In drug development, innovation tends to happen in the lab. But increasingly, innovation is also transforming the way therapies reach patients after approval. Pharmaceutical sales and marketing strategies – once built on static, decades-old models – are being reshaped by real-time data and artificial intelligence. For many in R&D and manufacturing, this world may seem far removed from the science of drug development, yet the way companies engage healthcare professionals (HCPs) ultimately affects how quickly and effectively treatments reach patients.
For more than 30 years, pharmaceutical field teams have relied on decile-based targeting (DBT), which is a process that ranks doctors by prescription volume and divides them into ten “deciles” or groups. Sales reps then focus their attention on those in the top tiers. While this system provided structure, it also locked the industry into a static, slow-moving approach that failed to reflect how prescribing behaviors and competitive dynamics shift in real time.
Now, a new model is emerging. Dynamic segmentation and targeting uses AI and live data streams, including from prescription trends and digital engagement to diagnostic activity, to continually update and refine outreach. Instead of relying on outdated lists, sales teams can respond to market shifts as they happen, aligning commercial activity with the pace of modern healthcare.
We speak with Peter Harbin of ODAIA and Frank Fascinato of Treviso Consulting to find out why static segmentation no longer meets the needs of a complex and fast-changing market, and how dynamic, AI-enabled systems are redefining how pharmaceutical companies connect with HCPs.
What are the problems with decile-based segmentation lists?
PH: HCP data is stale the moment it arrives, which creates major downstream problems across commercial activities, from marketing campaigns to sales reps’ face-to-face interactions and digital engagement. By the time a list gets analyzed, approved, and rolled out, reality has changed. Doctors can switch specialties, prescribing habits can change, or new competitors may enter the market. But no one sees this until the next list is done months – sometimes a year – later.
FF: Every sales rep has known forever that the call plan was old by the time they got it. You get your segments, see a few familiar names, maybe a few curveballs, or find a retired doctor. Then sales reps do what they always do: they make it work. That’s been the playbook for decades.
Why has the industry been slow to move away from this approach?
PH: Because it’s ingrained. We still build targeting lists the same way we did in the 1990s. You build a list once or twice a year and the field works from it until the next one arrives. Everyone hopes it reflects reality, but it never does. It’s just how things have always been done. Companies have been slow because they didn’t have to be fast.
FF: After two decades in pharma doing sales, ops, marketing, and training, I can tell you that nobody ever fully trusted the targeting list! Yet everyone sticks to it and adapts, and works around its limitations.
How do you see newer, dynamic models reshaping commercial strategy?
PH: Simply put, commercial teams will stop looking in the rear-view mirror and start looking at what’s going on around them right now. They’ll replace these annual or semi-annual exercises with forward-looking, signal-based continuous systems that take in new information as it arrives, provide context, and adapt their campaigns and call lists in real time. Organizations can finally account for behavioral signals as they happen, and combine them at the territory level to make HCP engagement much more relevant and timely. Teams can move beyond reach and frequency as the primary measure of field success.
FF: Dynamic segmentation and targeting can provide real-time insights that were nearly impossible to get before. It uses data for better insights, creates greater alignment across commercial teams, and when it works, something shifts. Marketing sees the same shift that the field is seeing. Ops notices the same movement in engagement that sales reps are sharing anecdotally. Suddenly, everyone is on the same page.
Do you envision this replacing segmentation cycles entirely, or coexisting with more traditional approaches?
FF: You have to go all in. You can’t have one foot in and one foot out. If you’re going to do this, commit fully. Otherwise, sales reps will just go back to what they know.
PH: Exactly. Change doesn’t happen just because you buy a new platform. It happens because executives push for new ways of working to challenge legacy processes.
Have you seen examples where early adopters of dynamic segmentation and targeting pulled ahead of competitors?
FF: Yes. In a pilot, one sales rep saw a physician move to the top of the list overnight. Another could see signals that a doctor started prescribing a competitive therapy. We used this data to reinforce the strengths of our therapies. We could not have done this with a static model.
PH: For a top pharma customer, our system flagged new diagnostic activity for a different indication, revealing the doctor was now seeing patients for another approved use of the brand. This prompted the sales rep to change their approach. Dynamic segmentation and targeting opened up an entirely new opportunity that the old model would’ve missed entirely.
Are there particular therapeutic areas where the shift is most urgent?
PH: In rare disease and specialty categories, patient populations are small and competitive pressure is high. If you miss the moment to engage the right doctor, it can mean missing the patient altogether, and you may not get another chance. That’s why dynamic segmentation and targeting isn’t just a field enablement strategy but a commercial imperative.
FF: There is definitely high urgency and high stakes in areas like rare disease. That said, every HCP writing a prescription is treating a patient, and for that individual, the treatment could be the difference between getting out of bed that day or not. Going to work that day, or not. Playing with their kids or not. I see this as an opportunity that crosses all therapeutic areas so that all HCPs can provide the best care for all patients.
What feedback have you received from field teams?
FF: Sales reps tell us how much time they get back. When you surface signals in one view, tied to what they’re asked to do, it clears the noise and reduces their cognitive load. They don’t click 12 times for insights – it’s all there in one place.
PH: The life sciences industry plays an important role. We’re not selling shoes here. Doctors are making life-altering decisions, and our job is to help them get it right. Dynamic segmentation and targeting speeds the path to the right therapy — diagnosing faster, acting with more accuracy, and cutting the time it takes for patients to get on treatment. Patients feel the benefit directly: engagement happens at the moment it matters, helping them start therapy sooner
Which real-time signals are the most valuable, and how do you ensure their accuracy?
PH: Behavioral signals matter most — things like lab diagnoses, HCPs visiting brand sites, ad clicks, or offices checking coverage. They all point to potential prescribing activity, and when you layer them together, you get real context. With that, you can give sales reps a clear rationale on how best to approach their target HCPs.
FF: This is really where the static models show their limitations. They don’t fail because the industry lacks data — they fail because they can’t capture real-time signals, so the field stops believing in them. Dynamic segmentation and targeting uses AI to surface live signals right when they matter. When signals and reasons match what they’re already seeing in the field, that’s when you earn the field’s trust.
Data fragmentation is a constant challenge in pharma. How do you overcome silos across prescription claims, lab triggers, and digital engagement data?
PH: Every pharma company is basically a data company now. The problem is that the data is slow, expensive, and siloed. What we do is connect structured and unstructured data from many channels, run it through different AI engines, and turn it into actionable context for the field.
FF: You need to balance getting enough data without flooding the field. Too much data causes analysis paralysis. But these data inputs are critical for shaping targeting and segmentation. AI changes everything because we can make sense of data faster than ever and get the richest view and context possible. It’s an evolution in the sophisticated use of data. Instead of relying on a single variable, you can draw from many at once and surface patterns that were previously invisible.
How do you see dynamic segmentation and targeting evolving over the next five years?
PH: Once real-time targeting is in place, omnichannel orchestration can become truly personal. Brand messaging can be adjusted in days, not months. Every HCP interaction, whether digital or in-person, feeds right back into the model. Success won’t be about who has the most data. It will be about who can act on the right data at the right time.
FF: With a dynamic view of targets, you can align other channels to match – digital touchpoints, marketing content, everything. It all works better when pointed at the right people at the right time. There’s no future commercial roadmap without AI as part of it. Ultimately, this evolution creates a foundation for better care delivery: doctors diagnose faster, prescribe sooner, and patients live healthier lives.