational analytics for data consumers

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Business Self-Serves
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Data Team is 10x Productive
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Data
Sources
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Cloud Data Platform
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Metric Trees
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Analytics
Modules
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Business Self-Serves
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Data Team is 10x Productive
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Data
Sources
Cloud Data Platform
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Modeling the business inputs and outputs via metric trees, Trace accelerates the manual, ad-hoc analysis workflows between data and business teams

Step 1

Design
Metric Trees

Start with critical output metrics and decompose them into granular inputs. Or, work your way bottom-up.
OKRs and planning processes are a vital source for this design exercise. Trees are organizational artifacts.
Metric trees can be domain-specific or higher-level, cross-functional in the inputs.
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Step 2

Map
the Metrics

Map the datasets and business logic behind the "nodes" in the metric tree.
Trace uses well-designed configuration files (a light-weight "metrics layer") to power the application.
Trace natively understands the syntax of DBT Metrics, but it is not essential to getting started.
Step 3

Bring Metric Trees To Life

Trace creates and populates the core metric tree artifacts for the organization.
Executives, business leads and data teams can visually align on the ongoing work and the desired outcomes.
Trees are backed by extensive datasets encompassing metrics and rich segmentation.
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Step 4

Utilize and Operate

Tap into a library of built-out algorithms for common metric analysis needs.
Streamline "always-on" analysis and insights for weekly and monthly business reviews.
Shape business strategy and drive consistent operational excellence.
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Frequently Asked Questions

Reach us anytime - we welcome your questions!

What are metric trees?
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Metric trees map the business KPIs to input drivers and granular segments. The closest analogy to today’s “BI" world is to think of them as connecting elements within and across dashboards via underlying business models - that is, metrics and segmentation, or metrics across various dashboards are linked to reflect the business processes and models.

How do I create a metric tree?
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Start with a high-level output KPI and then break it down layer by layer into granular inputs. For example, revenue can be decomposed into “orders”, “items per order”, “units per item” and “price per unit” and further into "new" vs "expansion" terms.

Why is this framework essential now?
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Organizations are making huge investments into data without realizing the ROI on the other end. They find themselves creating dashboard swamps - chopping up metrics into pieces losing sight of the underlying business processes and user needs. This manifests in slow time to insights, long queues or large data servicing teams, weak business self-service and an organization parched for clear operating insights. Teams feel disconnected from their business impact despite sitting on a "lot of data".

What are the benefits of metric trees?
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Metric trees are the missing layer to convert data into business strategy and operational excellence.
1) The C-suite gains clarity and alignment of the org-wide input levers and how they impact outcomes.
2) Analysts save enormous time executing deep dives as software does the heavy calculation lift.
3) Business leads enjoy rapid, granular insights, not a swamp of disconnected swamp of dashboards.

Integrates easily with the modern data  stack

Trace augments existing BI/reporting tools with a powerful browser-based design and implementation of metric trees.

and more

Trusted and Loved By

"Trace quickly and comprehensively analyzes segment-level drivers of our key KPIs. We are running complex pre/post analysis with a few clicks. Excited to leverage Trace for our needs."

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Peter Muller
Head of Insights
@ Capsule

"Trace is taking a novel approach to unlocking the power of data for end consumers. By building on a semantic layer abstraction, Trace is targeting use cases that are entirely manual and tedious today - KPI root causing, experimentation, audience building and OKR planning."

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

"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 segment root-cause analysis, experimentation etc. - a next generation analytics and operations tool."

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