Expanding the Pricing Research Toolbox with the Application of a Turf Analysis

Background

- For a company offering multiple variants in its product line (e.g. ice-cream flavors, perfume scents, paint colours, business/health care online forms), its business objective may go beyond estimating preference shares at specific price points. As well, it may want to understand how to best capture the widest customer base given its entire product portfolio.
- To address this additional objective, the “Reach” portion from TURF (i.e. Total Unduplicated Reach & Frequency) is used in tandem with a conjoint analysis.
- This article describes a pricing and value research project that Pricing Solutions Ltd. conducted in this area.

Download the PDF version

Background

For a company offering multiple variants in its product line (e.g. ice-cream flavors, perfume scents, paint colours, business/health care online forms), its business objective may go beyond estimating preference shares at specific price points. As well, it may want to understand how to best capture the widest customer base given its entire product portfolio.
To address this additional objective, the “Reach” portion from TURF (i.e. Total Unduplicated Reach & Frequency) is used in tandem with a conjoint analysis.
This article describes a pricing and value research project that Pricing Solutions Ltd. conducted in this area.

Research Method

Using choice-based conjoint, the questionnaire design and fieldwork followed the established guidelines related to this methodology.
However, the usual conjoint exercise was slightly modified. While systematically varying prices across scenarios, customers were allowed to purchase as many variants as appropriate using a series of check boxes. Of course, the ‘None’ option was made available if customers would rather not buy anything.

Pricing Analysis

In the pricing analysis, individual customer level utilities, not aggregate utilities, were estimated.
With regards to preference shares, either the first choice (“Maximum Utility Rule”) or share of preference method (“Logit Rule”) may be used. For the latter however, an appropriate cut-off point in the preference score was established to identify which among the variants resonated with each customer (i.e. he/she has been “reached” by said item) given a specific price point.

To the right is an example of the resulting market reach for a new product portfolio consisting of multiple flavors and using a 20% premium pricing strategy.
Note that unduplicated reach represents the proportion of customers who are interested in at least one flavor from the line-up at a 20% price premium. On the other hand, incremental reach refers to the additional proportion of customers who would be interested as each additional flavor is added at a 20% price premium.
Essentially, TURF maximizes the reach of the entire portfolio given a specific pricing strategy, not the reach of the individual flavors that make-up the portfolio. To this end, flavors that would appeal to a new/different set of customers are prioritized over those that would cater to the same set of customers.
In the flavor line-up shown above, the flavors are ordered from highest to lowest based on their contribution to the unduplicated market reach of the entire product portfolio. So that those unable to capture new customers are ranked last, although they may individually post stronger acceptance scores than the higher ranked flavors.
The chart also illustrates the variety-seeking behaviour of this target market, which is not particularly strong as there is no longer a substantial gain in unduplicated reach after the 3rd flavor.

Business Implications

By knowing the optimal number of variants, combination of variants, and possibly the ideal launch sequence of variants, TURF helps in budgeting resources as the cost of production can be compared with the benefit gained from having additional new customers.
Cannibalization is minimized with the help of TURF. This is particularly important for companies who have already established a presence in the market, and would like to supplement, not diminish, their existing products.
Lastly, TURF helps identify niche products. The resulting new customer segment tapped, while modest in number, may be strategically important in enhancing market acceptance for the product portfolio as a whole.