Pharma Programmatic Benchmarks: The Planning Numbers I Actually Use

A word on sourcing before any numbers. The figures below are planning ranges from campaigns I have personally run or overseen across HCP and DTC pharma programmatic. They are directional by design. I am deliberately not quoting precise industry-wide averages, because most published pharma benchmarks blend therapy areas, channels, and quality tiers into numbers that fit nobody. A rare-disease HCP campaign against nine hundred specialists and a mass-market DTC vaccine campaign share almost no economics. Use these as starting stakes in the ground, then replace them with your own data as fast as your measurement allows.

Cost: what pharma actually pays for media

My working planning figure for a blended pharma programmatic mix, display plus online video across HCP and DTC, is around an $18 blended CPM, the same directional number that drives the interactive planning model on my homepage. Underneath that blend, the spread is wide and predictable. Standard DTC display sits well below the blend. Online video and CTV sit meaningfully above it. And endemic HCP inventory, point-of-care and clinical reference environments where a validated prescriber audience is the product, prices at a multiple of consumer display, because you are paying for the audience guarantee, not the pixel.

The mistake I see most is treating a high HCP CPM as inefficiency. Cost per thousand impressions is the wrong unit for HCP media; the right unit is effective cost per reached target prescriber. A premium CPM against a perfectly matched specialist list routinely beats a bargain CPM that sprays the open web, once you divide spend by the prescribers who actually saw it.

Delivery: match rates and target-list reach

Two delivery benchmarks govern whether an HCP plan is real. First, the match rate: the share of the NPI list your identity partners can resolve to reachable digital identifiers. Expect meaningful loss here, and expect it to vary by specialty, list hygiene, and channel; CTV household matching behaves differently from endemic display matching. Second, verified target-list reach over the flight. I set reach expectations by specialty size: a small specialist universe can be covered deeply within a quarter, while a broad primary-care list is a reach-frequency tradeoff you manage deliberately. Whatever the number, the discipline is the same: reach against the list is reported weekly, from measurement-grade sources, not platform dashboards.

Outcomes: the funnel from exposure to script

On the outcome side, the two conversion rates I anchor plans on come straight from my measured campaign work. Roughly 1.25% of exposed, Crossix-verified audiences convert to a pharmacy or care visit in my directional planning model, and in the seasonal launch documented in my Crossix and IQVIA attribution case study, 31.5% of those verified visits converted to a prescription. Chain those with your CPM and you get the arithmetic my homepage planner animates: budget to impressions to verified visits to projected scripts. It is a directional model, and I present it to clients as exactly that, but it turns budget conversations from vibes into algebra.

What moves these rates? Indication urgency more than anything. A symptomatic condition with a seasonal spike converts exposure to visits far faster than a silent chronic condition. Creative quality and frequency sufficiency move them next. Audience quality moves them most of all, which is why the delivery benchmarks above are upstream of everything.

Engagement metrics: use with a long spoon

You will notice I have not offered CTR or video completion benchmarks as success metrics. They exist, and video completion in premium environments should be high, but in pharma they are diagnostics, not outcomes. A click is almost never the paid-for event; a verified script is. I use engagement metrics to catch delivery problems, a completion rate collapse flags bad supply, a CTR spike often flags accidental bot traffic, and never to declare victory. The measurement hierarchy that replaces them is laid out in How Programmatic Media Drives Rx Outcomes.

How to use benchmarks without overclaiming

Three rules keep benchmarks honest in client work. State the source and the confidence: a number from your own measured campaigns outranks any industry deck, and a directional model should be labeled directional every single time. Benchmark against yourself as fast as possible: after one measured flight, your own visit conversion and visit-to-Rx rates supersede anything generic, which is the real reason to invest in measurement early. And never let a benchmark become a promise: benchmarks set planning expectations, measurement settles outcomes, and confusing the two is how agencies lose client trust.

Building your own benchmark base

The endgame is a brand-specific benchmark file that compounds. Every flight should bank its verified reach, match rates, conversion rates, and cost-per-reached-target into a running reference, cut by therapy area, audience, and channel. Within a few flights, planning stops leaning on borrowed numbers entirely. That file, not any industry report, is the most valuable analytics asset a pharma media team owns.