Pharma

Selling in pharmacies in 2026: why yesterday's methods fall short

Pharma
Christopher Nadotti
Founder, Marvin.ai & b-flower
5 min read

The pharma rep's job has changed in nature. Here is what the pharmacy floor demands today, and how a lab like Pierre Fabre re-equipped its teams.

For twenty years, selling in pharmacies meant taking orders and negotiating volumes. That job has all but disappeared. Pharmacy footfall is rising again, the pharmacist has become a central player in the care pathway, and they no longer expect an order-taker: they expect a partner who can help them grow shelf revenue. The pharma rep has shifted from a sell-in logic to a sell-out logic. Many sales teams, though, are still trained for the market of before.

The challenges specific to the sector

Three new demands make pharmacy selling harder than it used to be. First, a rep's value no longer rests on volume or discount, but on their ability to run a merchandising assessment, work a shelf display, and train the pharmacy staff. Second, counter time is scarce and contested: a pharmacist grants a few minutes, not a thirty-minute product pitch. Third, the person across from you has become an expert on their own store, and so resistant to generic sales pitches.

The result: a rep now has to hold three roles in a single day. Strategist at the desk, on the data and the CRM. Operator on sell-in. Advisor and animator at the counter, on sell-out. No product training, however good, creates that behavioral agility.

How you practice for this: the Pierre Fabre example

Pierre Fabre Medical Care turned down the easy answer (hiring more senior profiles) and treated the issue as a systems problem. The sales method was not bought off the shelf, it was co-built with the teams, from real personas and real pharmacy situations. As a project lead at the lab puts it, the other providers offered something standard while the firm brought Pierre Fabre into the thinking.

But the real turning point came from practice. Each rep runs meetings against a role-played customer, with an AI that observes and analyzes, in a few seconds, the micro-behaviors that decide a meeting: talk-to-listen ratio, quality of discovery, needs reformulation, handling of silences, buying signals caught or missed. The measured gap is telling: the best reps talk 43% of the time on average, against 68% for the market average. Without measurement, a gap like that stays invisible. On top of that, having the right content in the meeting (up-to-date sheets, prepared objections, sector cases) makes sure the rep delivers the message marketing built, instead of improvising their own version.

What this changes

Coaching stops being a blind ride-along. Every week, the manager gets a map of their team's behaviors, not just their results. They know what to help each rep with, precisely. And forecasts become more reliable, because they rest on signals captured in real meetings rather than on the rep's optimistic self-reporting.

It shows that performance in pharmacies is not replayed in an annual seminar, but in regular repetition, until the right move becomes second nature.

To understand how the synergy between AI practice and sales content works on this kind of rollout, see the article on the Salesapps-Marvin partnership. And for the signals that conversation analytics makes visible in the field, the article on field conversation analytics rounds out the picture.

Frequently asked questions

What has changed in the pharma rep's job?

The rep has shifted from a sell-in logic (taking orders, negotiating volumes) to a sell-out logic (growing shelf revenue, working the shelf display, training the pharmacy staff). The pharmacist no longer expects an order-taker but a partner who can help them grow their store.

What are the three roles a pharma rep has to hold in a single day?

Strategist at the desk, on the data and the CRM. Operator on sell-in. Advisor and animator at the counter, on sell-out. No product training, however good, creates that behavioral agility: it is built through repetition on realistic cases.

What behavioral gap shows up between the best reps and the market average?

Field data shows that the best reps talk 43% of the time on average, against 68% for the market average. Without measurement, a gap like that stays invisible and cannot be corrected. That is exactly what AI analysis makes visible and actionable.

How does the manager's coaching change with AI analysis of meetings?

Coaching stops being a blind ride-along. Every week, the manager gets a map of their team's behaviors, not just their results. They know precisely what to help each rep with, which makes coaching faster, sharper, and more effective.

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