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Feature · Metric definitions

Metric definitions

Set the grain and calculation method before comparing retail results.

OverviewMetric definitions awaiting approval
Retail Analytics · Metric definitions

Metric definitions awaiting approval

Approval waits for the independent reviewer

New
IdNameGrainVersionAggregation methodStatus
IDD-544Definition 830GRN-245Rev ASumDraft
IDD-840Definition 282GRN-507Rev BCount distinctDraft
IDD-856Definition 361GRN-390Rev CRatio of sumsDraft
IDD-922Definition 200GRN-271Rev DLast as ofDraft
IDD-534Definition 395GRN-493Rev EMedianDraft
6 of 6 records
IDD-544Metric definitions · MD-79601
Sum
NameDefinition 830
GrainGRN-245
VersionRev A
StatusDraft
Example screen with sample data

What you can do

Decide what the number means

A metric definition holds a name, grain, numerator expression, denominator expression, unit, aggregation method, version and status. The Retail Analyst prepares this record so the reviewer can understand the measure before anyone compares values across stores or periods. A conversion number has little value when its denominator changes without a recorded decision. The approved definition gives the result a stable interpretation.

The definition can be related to a store definition and a reviewing person. A result can then reference the metric definition it used. That connection makes it possible to compare results while still finding the rule behind each value. The aggregation method is a recorded choice; the team should agree whether a ratio of sums or another method fits the reporting question.

How the work is organized

  • Grain. The grain explains the unit of observation that a result summarizes.
  • Expression. Numerator, denominator and unit state how the measure is read.
  • Version. Status and version separate a draft rule from an approved one and a retired one.

What to agree during setup

Write down how the business defines a session, shopper, conversion and exposure before setting the expressions. Pick an aggregation method that matches that definition. A ratio of sums can answer a different question from averaging store rates. The reviewer should see a worked example with a normal denominator and a zero denominator before approving the definition.

Agree when a new version is needed. A changed source mapping, eligibility rule or conversion event can change a metric even if its displayed name stays the same. Keep the earlier definition so historic values retain their meaning. Decide who prepares the rule and who can approve it; the reviewer should be independent from the preparer for material changes.

Check the handoff on an actual case

Use a dated store measurement with accepted basket facts. The analyst drafts a basket conversion definition, enters its grain and expressions, selects the aggregation method and gives it a version. The reviewer checks two source windows and records approval. The analyst then links a result to that approved definition and reviews its numerator, denominator, value and source row count.

Repeat the case with no eligible sessions. The result should show a clear exception reason instead of a usable conversion rate. Later, when the store changes the event mapping, retain the earlier version and prepare a new definition for the new period. Reviewers can then explain why values from different windows differ.

What your team sees

  • Metric definitions awaiting approval — Examine draft grain, method and reviewer before use.
  • Result windows — Compare values with their linked definition and period.

Follow the work through

What it keeps track of

Data model
Metric definitions
Approved metric definitions with grain, expressions and aggregation method.
Metric results
Calculated metric results persisted once per approved definition and window.
Retail stores
Configured measurement and experiment definitions with effective dating.
Source mappings
Reviewed field mappings between source and target definitions.
People
Analysts, owners and reviewers belonging to an organization.

Who uses it

Permissions
Retail Analyst
, Independent Reviewer, Data Steward

Set up Retail Analytics your way.

Start free, then use Proto to change fields, steps and approvals before your team goes live.

How to get started