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[Product and Program Optimization ]

railroad tracksMany management problems center on optimization decisions – tough choices that may also involve considerable risk.  Smart survey research powered by advanced analytics is ideally suited to answering questions such as:

  • which product to launch
  • how to design a new product or clinical trial to give the best chance of success
  • what promotional offers will drive trial
  • which SKUs to discontinue

Knowledge Networks helps clients launch new products and services by applying optimization models that can zone in on the best-case scenarios, including product and pricing configurations. Our rigorous design and analytical expertise are matched by an understanding of clients’ business challenges. 

With KN’s help, you can obtain clear, action-oriented answers to challenges such as:

  • pricing a new product introduction to minimize cannibalization and maximize volume draw from competitors
  • identifying the clinical endpoints that will optimize uptake for a new drug (in some cases using our proprietary patient chart studies – MD-diary® – to feed our models)
  • optimizing the features of a program to drive trial, retention and compliance
  • line and flavor optimization – both extensions and pruning
  • determining the bundles of claims that are most convincing across a variety of target segments
  • estimating the impact of a new entrant on existing market share

Introducing analytics at the design stage – KN's Perspective >>

KN in-house Advanced Analytics team has an early and visible role in partnering with our clients to determine the best designs and modeling methodologies. In fact, we actively involve our modelers at the design stages before any modeling actually takes place. We frequently use discrete choice and conjoint modeling to inform product and service configurations, resulting in easy-to-use simulators that allow clients to evaluate any number of scenarios. 

Discrete Choice vs. Conjoint

Discrete Choice models directly measure preferences, by assessing the trade-offs made between different product or drug attributes, or benefits made in the context of a purchase or ethics decision, as measured by a "utility score." In a conjoint analysis, consumers are asked to evaluate a series of hypothetical and/or real products, defined in terms of their features. From their responses, the relative value of each feature is isolated. Adaptive conjoint is an approach that Knowledge Networks can employ to make it easier to test an even larger number of attributes/levels.

We also partner with consulting firms that use our optimization tools to feed into market forecasts.

 

FEATURED INSIGHTS

For more information, contact:

CPG:
Audrey Rosen
646 742-5323
Email

Pharma/Health Care:
Stephan Benzekri
646 742-5316
Email

Fact Sheet

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