Identify unknown potential with the TURF Analysis

Discovering which product will appeal to the greatest number of customers can be a challenge for any company.

Enter TURF analysis, the Total Unduplicated Reach and Frequency method, which can help businesses identify the ideal product portfolio or marketing mix that will reach the broadest target group. This powerful market research tool provides valuable insights that enable companies to make data-driven decisions and maximize their reach and impact in the market.

In this article, we'll dive into the ins and outs of TURF analysis and show you how to apply it to your business strategy.

What is the TURF Analysis?

TURF Analysis is a powerful way to analyse existing data, originally developed in media research to determine the reach of advertising campaigns.

Using TURF, researchers can identify the optimal combination of channels to reach each person in the target audience at least once (Unduplicated Reach) and how frequently they are exposed to the product or campaign (Frequency).

Initially, the focus of TURF analysis was to increase the efficiency of campaigns without increasing the budget.

However, this method can now be applied to many other areas beyond media planning, such as assortment planning, product portfolio development, and optimisation.

By analysing the metrics of reach and frequency for an entire portfolio, TURF analysis helps answer two critical questions:

1. Which products should be included in my portfolio to reach the largest possible target audience? (Reach)
2. On average, how many products will the target audience purchase from my product portfolio? (Frequency)

Use cases for the TURF method

The TURF Analysis, originally used for media research and planning, is now applied to various fields such as product planning, claim testing, and advertising placement.

This is because the TURF components of Total Unduplicated Reach and Frequency are critical in these areas.

Additionally, TURF considers limiting factors such as budget and limited space, such as on supermarket shelves or packaging.

TURF Analysis is a versatile tool that can answer a range of questions, including:

• Which ice cream varieties should I offer to reach the most customers while providing each person with at least one preferred variety?
  
  
• Can I expand my fruit juice range to attract new customers, and will the costs of launching a new product be justified by the additional revenue?
  
  
• Which product USP should be emphasised on the packaging to appeal to the most customers?
  
  
• Which magazines should I choose for print ads to reach the most customers with a limited budget?
  
  
• Will adding oat milk to a café's product range attract new customers or only cater to the existing customer base?

How to use the TURF method

The Multiple Choice results for the fruit juice example may seem clear, as the flavours of orange, apple, peach, and passion fruit were identified as the most popular choices.

However, since participants can choose multiple options, there could be overlap between groups. For instance, the 64% of participants who prefer orange juice may also prefer the other three flavours. Thus, offering these four flavours alone may only reach 64% of the target group.

To expand the target group, it may be necessary to add a less popular flavour to the range.

This is where the TURF Analysis comes in handy, as it can determine which flavour combination can reach the most customers.

By using the TURF method, it is possible to identify which product portfolio combination has the highest unduplicated reach and frequency, thus maximising the efficiency of the product portfolio.

Evaluating the TURF Analysis results with Appinio

After conducting a TURF analysis, the results are presented in a waterfall diagram which illustrates the percentage of customers that can be reached with additional products.

In the case of the fruit juice example, the analysis showed that offering four different flavours would reach 91% of all customers, with each customer on average liking 2.3 of the varieties offered.

However, the optimal portfolio size must take into account the costs associated with launching a new product.

Adding a fifth variety may only reach an additional 2% of customers, but may not be economically viable as it would not generate enough revenue to cover for the product launch costs.

Now that the optimal portfolio size has been determined, which flavours should be offered?

These tables show the optimal variety combination depending on the portfolio size.

In the case of the fruit juice example, the recommended combination is orange, apple, grapefruit and mango (highlighted in blue on the table).

The table also includes the values for Reach and Frequency.

With this portfolio, 91% of all customers can be reached. Of these, on average everyone likes 2.3 of the varieties offered (Frequency) and will most likely buy several.

Advantages and disadvantages

TURF Analysis has many advantages that make it a popular method for determining sales potential.

Advantages

• The method is flexible and can be applied to a wide range of topics in assortment, category, and media planning.
  
  
• It provides direct calculation of two metrics: frequency (how many products does a customer like on average?) and reach (which products really reach new customers?), making it a useful tool for estimating both sales potential and purchase behavior.
  
  
• TURF Analysis can also help identify cannibalization of products, allowing businesses to optimize their product portfolios.
  
  
• The method is easy to use, and no special question or survey methodology needs to be considered to conduct a TURF Analysis.

Disadvantages

While TURF analysis can be a useful tool for identifying the optimal combination of products or services to reach a target audience, there are several limitations to consider:

• Assumptions about independence
  TURF analysis assumes that the products or services being analyzed are independent of each other, meaning that the introduction of one product or service does not affect the reach or frequency of the others. However, this may not always be the case in reality.
  
  
• Limited view of consumer behaviour
  TURF analysis only considers reach and frequency, and does not take into account other factors that may influence consumer behaviour, such as price, quality, brand loyalty, and product features.
  
  
• Assumes equal importance of all products
  TURF analysis assumes that all products or services being analyzed are equally important to consumers, which may not be true in all cases.
  
  
• Small sample sizes
  It requires a large sample size to ensure accuracy, which may be difficult or expensive to obtain in certain situations.
  
  
• Does not account for external factors
  It does not take into account external factors such as market competition, economic conditions, and cultural differences, which may influence consumer behaviour and product adoption.

Conclusion

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