Our Chief Strategy Officer, Hemal Somaiya, took the stage at the recent Reuters Pharma Customer Engagement USA conference. Her presentation addressed a quiet frustration with omnichannel that is shared by many in the industry: We feel like we paid enough to buy a Ferrari, but we are stuck in a stalled mid-market sedan.
Companies have spent years investing in infrastructure and tools, yet 8 in 10 pharma leaders still struggle to see the measurable impact of omnichannel on customer engagement.
During her session, “AI-Powered Precision and Agility: Redefining Customer Engagement,” Hemal broke down why the current model is stalling and introduced the next evolution: Optichannel. Tech has outpaced pharma’s ability to keep up, and delivering more relevance through optichannel strategies will help customer engagement teams drive sustained impact.
Here is a recap of the session, including the real-world case study she presented that proves why “being everywhere” should not be the goal.
Multichannel vs. omnichannel vs. optichannel in pharma
Over the past decade, the industry has moved through three distinct phases:- Multichannel: This is the past for many but continues to be the reality for some marketers. Many channels are used (email, rep, web ads), but they’re siloed. The goal is generally about volume, and little data is shared across channels.
- Omnichannel: This is the present for some teams, who have connected the channels with an aim of creating a seamless experience. The goal was consistency in customer experience, but in reality there’s still little orchestration to improve experience beyond consistent messaging and creative.
- Optichannel: This is the present for early adopters and the future for the industry. We use AI and real-world data (RWD) to select the best channels and moments for each specific HCP. The goal is precision and ROI by using data and predictive insights, without the need to invest everywhere and stretch budgets too thinly.
Case study: "Before and after" look at launch efficiency
Hemal presented a case study of a recent specialty oncology product launch. This scenario is becoming the new normal: a mutation-driven indication with a small patient population, tight budget, and a competitive environment where breaking through the noise to engage overwhelmed HCPs is difficult.
The brand needed to identify and engage treating providers efficiently, but the traditional launch playbook wasn’t delivering results. In fact, it doesn’t work for most brands–data analyzed by EY in 2025 shows that more than half of new products are missing their sales forecasts.
BEFORE: Traditional launch strategy (Months 1-6)
For the first six months post-launch, the brand relied on a standard omnichannel, “always-on” media approach with content and several connected channels. However, they lacked the real-time triggers to make engagement relevant, the dynamic data to deliver via the best channel and tactic for each customer, and the orchestration to ensure that content on one channel complemented different content delivered on another. The brand saw some uptake, but it was slow and they experienced difficulty gaining share of voice.
AFTER: The optichannel pivot (Months 7-11)
Frustrated by lackluster results, the brand partnered with us to implement an optichannel strategy. Instead of broad outreach, the strategy pivoted to AI-powered precision using:
88% of new scripts could be tracked directly back to PFIQ triggers. The approach also uncovered hidden opportunities that contributed more to the topline metrics: The system identified ~400 new HCPs outside the original target list who had eligible patients and who began to receive personalized next-best-action journeys.
Insights were also shared with reps via the brand’s existing CRM workflows so the field had more context on HCPs, what they were engaging with via digital, and how to add even further value within their territories.
- Affinity intelligence: We mapped audience preferences to predict exactly where target HCPs spent their time, predicting the most valuable and optimal mix to maximize engagement and eliminate media waste.
- Real-time triggers: The campaign utilized lab data from mutation test results and claims data to trigger outreach in relevant moments when HCPs were more likely to have an interest and need.
- Speed to engagement: When a trigger was identified (e.g., a positive test result), the system deployed a personalized “Next-Best-Action” sequence across channels within 24–48 hours—engaging the HCP based on their individual preferences before the treatment decision was made.
- Ongoing optimization: Sequences were optimized via machine learning in real-time based on HCP engagements and non-engagements. More importantly, we also tracked Rx lift so the system could double down on what was driving prescriptions and cut what wasn’t—optimizing the campaign in real time, not at the end of the quarter.
Moving the needle on market share in just 5 months
The difference between “being available” (omnichannel) and “being relevant” (optichannel) was obvious in less than six months. Average HCP engagement rates grew by more than 4x, and monthly market share jumped rapidly. Individual journey-level metrics and aggregate impacts were shared via live dashboards so the brand team could see progress in real time, including on script lift.| Metric | First 6 months | 5 months after adding PFIQ | Impact |
| HCP engagement rates | 12% | 52% | +4x engagement |
| NRx share per month | 38% | 47% | +24% lift in market share |
Why it works: Relevance over reach
Speed and relevance are the new standards for pharma marketing.
By waiting two or more weeks for partner turnarounds and a quarter or more for standard reporting cycles, brands miss the critical window of influence. The optichannel model works because it shifts to agile media—engaging customers rapidly in the right moments when the information is truly relevant to a patient and an upcoming treatment decision.
Optichannel is about focusing resources to drive outcomes. The goal is to use data quickly and efficiently to predict channel mix for your audience and optimize dynamically. As the case study showed, shifting from “everywhere” to “exactly where it matters” can save on media costs and drive the kind of script lift that traditional launches struggle to achieve in years, let alone months.