Why HCP Audience Match Rates Differ Across Partners
A reconciliation workflow for comparing HCP match rates across partners by testing denominators, eligibility, identity, geography, and channel rules.
The short answer
Two HCP partners receive the same NPI list and report match rates of 45% and 78%. The instinct is to assume the higher number is better. Often it is not. Match rates differ because partners define matching differently, start from different denominators, and apply different rules. Before comparing, reconcile.
What a match rate actually measures
A match rate is the share of a submitted list that a partner can associate with something it can target: a device, a cookie, an email, a login, or a professional platform account. "Matched" can mean very different things:
- Deterministic match to a verified professional login or registration.
- Deterministic match to an email address tied to the NPI.
- Probabilistic match based on location, device behavior, or modeled signals.
A 78% probabilistic match rate and a 45% deterministic match rate are not comparable. See deterministic vs. probabilistic HCP identity.
The reconciliation workflow
Ask each partner the same five questions and put the answers side by side.
| Check | Question to ask |
|---|---|
| Denominator | What list count did you start from, and did you remove any records before matching? |
| Eligibility | Which providers did you exclude by policy, and how many? |
| Identity method | What share of matches are deterministic, and to what identifier? |
| Channel scope | Is the match rate for all channels or only one (display, video, email)? |
| Recency | Does "matched" require recent activity, or any record ever seen? |
Partners that cannot answer these in writing are telling you something about their transparency.
Common reasons rates differ
Pre-filtering. Some partners remove records they know they cannot match before calculating the rate, which inflates it.
Channel mixing. A partner may report a blended match across display, video, and email, while another reports display only.
Recency windows. A match based on a login seen in the past 30 days is much stronger than one seen in the past two years.
Geography and specialty. Coverage often varies by region and specialty. Two partners can have similar overall rates and very different rates for your priority segment.
Compare what matters
After reconciling, compare three things instead of the headline match rate:
- Deterministic matches against the full submitted list.
- Match rate within your highest-priority segment.
- Verified reach delivered in a test flight, measured against the intended universe.
The third is the most useful. A partner that matches fewer providers but delivers verified impressions to more of them can be the better buy.
Hypothetical example
Partner A reports 78% match. After reconciliation, 30 percentage points are probabilistic, and the rate was calculated after removing 15% of records as unmatchable. Partner B reports 45%, all deterministic, calculated on the full list. In a two-week test, Partner B delivers verified impressions to more top-decile prescribers than Partner A. These figures are illustrative.
Practical takeaway
Never compare match rates without the five reconciliation answers. Better yet, run a short, equal-budget test and compare verified reach against the same fixed list.
Sources
External guidance and platform documentation change. Links were current at publication; check them again before relying on them for a decision.
Editorial note. Analysis and frameworks are the author's own and do not represent Acxiom or any current or former employer, client, or named platform. Examples labeled hypothetical or illustrative are not results from real campaigns. Nothing here is legal, regulatory, or medical advice.
New pharma programmatic breakdowns, occasionally
One email when I publish something worth reading. Benchmarks, measurement teardowns, and case studies with the caveats attached. No cadence promises, no reselling your address.
Unsubscribe any time. See the privacy policy.
Working through this decision on a real plan?
I work on health and pharma data, identity, and activation, after five years running HCP and DTC programmatic agency-side. Happy to talk through how this applies to your situation.