Framework
The four rungs of customer data
From retail scans to interviews: what each level of data can and cannot tell you
A four-level ladder for thinking about customer data. Transaction data (retail measurement) covers almost the whole market but contains no people. Household panels add a persistent identity behind each purchase. Person-level surveys capture attitudes. Reason-level interviews explain the decision itself. Insights teams can use it to see which question each data source can answer, and where an interview study fills the gap that syndicated data leaves.
Where this appears
What's in this framework
- 1. Transaction: Item by store by week. Huge coverage, no people in it.
- 2. Household: Basket, trip and household. A persistent identity behind each purchase.
- 3. Person: Respondent and occasion. Attitudes, awareness and stated consideration.
- 4. Reason: Decision and cause. Interviews explain why this, why now, why not the other.
Use this image
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<a href="https://www.koji.so/visuals/customer-data-measurement-ladder-four-rungs"><img src="https://www.koji.so/visuals/customer-data-measurement-ladder-four-rungs/customer-data-measurement-ladder-four-rungs.png" alt="Framework showing the four rungs of customer data: transaction, household, person and reason, from broad retail measurement down to interviews." width="1200" height="699" /></a>
<p>Source: <a href="https://www.koji.so/visuals/customer-data-measurement-ladder-four-rungs">The four rungs of customer data</a>, Koji</p>
