What is data enrichment?

Appending attributes from a third-party source — firmographics, technographics, contact details — to records in your CRM.

How accurate is enrichment data?

Variable, and it decays. Employee counts, job titles and technology stacks all change continuously, so a field enriched a year ago describes a company that may no longer exist in that form.

What is match rate and why does it matter?

The share of your records the provider can identify at all. A 90% accurate provider with a 40% match rate enriches 36% of your records, and that is the number that matters for anything keyed on those fields.

When does enrichment fail to help?

When it lands after the decision that needed it. If routing fires before enrichment returns, the rules read empty fields and the data is irrelevant however good it is.

Enrichment

Appending third-party data to records so routing, scoring and segmentation have fields to operate on.

The two numbers that decide the value

Match rate — how many of your records the provider can identify — and freshness — how recently the attributes were true. Vendors lead with accuracy, which is the least binding of the three.

Timing beats accuracy

If enrichment is asynchronous and routing fires on record creation, the rules evaluate empty fields. The enrichment arrives seconds later and changes nothing. Measure the null rate at the moment the rule runs, not after the queue drains — this single check explains a large share of routing complaints.

Evaluating a provider on your own data

Take a sample of your real records, not the vendor's test file, and measure match rate.
Spot-check accuracy against a source you trust for fields that actually drive decisions.
Measure latency end to end, from record creation to field populated, and compare it against when your rules fire.
Only then compare price, and price per matched record rather than per record submitted.

Using it sensibly

Enrich the fields that feed a decision. Enriching everything creates a maintenance surface with no consumer.
Re-enrich on a schedule for volatile fields; treat them as perishable rather than permanent.
Record provenance and date on enriched fields, so a stale value is identifiable as stale.
Never let enrichment overwrite a value a human or the customer supplied.

How to run enrichment without degrading the database

Decide which fields the provider may overwrite and which are sacrosanct. Enrichment overwriting a field a human verified is the fastest way to lose trust in the whole dataset.
Record provenance per field: which source wrote it and when. Without that, a wrong value is unattributable and unfixable at source.
Measure match rate and accuracy separately. A provider matching 90% of records at 70% accuracy is worse than one matching 60% at 95%.
Sample-test before committing. Take 100 records you can verify independently and check the provider against them rather than against another provider.
Re-enrich on a schedule matched to how fast the field decays. Headcount and funding move quickly; industry and country do not.

Where it misleads

Coverage is sold as accuracy. A high fill rate says the provider had something to write, not that what it wrote is right.
Enriched data ages silently. A field enriched two years ago looks identical to one enriched yesterday unless provenance is recorded.
Routing and scoring built on enriched fields inherit the provider's error rate, and the error is invisible at the point it causes a bad decision.
Enrichment cannot fix a collection problem. If the form does not ask, and the provider guesses, the guess becomes the record.

RELATED TERMS

Data Hygiene

The continuous practice of keeping records accurate, complete and current — as distinct from data quality, which is the state that practice produces.

Ideal Customer Profile (ICP)

The definition of the accounts your product serves best, grounded in the observed characteristics of customers who buy quickly, stay, and expand.

Lead Routing

The rules assigning each inbound lead to a specific owner — by territory, segment, product, account ownership or round-robin.

Lead Scoring

A model assigning a numeric value to leads based on fit and behaviour, so attention goes to the ones most likely to convert.

COMMON QUESTIONS

What is data enrichment?: Appending attributes from a third-party source — firmographics, technographics, contact details — to records in your CRM.
How accurate is enrichment data?: Variable, and it decays. Employee counts, job titles and technology stacks all change continuously, so a field enriched a year ago describes a company that may no longer exist in that form.
What is match rate and why does it matter?: The share of your records the provider can identify at all. A 90% accurate provider with a 40% match rate enriches 36% of your records, and that is the number that matters for anything keyed on those fields.
When does enrichment fail to help?: When it lands after the decision that needed it. If routing fires before enrichment returns, the rules read empty fields and the data is irrelevant however good it is.

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