shutterstock_271365908.jpgMany pharmaceutical companies have started using customer suggestions to help improve the customer experience. Customer suggestion technologies use data science and technology to identify customer insights and generate recommended actions to take with each customer. With customer suggestions, you can proactively diagnose performance issues with your customers and tailor your communication efforts to match customer preferences and increase engagement.

Several companies have started using customer suggestion tools on the sales side of the business. From the sales perspective, a rep might receive an insight like, “Dr. Smith’s new patient enrollment is up,” along with a recommended action, such as to consider asking Dr. Smith about her patients’ experiences when visiting her office for the first time. Suggestions help sales reps connect the dots. Reps are already trying to filter through a wide variety of data to get customer insights and determine the next action to take. With customer suggestions, this process is faster and more accurate.

While many understand the process for how sales teams use customer suggestions, the process for marketing isn’t as well known. However, there’s a significant opportunity for marketing teams to use customer suggestions to help determine whether to adjust an in-flight campaign to increase customer engagement. Here’s how we’ve seen marketing teams use them:

Step 1: The marketing team designs the campaign or customer journeys using customer insights.

Step 2: Once the team has finalized the strategy, they code the campaign or journeys into a marketing automation platform.

Step 3: Next, they launch the campaigns in the marketplace. While the campaign is in flight, they continuously collect and combine customer engagement data with affinity, performance and other data sets.

Step 4: The suggestion solution captures campaign engagement data and uses data science algorithms to generate customer suggestions.

Step 5: The marketing operations team reviews generated suggestions and determines if recommended adjustments to optimize in-flight campaigns or journeys are appropriate. For example, swapping out one email for another email isn’t a big deal. They cost the same. However, if the suggestion is to use a telesales rep to contact the customer instead of sending an email, that requires governance from the marketing operations team to assess whether you have budget and if the process is set up. After the marketing operations team redeploys the campaign, the process starts over again.

It’s important to think about your marketing process when using customer suggestions. If you buy the tools and capabilities outlined above and develop the strategy to drive the campaigns, but you keep your old process, your results will be subpar. It’s critical that you focus on your process and make it as automated as possible. 


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Three Types of Customer Suggestions

One thing to keep in mind when just starting out with suggestions is that the degree of sophistication of the insights and recommended actions generated can vary based on what you’re ready to do. Many organizations like to start with the least complex, event-driven suggestions that are generated when an event in the customer journey occurs or when a customer performs a specific action, and then move to more advanced, data-science-based suggestions over time. Here are examples of each type of customer suggestion:

  • Event-driven suggestion: A marketer sees that a group of doctors with a strong preference for digital marketing viewed “expedite remission” content online. The marketer receives a recommended action to send an approved efficacy email to this group.
  • Threshold value-based: A marketer sees that a group of doctors has recently switched more patients from competitor brands to her brand and receives a recommended action to invite this group, which hasn’t received an invitation in the last six months, to an upcoming speaker program.
  • Advanced analytics-based: A marketer sees that projected ROI for a campaign is significantly less than the goal, and that the campaign emails have much lower engagement than usual. The suggested action for the marketer is to consider revisiting the subject line and content for the campaign emails.

Each type of suggestion is valuable, but data-science-enabled suggestions provide actionable insight into multiple factors known to influence customer engagement, such as market share, response to promotions and managed care favorability. As a whole, suggestions allow sales and marketing teams to identify important changes in customer behavior and address the right issues with customers before they become a problem.

Accelerate the Delivery of Customer Suggestions

Many of my clients think that getting started with customer suggestions is a lot of work, but it doesn’t have to be. Suggestion solutions with the following five pre-built assets and capabilities can accelerate the delivery of and value provided from these tools:

  1. Suggestions “library” and metrics: Tested insight/action pairs based on key business metrics are typically included in customer suggestion engines and help you get started quickly.
  2. Data infrastructure: Customer suggestions are usually cloud-based solutions that are easy to “plug and play.”
  3. Sophisticated algorithms: These technologies leverage algorithms that are already developed and tested within the pharmaceutical industry, so you can feel confident about using the suggestions generated to adjust your messaging with clients and in campaigns.
  4. Platform integration: Suggestion engines often seamlessly connect with marketing automation and sales force platforms.
  5. Suggestion administration and governance: This is the hardest part of implementing your suggestions capability, but a good change management process and intuitive administrative interfaces can help you effectively utilize customer suggestions for sales and marketing.

You can get started with customer suggestions no matter where your organization currently falls on the customer-centric marketing maturity curve. Now is the time to begin building a long-term strategy for customer engagement.

 

Topics: customer experience, Pete Mehr, customer suggestions