In recent years, our target audience changed from just doctors and patients to also include payers, pharmacists, physician assistants, nurse prescribers, patient associations and more. Despite these differences, pharma marketers are still segmenting customers the same way they have for decades.
As you know, segmentation is about dividing customers into groups that are similar in specific ways with respect to various dimensions that are relevant to the business, and meeting the needs of that customer group appropriately. Typically, marketers focus on value segmentation (value to us) grouping the physicians by their value to the brand or company. Then each physician is prioritized and resources allocated against the segments with the higher value physician being seen more by sales reps and given more services and so on. While each segment has a tailored campaign created for them, the segment is still broad.
As you know, typical segmentation approaches have a combination of factors including prescribing levels, as well as attitude and behavior outside of prescribing. But they do still tend to be measured on a limited number of variables which are analyzed using a linear approach to determine the best set of attributes. This is extremely limited when one understands the variety of variable that go into why humans behave as we behave, and make the choices we make. Additionally, within one pharma company you are likely to have the same physicians in multiple brand target lists – but these are siloed and not integrated with each other. By unifying these data siloes, far richer customer information can be found.
Today’s customers expect a personalized approach. For example, you’ve probably shopped at Amazon.com. You’re aware of the way the retail giant segments their customer base by making suggestions based on past behavior. You may have purchased something based on such recommendations. Now imagine that pharma marketing can be similarly targeted but potentially with even more data if you are adding in your CRM data, ATU data, IMS data, IOT data and much more.
When you harness the power of Big Data you can improve your segmentation because you have the information you need to make reliable and actionable decisions. Targeted segmentation is a fundamental part of a marketing plan and can be a powerful tool for a company – especially if that company uses such information to create specific offerings for each segment and breaks them into smaller groups.
The Future of Segmentation
An approach that achieves value for both pharma and the different customers is be possible using artificial intelligence (AI.)
You can think of AI as a component of algorithms that use a non-linear approach to gather millions of data points (Big Data) and synthesize it into useful insights for your marketing.
With AI we can marry unlimited customer variables into the algorithms in real time, and find the optimal segmentation among these. This approach links the segmentation to business results that is embedded into the code. When we connect all our data and apply AI to it, we create:
- A 360 degree view of the customer and data input in real time and constantly updated in real time so that you know what your customers are responding to and you can adjust your marketing accordingly. You won’t have siloed data that lacks integration.
- Effective segmentation treats each customer as an individual based on their individual needs. You know the “one size fits all” approach doesn’t work. AI can help you hone in on preferred channels and messaging to connect with individuals.
- Identify inconsistencies in behaviour to spark serious personalization.
Today’s pharma marketers face splintered channels and fragmented audiences. With AI, you can use this to your advantage. AI makes it possible to align the brand strategy with value propositions that speak to a narrow market segment. For example, what type of marketing approach does your customer appreciate? Depending on whom they are and where they are in the buying cycle, they may prefer educational opportunities such as webinars or prefer calls from sales people. AI can segment these for you so you’re maximizing your marketing budget by reaching the right people through the right channel with the right messaging.
Pharma companies have the opportunity to become trustworthy partners through this level of improved customer service. You already understand the value of highly targeted segmentation from your experience with consumer brands like Amazon. Eularis use AI to help pharma companies take this to another level so you can be ahead of Amazon. Using AI alone is not a panacea. We see pharma companies working with well-known AI brands who do not have the history in pharma and so are not linking pharma strategy with AI effectively for their pharma clients. It is critical to not just trust that AI alone will solve your challenges however effective and strategic use of AI can.
Marketers who develop well-optimized strategies that align your marketing tactics with customer behaviours have the opportunity to create more personal connections with your customers. In the era of personalization, that’s a very real competitive advantage. Eularis.com works with our pharma clients to create a powerful combination of business strategy with customized algorithms that incorporate all your data (CRM, CMS, social media) in one platform and deliver the information you need to develop a successful marketing strategy. As a marketer, you want to trim costs and increase revenue. Applying AI to your customer segmentation can help you optimize your marketing channels.
For help in planning your data strategy, or for more information on anything in this article, please contact the author, Dr Andrée Bates, at Eularis: http://www.eularis.com.