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Blog, Comment & Insight

For Pharmaceutical Marketing Analytics

How AI Is Changing the Pharma Sales Force Model

Posted by Dr. Andrée Bates | Apr 12, 2018 4:35:58 AM

Pharma sales reps historically have faced numerous challenges. Access is difficult with a recent survey showing that 49% of physicians placing moderate to severe access restrictions (up from 45% in 2013)[1]. This access situation continues to get worse due to factors such as physicians simply having less time, physicians being part of a larger integrated healthcare group, the Affordable Care act shifting away from a fee for service to a value/outcomes model, the implementation of the Sunshine act, and physician convenience.

Now more than ever, it is critical to both target the right physicians who are receptive to the right message, at the right time, and provide the optimal messages for those individual physicians.

Although there is a lot of data about physicians that can now be accessed (the CRM call notes, prescribing data, social media data, physician browsing data, claims data and a whole lot more), most reps lack time to make sense of it all and the fact that much is hidden within big data (social media data, claims data etc), and reps do not have the resources to access and analyse it. Traditional CLM eDetailing is not able to take these external data points into account, nor the ongoing changes in doctors’ perceptions in real time with every interaction they have.

With big data and the latest advances in artificial intelligence, the sales force model is being revolutionized by forward thinking pharmaceutical companies in areas such as precision targeting, precision messaging and precision sequence and frequency of multichannel marketing including sales rep, eDetailing and other channels. Below we take a look at some key areas around improving the sales force model with AI.

 1. Precision Targeting with AI 

Targeting traditionally only done once or twice a year using historical data, with minimal understanding of the volume of patients with the condition individual physicians have and how they make their drug choice based on different patient ‘jobs to be done’. are still relying on historical information to make physician targeting decisions. Up till now, pharmaceutical sales teams have physicians in the call plan that are believed to be valuable, and historically they have been valuable. But the market is not about yesterday, it is about tomorrow. We are fortunate today that the data available allows us to make more precise predictions about tomorrow using AI.

Wayne Gretzky once answered a question as to why he thought he was so successful and he answered ‘I skate to where the puck is going to be, not where it has been.’ This concept is as valid for physician targeting as it is for ice hockey. When you put this concept into thinking about physician targeting, it is thinking about where the next script is going to be written for the patient condition or type, what are the factors that could help us predict the probability of the next script written for our brand, and how we could enhance that result.

Utilizing predictive physician targeting allows dynamic physician targeting and segmentation, as well as linking to sales force call list prioritization. In addition, it can identify whether a physician is showing signs of switching away from one brand to another. On top of that, if they are important to see soon, it can also identify Which physician is more likely to accept appointments that week (or at short notice)

 2. Precision Messaging with AI 

Pharma sales messaging tends to be one size fits all, with no or limited personalization of optimal message or frequency of message delivery. Sales reps need to find clever and innovative ways to access and engage the most valuable customers, with the right message at the optimal time for the customer, despite having less time and less budget. One size does not fit all. Each physician, and patient, are individuals with different needs which change with time and situation.

By unifying numerous data sources around a physician, and using artificial intelligence to analyze them we can create precision messaging for an individual physician, which means the sales rep can be confident that the messaging they provide is one that will both engage the physician and gain maximum results.

3. Precision Frequency and Sequencing of eDetail and Face-to-Face Details with AI

Using AI we are now able to identify, by individual physician, what the best sequence of events (messaging and channel i.e. sales rep, eDetail, other channel) is for individual physicians. This means we can achieve the optimal balance of detailing, eDetailing and other sales and marketing channels by doctor. All of this can be automated to work with the sales reps CRM and other automated web management programs for the ultimate automation so free up the reps to get maximum value from the face to face calls they make.

Conclusion 

The most successful sales reps present the right content to the right physician at the right time in the right sequence. However, most sales reps do not know who are the best physicians, cannot find the best content and do not know what influences the physician has had since they last spoke with them, nor are able to see the physician at the right time.

By integrating all the data available and applying Artificial Intelligence algorithms to it, we can get maximum engagement and results from not only our sales force but the other channels working in harmony with the sales teams’ efforts.

Companies can now achieve all these things with recent advances in big data and the use of Artificial Intelligence.

For more information on how Eularis do this, please contact the author at Eularis http://www.eularis.com

[1] https://www.zs.com/Publications/Articles/AccessMonitor-2014-Executive-Summary

Topics: Marketing Insights, Big Data, Artificial Intelligence, Advanced Analytics

Written by Dr. Andrée Bates