Within the marketing world, TURF (which attempts to optimize a line by maximizing
the number of consumers who would find their favorite items in the line) has long been the "default" method for making product line decisions.  While TURF can be adequate for identifying the total number of items for a product line, it often falls short as the best tool for identifying which specific items should be included.
 
GRP developed PowerLine to overcome limitations often seen with traditional TURF analysis for product line decisions.  While TURF focuses only on number of people "reached" by a product line, PowerLine takes a multidimensional approach and examines both breadth and depth of appeal for alternative product lines, in addition to other key diagnostics.
 
While total market "reach" (penetration) for the product line is an important consideration, PowerLine shifts the primary focus of the analysis to which product line produces the greatest share of category volume for the brand overall, while keeping one eye on total number of customers reached by the full line.  The ultimate goal is to find the set of products (or flavors or items, etc.) that provide the greatest share (and thus revenue) potential, with the fewest items possible, and at an acceptable level of market penetration for the line.
 
In the above example, it can be seen that going to a seven flavor line provides incremental share, but little improvement in total number of customers reached by the line.  With this kind of information, marketing managers can make a much more informed decision as to whether or not the incremental share of volume gained is likely worth the cost of carrying the seventh flavor in the line.   It may well be worth the extra investment because of the additional business potential, but if this decision was being made only on "reach," then the seventh flavor would most likely not be considered.
 
 
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PowerLine™ - Product Line Optimization Beyond TURF
PowerLine™ - Conjoint/Choice Modeling Approach
 
PowerLine is especially powerful when combined with output from conjoint or discrete choice modeling.  In this situation, there can literally be millions of potential product configurations, and tens of millions of alternative product lines/portfolios of various sizes.  The PowerLine simulator provides key information for the following product design and product line decisions:
 
-Optimal Single Product Profile.  Across all specific product features such as brand, price, package size, color, performance, etc., what is the single best combination of features to maximize share, revenue, or profitability?
 
- Optimal Multi-Product Line/Portfolio.  In addition to the "best" overall product, which additional products should be produced in order to maximize share, revenue, or profitability?
 
-Retail SKU Optimization.  For retailers, which brands should be carried, how can we "right size" the variety of product choices within a given category in order to maximize store or website visits, revenue or profits?