Glossary/Audience data/Data enrichment
What is data enrichment and how does it improve audiences?
What data enrichment is, the kinds of data publishers add to their own, and how enrichment turns reader data into audiences advertisers ask for.
Written by Samhub with the help of AI·Updated 13 Oct 2026·3 min readData enrichment is adding detail to the data you already have, for example age, household, income or interests, by combining it with other data sources or models.
Common types of enrichment
| Type | Adds | Example |
|---|---|---|
| Context | What the page is about | Articles about electric cars |
| Interest | Long-term interests from reading | Personal finance |
| Population data | Statistics for an area | Average income in a postcode |
| Modeled data | Likely traits from patterns | Likely family with children |
Why it matters for publishers
Advertisers ask for audiences in their own terms: age, life stage, income, purchase intent. Raw page views do not answer that. Enrichment turns reader data into the audiences buyers already plan with.
16 pages for publishers, with a checklist for data, programmatic and direct sales.
Enrich with care
Use lawful sources
Check how each data source was collected and what it may be used for.
Prefer aggregated data
Area statistics and models avoid moving personal data around.
Keep it in one place
Enrich in the same platform that holds your data, to avoid copies in many tools.
Addressability at Stampen Media after moving its reader data into one layer with Samhub.
Frequently asked questions
Not necessarily. Enrichment can use public statistics, context and models, not only bought data.
When it adds to personal profiles used for advertising, yes, under GDPR.
Modeled and area data are estimates. Test segments in campaigns and keep the ones that perform.
Enrichment adds detail. Segmentation groups readers by that detail.
Related terms
Collects and segments audience data for advertising.
Data you collect directly from your own readers.
Targeting ads based on what readers have done before.
Targeting ads based on the content of the page.
Targeting by age, gender, income or household.
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