How does a TURF analysis work?


TURF (Total Unduplicated Reach and Frequency) is considered the standard procedure for determining optimal product combinations and provides insights into:

  • Identification of an optimal product portfolio, i.e. optimization of the product composition / product line and size of the portfolio.
  • Identifying optimal product combinations that reach the largest possible number of consumers (Unduplicated Reach).
  • Which product combination generates the highest sales numbers.
  • Avoiding sales losses by taking out-of-stock situations into account (Shapley Value approach).

By enhancing the TURF analysis with purchase frequencies, purchase reasons and socio-demographic characteristics of the respondents, detailed statements can be made about purchasing behavior.


Thus, not only can the product line with the maximum reach be identified, but insights can also be gained for optimizing product lines for different sales channels, buying situations, and revenue and profit targets.



An example:


Imagine you have 7 different varieties of chocolate (e.g. whole milk, dark, nougat, white chocolate etc.) and need to identify those 5 varieties that combined would reach the biggest number of buyers (Unduplicated Reach).


Indeed this set does not necessarily have to comprise of the five varieties that – considered separately – have the highest share of buyers (as measured with Top-2 Boxes in purchase intention, for example), i.e. A+B+C+D+E…


…instead a better set would be made up with A+B+C+D+F, because the TURF-Analysis proves that buyers of B and E are identical customers, for the most part, while variety F reaches other, additional buyers.


The TURF-Analysis delivers the net share of all buyers for each possible set of 5 chocolate varieties. This makes it possible to quickly identify the combination that promises the biggest total number of buyers that can be reached.


In addition to the above data TURF will also determine the ideal number of varieties that should be included in the sales mix in order to achieve maximum reach. Thus it would be possible that 3 or max. 4 varieties in the sales mix would be enough to reach the biggest buyer share and that any additional variety would not reach a worthwhile number of additional buyers.


Moreover, it is possible to calculate scenarios with a smaller or bigger number of varieties, with or without specific varieties (e.g. an already existing product or a competitor product).


Simple and transparent query:


Respondents are asked to give their purchase intention for all researched alternatives. This can be done in a binary mode (would buy/ would not buy) are in scaled mode (“I would buy definitely” to “I would definitely not buy”). The resulting data will be used to determine reach. In order to predict sellable numbers of products respondents will be asked how often or in which quantities they will buy accepted varieties.


Since the question style is very simple it is feasible to use all of the usual survey channels (mobile at the POS or online).


Identify the product line with the maximum reach, optimized by sales channel, buying situations, revenue and profit targets using TURF analysis.