Whether you’re looking to add a new product to your product mix, rationalize your service offering, or tweak your messaging approach, a TURF analysis is critical to understanding how those potential changes will affect your business’ performance in the market. By testing the impact of different combinations of products, services, and messages on consumer reach and purchasing frequency, businesses are empowered with the data they need to make confident, successful adjustments to their offering that are guaranteed to boost sales and capture market share.
In this article, we take a closer look at TURF analysis, including what it is, how it works, and how it can be applied to real-world scenarios to supercharge strategic decision-making.
Let’s dive in!
A TURF analysis, or Total Unduplicated Reach and Frequency analysis, is a statistical methodology applied to consumer market research data to determine the optimal combination of products, services, features, and messaging that will appeal to the greatest number of unique customers while minimizing redundancy. Using TURF analysis, companies can optimize their product mix to ensure it appeals to the maximum number of potential customers, driving the maximum number of possible sales across the range.
It is important to note that in the vast majority of market research applications, the approach being used is more akin to “TUR” analysis, since the project objectives typically have an optimization focus and the “F” (Frequency) is often handled, when needed, in later stages of research including volume forecasting.
In practice, one of the things a TURF analysis may reveal is that customers are happy to replace a mandarin juice option with an orange juice option, but are unlikely to buy both. In this instance, having both mandarin juice and orange juice in the range is redundant. Removing mandarin juice and replacing it with a juice that customers are likely to buy in addition to orange juice – apple juice, for example – will drive more sales, while possibly appealing to a wider customer base.
Let’s take a look at another example.
This diagram shows the reach of three different products. The business in question wants to know which two products will deliver the maximum reach in combination. At first glance, it appears that products A and B, when added together, would deliver the most reach, at 73%. A TURF analysis reveals that, in reality, there is a significant overlap of demand between products A and B. This means that the same consumers want both products (duplicate reach), and that they are likely to make an either-or choice between them. Having both A and B creates redundancy – marketing one may cannibalize the consumer base of the other, and the combination is not going to attract new consumers to the brand – and the combination of product A and product C is the better path to take, as it should maximize both reach and demand.