Maximizing MCM Impact: Part 4
Magali David, Solution Sales Manager Gilbert Merariu, Senior Principal, Technology
Blog
Nov 21, 2019

Leveraging Artificial Intelligence and Machine Learning to Maximize MCM Impact

Brand teams can use Artificial intelligence (AI) and Machine Learning (ML) to make the most of each multichannel engagement. Here are a few suggestions and predictions that AI/ML can help you with:

  1. Each customer’s preferred channel of communication (e.g. email, text, face-to-face, physical brochures, presentations)
  2. Best messaging
  3. Best cadence (frequency for each channel)
  4. Timeline (time of day/month)
  5. Most appropriate tone of message based on profiles

Using AI/ML suggestions appropriately can lead to a larger impact on your MCM efforts.

The chart below shows the impact of each individual channel on your customer behavior (left). Although face-to-face details is the highest impact channel overall for customers, this is not true for every physician. The graph at the bottom right shows that Dr F. responds best to digital channels which deliver a better impact for this particular individual.

If you are a brand manager, we can guess at this point that you would be willing to do the same analysis with your customers to show the organization the value your MCM strategy and tactics are bringing to them.

To do that, as was discussed in the previous blog in this series by Mike Ness of Data Ad, it’s imperative to collect metrics on your outreach activities as part of your MCM execution plan in order to measure success.

Like most Life Sciences manufacturers, today you are probably only capturing Rep touchpoints. Other channels such as email, website, direct mail, phone detailing, and other non-personal channels are not being captured at all or, at least, not at the level of granularity that is needed to analyze, let alone perform, AI/ML studies.

What should you do to collect and organize data for AI/ML?

1) Own – Use technology to execute and capture all of your touchpoints. Ensure your third-party partners doing outreach on your behalf are collecting and sharing detailed information at the customer level.

2) Centralize – Create a central repository where every single activity is captured at the customer level. Set up processes to update your data frequently, in real time, if possible.

3) Organize to enable orchestration – Standardize, clean and segment all captured data, so it is ready to be consumed by your AI/ML algorithms and other analytical tools.

What’s Next…

This is an exciting time for Pharma Marketers. Our prediction for the next decade is that the companies who will lead the industry are those that have a strong orchestrated client engagement strategy bundled with tactics supported by technology, including AI/ML, rich data, and strong domain expertise.

If you are fascinated by AI/ML and want to learn more, we highly recommend you read the blogs written by our colleague Hans Hansen, at this link: Leveraging AI/ML to Drive Commercial Success in Canada (Part 1)

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