How to Use AI to Create Value for Physicians, Not Just Target Them

This kind of precision targeting is leaps ahead of the kind of targeting exercise many companies are still doing which is essentially making decisions about value based on historical information of past value rather than more precision about future value. So using AI for targeting is a critical first step.
 
AI can answer the following 2 questions:
    •    Who prescribes what, when, and at what price?
    •    Can we can link what the physicians hear, read and view to what they prescribe?
By knowing the answer to these, we can improve targeting and focus our marketing budget on the right channels for the right doctors which is helpful – but is it enough?
 
Marketers and sales teams want to uncover and target the next prescription written, and they can; the company using AI will win that prescription. But, what happens if every company starts to do this with AI? Sure, the best algorithms will do it better but let’s assume they are all pretty good. What then? There is no sustainable competitive advantage in winning the next script. I am not arguing against doing this. I think it is a must, especially given so few companies are doing it yet. However, rather than just looking at how to target customers better, we also should be looking at how to create better value for our customers in order to crate longer term customer loyalty and stronger customer relationships and engagement.
 
In order to do these types of analyses we need to ask how big data can create value and experience for customers and bring profitable results to the company? Amazon does both in a simple way with their recommendation engines – they suggest products you may like, offering a service to you that is using AI, but it also gets them more sales as in many cases, the products are bought. Amazon reported a 29% sales increase to $12.83 billion during its second fiscal quarter, up from $9.9 billion during the same time last year. Fortune magazine reported that growth arguably has to do with the way Amazon has integrated recommendations into nearly every part of the purchasing process. Their recommender system is based on several components of data: what a user has bought in the past, which items they have in their virtual shopping cart, items they’ve rated and liked, and what other customers have viewed and purchased.
 
You do not have to be Amazon to create valuable AI driven services that will assist not only your physicians and patients but also your bottom line. Pharma may not have that data but we have fairly strong data on physicians that we can integrate and create recommender systems for both rep actions as well as integrated marketing.
 
Value and strong customer experiences are formed with all contact (either direct or indirect) with the company. For a physician, direct contact is through actions such as the sales call, the call center interaction and even interacting with patients on your drugs. Indirect would be things like your marketing (advertising, your website, word of mouth, reviews, editorials etc). Successful brands shape their customer experience by embedding their value in all interactions.
 
As more patients participate in their healthcare through wearables, ingestables, and implantables, opportunities arise to understand customers in a holistic way. This allows us to analyze, understand and predict what would offer real value to customers, and deliver more comprehensive healthcare solutions.
 

We used artificial intelligence to identify what both these services as well as the individual components needed within each service to ensure it offered enough value-add for the brand to launch successfully if they offered them despite the high price tag compared with other identical products. The project involved both a patients and physicians, and saw the drug become the largest in the class within six months of launch. The company is now taking this further by adding this data to other data – wearable sensors, social media, CRM, doctor prescribing data – to further refine and tweak the program.
 
So this demonstrates that we can use AI to augment the services offered around a pill and AI can help both uncover and design the components of those services as well as be a component in the service offering. Using big data, Artificial Intelligence can answer fundamental questions that previously could not be answered.
 

1. What type of information will help physicians (or your patients)?
This is something that needs careful analysis when looking at data. There will be many options that answer this question and is something Eularis do in our consulting practice.
2. What type of data is available but not integrated that would yield a lot of insights if it was aggregated together?
3. Would there be a way for my customers to benefit if we aggregated their data with each other?
For example, data from devices on inhalers in asthma, or blood glucose monitoring can be combined to predict which patient is likely to have an attack, which could save the patients’ life.
 
There is so much that is possible with a little thought and planning and data discovery. And if you need help, you know where to find us.
 
For more information on this topic, please contact the author at abates@eularis.com or contact us via the contact form on our website.