TURF Analysis

The TURF Analysis applet allows users to score checkbox questions and MaxDiff exercises to identify the best combination of products, flavors, or other varieties, not just the best-performing individual ones.

What is TURF?

TURF stands for "Total Unduplicated Reach and Frequency." Originating from the media planning world, but since having been adopted by the market research industry, the initial goal of TURF was two-fold - to maximize reach (the percent of the target audience that sees at least one ad) and to maximize frequency (the average number of exposures, or number of times, an ad is seen by a member of the target audience). In market research, the focus is more on maximizing the "reach" of a product line (i.e., what percent of customers would buy any of the items in the line), especially in the case of attempting to expand the options in a particular product line. In this situation, TURF examines how adding one or more new product options can increase the number of potential customers "reached" by the product line, assuming that not all of the newly proposed options will be kept. Frequency, i.e., the average number of portfolio items customers would buy, is often used as a tiebreaker between combinations with the same reach.

As an example, think of ice cream flavors. An ice cream company can only offer so many flavors based on production, shelf space, etc.. If they conduct a survey that asks potential customers what flavors they purchase most often, they could potentially have results like this. 

Just looking at the percentages, you might recommend Item 1, Item 6, and Item 5 (with Item 8 as the fourth, if needed).

But what if those top three items are Chocolate, Chocolate Chip Cookie Dough, and Cookies & Cream? If a company chose those three flavors, they wouldn’t be able to sell any ice cream to people who don’t like chocolate, have chocolate allergies, love other flavors, etc. While chocolate lovers will have multiple options, they won’t necessarily purchase more ice cream to make up for the consumers that are alienated by the "choco-centric" assortment.

Instead, a TURF analysis identifies what combination of flavors maximizes reach, i.e., how to get the most people to buy any of your options. Results would likely recommend an assortment of flavors to fit different consumers’ preferences.

Although there is no technical minimum to run a TURF analysis so long as there is more than one complete, it is recommended to have a minimum of 100 respondents for a TURF analysis (the more, the better). Also, it is best to run any analysis after data collection is complete.

When to perform a TURF analysis

TURF might be the right analysis when you hear these key terms:

• Combination – When clients are interested not just in the highest performing option(s), but those that work best together in market/on shelf. Note that not all combination questions are a fit for TURF, though; for example, TURF is often not recommended for marketing messages or features within a single product (see below).
• Portfolio Strategy – TURF use cases include situations where product assortment is constrained by shelf space, portfolio rationalization (i.e., removing underperforming portfolio items or varieties), or line extensions (e.g., which varieties to add to existing products in market). TURF can answer both how many varieties to go to market with (i.e., at what number reach starts to plateau), as well as which ones make the optimal combination. It can also reveal the incremental reach of introducing each new variety (i.e., the additional share your brand will attract beyond what it already owns).
• Cannibalization – TURF can be used to determine whether a new product or line extension will attract new customers or just steal consumers of your own current products.

 

When to potentially not to use TURF:

• Marketing messages – While TURF originated in the marketing space, as it is currently used, it may not be a fit for marketing use cases. If messages cannot be targeted to the appropriate consumers, they may potentially see more than one message identified by TURF analysis, including one(s) that do not resonate with them personally, potentially counteracting their preferred message(s).
• Features within a product – When consumers purchase a product, they are purchasing all the features – they cannot pick and choose the way they can with flavors or varieties. Thus, if a product includes lower-performing features, it could alienate consumers and discourage purchase rather than attracting different consumers who prefer different features. This is a better use case for conjoint analysis.

Performing a TURF analysis

To access the TURF Analysis applet, expand the Analytics button group and select TURF Analysis.

The TURF Analysis applet is similar to other reporting applets in that it uses the Record Selector to specify which records to include (defaulting to Completed records) and the Field Selector to specify which field to include. TURF can only analyze one question at a time. Additionally, only multi-select question types/variables and MaxDiff questions may be analyzed. However, additional question types such as ranking questions could be used for TURF if they are reprogrammed into a multi-select variable.

TURF for checkbox questions

To start, set your filters and apply weights the way you would for any other reports being ran for the study and choose the question from the Field dropdown. The platform should only list eligible questions for TURF analysis. After specifying which records and field to include, click Next to continue. 

If any records have missing data, the user will be prompted to select how to deal with these records. Users may elect to exclude these records (default) or to assign a "0" for the missing values. Whether or not to exclude these records depends on the wording of the question and survey logic. For some, blank means "not seen," but for others, blank means "did not select this item based on previous survey answers," so the researcher can make this decision based on their interpretation of the data. After making a selection, click Next to continue.

 

On the next screen, users will be prompted to indicate the Number of items to include in each portfolio. Portfolios are groupings of items which TURF is asked to analyze in order to maximize the reach within the population. Users may specify a single value (e.g., "3") or a range of values (e.g., "3-5" or "3:5"). A single value indicates to examine the reach with the specified number of items (e.g., 3), whereas a range indicates to make separate analyses for each number of items specified. For example, if the range "3-5" is specified, reach will be calculated for a portfolio of 3 items, then 4 items, and lastly 5 items.

Note that the minimum number of items is 2, while the maximum is one less than the total number of items. If you want the reach of 1 item, you can simply refer to the percent it was selected in a Topline report or Frequency report.

Users should provide a name or description to identify the analysis in the Name this calculation field, then click Next to continue.

 

The final screen will show the results of the calculation. Using the example above (3-5 items), you will see the top combination selected for each portfolio with its respective reach, frequency, and the items selected in the groupings. In this example, the best reach for a portfolio of 3 items is 0.68 (68% of the population), and the optimal items to include are 2, 3, and 8. These are indicated below with a value of "1". Yet, if we increase the portfolio to 4 items, we increase our reach to 0.77, and we would incorporate item 1 to the group. Lastly, increasing the portfolio to 5 items would grow the reach to 0.84, and we would add item 4 to the group.

From here, users may create a new TURF analysis by clicking the Back button, or download an Excel version of the report's results by clicking the Export button in the upper right-hand corner. To see all combinations of items and their respective reach and frequency, export the report. Note that calculations can take time to process if there are a large number of items or combinations.

 

The first tab of the Excel output provides details on the analysis, including a key for which options the item numbers indicate. It also provides a similar data table as the platform, showing reach, delta, frequency, and composition of the top combination by portfolio size.

The Excel output will also include tabs for each portfolio size included in the analysis. These tabs list out every combination for the portfolio in order of best reach followed by best frequency. Reach is rounded to the nearest hundredth decimal point for reporting purposes, however, the full decimal string is considered when ordering the combinations from greatest to least.

 

Continuing with the example above in which we ran a TURF analysis for 3 portfolios which consisted of 3 items, 4 items, and 5 items, these 3 portfolios will each have a tab named "3 Items," "4 Items," and "5 Items," respectively. The results of each portfolio show the best combination in the first row, with the reach, frequency and items to include flagged with a value of "1". Combinations are ordered by highest reach, with frequency as a tiebreaker (note that the Combo column simply assigns each combination a number for reference and does not factor into the results.) The data from the top combination in each tab should match the data for that portfolio size on the summary tab.

Portfolio of 3 Items in detail (first 3 rows):

 

Portfolio of 4 Items in detail (first 3 rows):

 

Portfolio of 5 Items in detail (first 3 rows):

TURF for MaxDiff questions

TURF analysis for MaxDiff questions begins in a similar fashion as scoring checkbox questions, with the relevant questions available in the Field dropdown. As with multi-select questions, the Record Selector will allow users to apply filters and weights as needed.

To perform a TURF analysis on a MaxDiff question, first make sure the question has been scored via the MCMC applet.  

 

After selecting which question to score, users will be prompted on the next screen to select a Reach Assessment Technique. Options include Threshold, First Choice, or Top Two. These options refer to which items the calculations count as "reached" based on MaxDiff utility scores.

Threshold 

The Threshold reach assessment technique recodes MaxDiff utilities into binary values, with those above the threshold counting as "1", or "reached," and below the threshold as "0", or "not reached." The calculations will depend on the threshold chosen. A good starting point for a threshold is 2 – 3 times the average utility (i.e., if utility were evenly divided among all options). Try to find a level where reach numbers are useful. If the reach numbers are too high or low, (e.g., everything is 98%+ or <5% reach), there is little to differentiate results, and the numbers will not reflect actual market behaviors (e.g., more than 5% of respondents probably buy ice cream).

Comparing this to the Descriptive Statistics section shown in the platform is a good first step to see what level might be appropriate. Users should note that a threshold above the maximum for too many items could result in not enough items being counted as "reached" for analysis.

Once a threshold is entered, click on Compute at this threshold or simply hit the Enter key. Then, additional Descriptive Statistics recalculated at the threshold specified will be shown for reference.

First Choice

First Choice only counts an item as "reached" for a given respondent if the item has the highest utility score. This approach makes less efficient use of the granular preference information provided by a MaxDiff, so small changes to the data have relatively more impact on the rank-order of the outcomes. However, a simple "Top choice" may be the easiest to interpret and describe compared to the MaxDiff utility scores, and it may be all the client needs.

Top Two

Top Two counts an item as "reached" if it has one of the given respondent's two highest utility scores.

From this point, the process matches the earlier flow shown for analyzing checkbox questions. The data output for MaxDiff indicates the threshold used on the summary page, otherwise TURF analysis for checkbox questions and MaxDiff is the same.

What else TURF analysis involves

Clients may use TURF outputs in different ways. First of all, clients might have parameters for their portfolio; for instance, they must retain two existing varieties. This is also called "forcing" or "pinning" items to a portfolio. This can be easily accomplished with Excel filters.

 

One important question might be to identify optimal portfolio size, i.e., the level at which reach plateaus. Plotting the data from the first Excel output tab should show the portfolio size where incremental reach is too low to justify an additional variety. While there is no clear threshold, typically you might see an inflection point where reach delta falls into the low single digits. In the example below, we might recommend a bundle size of 4, since a fifth variety only adds ~3% reach.