Ipsos Ideas

Skip Navigation

Not Signed In Your status: not signed in. [ Sign in ] [ Subscribe ]

Appropriate Applications of TURF and Shapley Value for Product Line Optimization

Part one of a two-part series on product line optimization

TURF analysis is often criticized for not clearly pointing to the most optimal product line composition. To provide better solutions, Ipsos-Insight has developed new ways to analyze TURF using measures directly related to marketing. These measures, when employed together, work to increase discrimination among product lines. In addition, changing the conventional parameters linked to TURF based on the business issues at hand also helps produce more actionable results. This paper discusses these new measures and parameters, which constitute a two-level system that greatly improves TURF analysis.

Sign In

Forget Your Password?

e-mail: password:

Remember me

The information you requested is available to members only. Please enter your e-mail and password to gain access to the full article.

GOOD RESEARCH LEADS TO GOOD IDEAS - GOOD IDEAS LEAD TO SMART STRATEGIES

To access the full article you have requested, please create a free membership. With your membership, you will have unlimited access to all of our knowledge resources-white papers, point-of-views, new and archived articles from Ipsos Ideas magazine, and recent Ipsos publications from around the globe- from each of our research specialty practices: advertising, customer loyalty, marketing, public affairs, and forecasting, modeling, and consulting.

In addition, you can choose to receive breaking news, research, and analysis specific to your industry and interests. Member benefits also include invitations to exclusive webinars, local event notification, and more. Sign up is easy, and should only take a moment of your time.

Step 1 of 4: Create your user ID

Become a Subscriber:

EMAIL ADDRESS  

 

Please use your
email address to sign in

PASSWORD  

 

4 to 16 characters

CONFIRM PASSWORD  

 

Retype password
to confirm