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Case Studies in Patient Incentives

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Three Brands One Offer

A Case Study for Three Brands Needing One Offer

Situation:

A top pharma company had just acquired two new brands which were complimentary to their current brand.  Each brand had its own strategy and a different co-pay discount offer in the form of a co-pay card and an on-line discount coupon.

The brand team had three major issues:

  • They wanted to save deployment funds by finding one offer that would work effectively across their entire three brand franchise.
  • They needed to understand how the brands would perform together as a group and wanted to promote multiple product use by their patients.
  • The brand team wanted a competitive offer but wanted to find the “tipping point” where a further increase in the offer would begin to show a lower ROI.

Our Solution:

  • Alpha 1C produced a unique value added analysis using our unique “Patient Incentive Optimal Offer Model”.
  • We examined the history of each of the brands to be included in the new multiple use strategy.
  • As additional background for the analysis, we met with the brand group and reviewed a series of strategic and tactical brand & market specific issues as well as each brand’s financial information.

Result:

  • Alpha 1C utilized the client specific information and combined it with key performance data from the client’s co-pay vendor to produce a “composite brand” which was a combination of the three brands.
  • We were able to produce a unique simulation model specific to the client’s combined brands and current market situation.
  • The resulting model showed a side by side analysis of  many offer types including “pay no more than”, “save”, “free trial”, ‘zero co-pay” and more including their current in-market offers.
  • The model presented a “mini case study” on each of the scenarios showing all the KPI’s side by side.
  • The model was customized with new features that allowed the brand to change the estimated mix of sales between the three products as well as change the estimates for patients buying multiple brands at the same time.
  • The model’s flexible  simulation capabilities allowed the brand team to run many more patient offer scenarios “on-the-fly” to quickly determine the impact of additional offer variations on brand results.   This simulation capability also allowed the brand team to quickly react to changing market conditions.
  • The brand team was able to utilize the model to find the optimal offer that would best meet the needs of all three brands as well as ensuring the best financial return for the company.

Timing:

  • The Alpha 1C finished the entire analysis in less than two weeks!