How Machine Learning Improves Marketing Sequence, Messaging and Channel Optimization

Machine learning and artificial intelligence may sound like something out of a sci-fi movie, but they're actually the dynamic duo of marketing, reaching the majority of homes nationwide every day. When's the last time Netflix or Amazon recommended a movie, book or product to you based on your past purchases? Five minutes ago? That's AI-powered marketing via machine learning in action.

But is it relevant to Pharma? The answer is a resounding yes. Whether it's marketing the latest binge-worthy series to a consumer audience or creating a pharmaceutical brand management strategy to reach health care providers (HCPs), it's about connecting with the customer in a meaningful, even personal way.

For example, Netflix’s recommendation engine uses a consumer’s past watching preferences to identify similar movies and recommends them. Similarly, a pharma marketer can observe HCPs' online behavior (clicks, opens, views, etc.) to figure out what type of channel (email, banner ad, paid search, etc.) and content (efficacy, safety, disease awareness) an HCP prefers at a given point in time to predict what to target that HCP with next.

Historically, marketing a new drug or treatment or other product to an HCP was a two-pronged event. The sales reps would visit the health care facility to speak with the HCPs about the product and then back at headquarters or the marketing office, the digital team would craft messaging, either emails or banner ads or other messaging, to shore up that visit. The challenge? Sequencing those messages, the physical interaction of the salesperson and the digital interaction of the email or other digital message.

The question is, how do you sequence those tactics to get the most out of the physical sales force AND the digital strategy to create one powerful message for the HCP? How often, and when, to reach out to customers has been the Riddle of the Sphinx for marketers since people started selling goods and services. What is the optimal sequence of channels in which marketers should promote to HCPs? How early? How often? What time of day? When is too soon for a follow-up? Also, which channel is best? Email? In person? A webinar?

The answer is with data. Now, we have data going back years. We can observe the HCP's behavior over time. We can look historically and identify which sequences of marketing actions led to the ultimate goal, the physician prescribing the drug or treatment.

Using this engagement data, we can craft future marketing strategies with the optimal sequence that will engage HCPs.

The right channels and messages and how they are sequenced are key to creating a meaningful conversation with a physician. Not only can marketers deploy the right sequence of promotional channels and messages, but they also can measure effectiveness with clickthrough rates, open rates and Rx lift. A whole host of data can be collected by measuring the effectiveness of the message.

Using this data, we can predict the effectiveness of future similar marketing campaigns. Machine learning can predict the next best email message to send to maximize message opening by HCPs. It can also provide a roadmap to sequence optimization — how many messages to send, and when.

You can expand this model to other channels of communication as well, be they webinars, personal visits or social media optimization.

In marketing, machine learning and artificial intelligence is all about customer data, and it's the Holy Grail for reaching a customer at just the right time in just the right way with just the right message. It's about using past behavior to predict future behavior, based on the customer's wants and needs.

Using AI, you can reach for better results from your multichannel and omnichannel marketing. It can help you discover a treasure trove of unique data for each customer, be they physicians, patients or payers, and create unique profiles using that combined data. The insights into each customer's journey, powered by AI, can be used for predictive intelligence, in the same way that Netflix knows which movie you want to watch before you've even heard of it. The result is a heightened, personalized customer experience, a more meaningful interaction with you and your brand, and increased loyalty because you've demonstrated that you know your customer's needs and wants before they do, are anticipating their needs, and coming up with solutions even before they know they need something. That's the goal.

So next time you're settling in to binge watch a series you'd never heard of until Netflix recommended it for you, think of the kind of power AI and machine learning can bring to your healthcare marketing efforts.

Want to learn more? Please read the PMSA journal article by Dr. Decker and Dr. Cohen to further understand machine learning models that empower improved HCP email messaging strategies. 

Please also consider attending the PMSA 2019 Annual Conference, Designing the Future of Analytics in Biopharma, April 14-17 in San Diego. It's a great opportunity to meet the authors and your peers in the pharma management science area.
 




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