Could an algorithm improve the commercial model in Pharma? Launching a new medicine carries much effort and preparation. And yet the moment of truth comes when doctors may prescribe the product.

Why is he/she picking out this new medicine instead of any other available option? What sort of information has he/she received to influence their prescribing behaviour? What’s the unmet need this medicine is satisfying to a specific patient and a particular prescriber?

Marketing efforts boil down to the famous statement: delivering the right message to the right audience at the right time on the right channel. Thus it seems extraordinarily relevant to tease physicians’ personal needs out and to hone communication strategies at an individual level.

The most common approach is to hold sales reps accountable for this process. Many resources, studies, etc. are handed to them, and they must prioritise what really matters to individual prescribers. In addition, MCM is often used to enhance the share of voice by adding more interaction and diversifying channels.

Orchestrating all channels, however, is not an easy process. Profound knowledge of customers’ needs, concerns and expectations are needed.

Algorithms that provide best-in-class customer experience: Google, Spotify and LinkedIn

Many people would claim that Google’s algorithm has made the world a better place (Silicon Valley’s famous motto). Larry Page and Sergey Brin came up with an algorithm to rank web pages. As a consequence, to look for information on the internet became quicker, and the results displayed are even tailored to our personal needs.

Spotify can propose songs that you’ll probably like. Firstly, your taste profile is determined. Secondly, an algorithm tracks playlists created by people with the same music taste. Finally, Spotify will suggest the mainstream songs among all playlist, with a good chance you’ll like them. Simple, isn´t it?

LinkedIn or Facebook need to capture our attention as long as possible. Every post relevance is dynamically calculated taking into consideration the interaction from other users. Additionally, your profile is identified according to your communications and likes. Lastly, an algorithm will work its magic and, as a consequence, a curated feed is displayed to us.

Pharma industry is different… or isn’t

On the one hand, there are as many digital enthusiastic as sceptical people. Some digital evangelists show examples from other industries as a means to inspire change.  

On the other hand, less enthusiast people challenge the real value delivered by digital channels. At most, they acknowledge their importance in terms of brand awareness, but not customer engagement (=sales).  

Digitalisation, MCM and digital engagement seem to be at the top of every agenda. However, adding more channels could be seen as an investment with low or no return at all. Indeed, the crucial point may be in identifying what really matters to individual prescribers, and meet their needs with a variety of channels.

Arguably, the critical challenge is to gain in-depth knowledge of healthcare professionals and, subsequently, to fulfil their individual needs. In short, to deliver best-in-class customer experience.

Building an algorithm to improve customer experience in Pharma

Searching for inspiration

I’m a confessed believer in the start-up methodology, although it’s not always supported in corporate companies.

Before committing significant investments and involving many people, the hypothesis should be tested. The term MVP (minimum viable product) could be adapted to MVS (minimum viable service) or MVW (minimum viable whatever).

#algorithm #CX #Pharma #engament
Image by Henrik Kniberg

The hypothesis

As mentioned above, best-in-class customer experience is delivered tailoring communications or services to single users (=prescribers). Therefore, customer profiling seems crucial to accomplish this mission.

eDetailing for customer profiling

Most medical sales reps are equipped with tablets, and it’s quite common to use digital sales aids to detail doctors. Consequently, a purposefully created presentation is more than enough to prove our hypothesis.

Let me elaborate on this:

  • Define personas (=segments) according to the strategic goals. For instance, it may be according to the data they need to start prescribing a medicine (mechanism of action, comparison vs competitors, KOLs’ endorsements,…)
  • Devise a digital sales aid to be handed to reps. A few screens with relevant data is useful both to support reps’ pitches and to track physicians’ needs.
  • Let reps do their job and capture what information they use with every single doctor.

The beauty of simplicity

As much information is captured in a variety of channel, much accurate should a profiling be, but to start small allows to test assumptions and to learn in the process.

The idea is simple and the algorithm too: if some screens are more used than others, then it will mean prescriber interest is in that particular topic. Obviously, succeeding in this endeavour requires effort, knowledge and an innovative attitude. Nevertheless, the future of business is data-driven, and we mustn’t forget this fact.

Key to success

Finally, I would like to highlight some key factors:

  • Don´t focus too much on technology. To use Veeva, Agnitio or MI touch doesn´t make any difference. As I’ll discuss in further posts, technology can be a big distraction from what matters.
  • “Human intelligence” is a must. Forget buzzwords such as AI or machine learning. My colleague Alberto, provided with his analytical mind and deep business knowledge used to show me how to transform a bunch of numbers into valuable insights.   
  • Change management. Many people are still sceptical with regards to multi-channel engagement with customers. Communication, upskilling and, above all, short-term wins help to change mindsets.

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