TURF

TURF Analysis Simulator

Conjointly provides the ability to conduct TURF analysis on data from any of your experiments or a custom dataset of your own. TURF stands for Total Unduplicated Reach and Frequency. It is a technique that came into prominence during the 1950s in the space of media planning and is used extensively in range optimisation. This page guides you how to use Conjointly’s modern TURF analysis tool – the best and easiest such tool in existence that helps you digest and check your data and even prepare PowerPoint presentations of your findings:

Key outputs

Top combinations of items in TURF analysis

Top combinations

Top combinations will give you the combinations of items that provide the highest reach. You can change the number of items in each combination by adjusting the Number of items in combination slider.
Prioritised sequence of combinations (ladder) in TURF analysis

Prioritised sequence of launching SKUs (the ladder)

This output provides you the top combination for incrementally increasing number of options in each combination. This means the first row will give the item with the highest reach, the second row will give the combination of two items with the highest reach, and so on.
Easily calculate reach and frequency in TURF analysis

Simulate scenarios

This output will calculate the reach and frequency of custom combinations of items. Use this output if you already have one or more scenarios in mind and want to look at their performance.
Easily see correlations in TURF analysis

Correlations

This output displays the correlations of scores between each item. Correlations are a measure of how similar the scores between two sets of items are. Items that are both preferred and strongly negatively correlated with each other will appeal to different groups of respondents, and tend to be included in the same combinations to maximise reach.
Easily see reach of individual items separately in TURF analysis

Table of reach by item

This output displays which respondents are activated by which item. Cells that are highlighted green represents items that are considered active for that respondent. The criterion for activated items depends on the reach method and threshold chosen as described below.
Easily see score metrics for each item individually in TURF analysis

Performance of each item separately

This output displays score metrics for each item individually, such as the mean, the standard deviation, the rank of the item by mean score, and reach. Use this output for a quick summary of the performance of individual items.
Easily export results of TURF analysis into PowerPoint and Excel

Exports into PowerPoint and Excel

There are multiple ways to export outputs:
  • You can export the output of all tabs into either Excel or Powerpoint by clicking on the Export into Excel or Export into PowerPoint button.
  • Alternatively, you can export tabs individually using the CSV button at the bottom.
  • Clicking on Copy will copy the data into your clipboard so you can paste it into the program of your choice.


How to access the TURF Analysis Simulator

Method 1: Access the tool using data from your experiment

Certain outputs in Conjointly experiments will allow you to go to the TURF analysis tool with the data from that experiment preloaded. Look for the Run TURF button on the top right corner of the output panel. Conjointly outputs that can be used to run TURF include:

It is not available for Brand-Price Trade-Off preference scores.

Method 2: Upload your own dataset

When you open the TURF analysis tool, you will see three preloaded example datasets. To upload a custom dataset into the app, click on the Upload a new dataset button:

The dataset should be in a .csv file where each row represents a respondent and each column represents an item ( Example dataset).

If you want to use weighting for your dataset, ensure that one of the columns is called weights and all its values are between 0 and 1.

TURF analysis simulator settings

You can adjust the number of items to include in combinations tested by moving the slider:

As different data sources will have different representation of how respondents show preference, the TURF analysis tool allows you to choose how respondents are determined to be activated by combinations of items. You can specify how activated respondents are chosen using the Reach method drop down. TURF analysis tool supports these Reach methods:

  • Among top options for a person: respondents are activated by items if the score for that item is in the top N items by score. The number of top options can be set by changing the threshold value. This reach method can be used where higher scores indicate stronger preference for a particular item. For most applications, we recommend using this method, setting N = 1.
  • Among bottom options for a person: respondents are activated by items if the score for those items is among the bottom N items by score. The number of bottom options can be set by changing the threshold value. This reach method should be used with data where lower scores represent higher preferences.
  • Greater than: respondents are activated by items if the score for that item is greater than the threshold value. This reach method can be used with data where scores above a certain value indicate preference.
  • Greater than or equal to: respondents are activated by an item if the score for that item is greater or equal to than the threshold value. This reach method can be used with data where scores above a certain value indicate preference.
  • Equal to: respondents are activated by an item if the score for that item is equal to the threshold value. This reach method is best used when scores of a specific value represents activation, such as data from a multiple choice question.
  • Less than: respondents are activated by items if the score for that item is less than the threshold value. This reach method can be used with data where scores below a certain value indicate preference.
  • Less than or equal: respondents are activated by items if the score for that item is less than or equal to the threshold. This reach method can be used with data where scores below a certain value indicate preference.
  • Utils: Utils calculates the average probability an item in a combination will reach the respondent if placed among a set of other combinations. This reach method is better at considering strong secondary preferences and is best used for utility scores from conjoints and MaxDiffs. It can also be used for any data where the scores are mean centred (the mean is 0). There no frequency value when using the “Utils” method.

You can also modify options such as the threshold the app uses for each of these reach methods by changing the threshold value, force inclusion of certain options or force the exclusion of certain options.

  • Changing the threshold value: This option is only available for certain reach types that uses a threshold value (see section on reach methods). In general, changing this value will affect how many options are activated for each respondent
  • Ensure each combination has at least one high-ranking item: This option will filter combinations so that they always will contain at least one of the top N rated items. You can change how many top items are included in the top items by adjusting the option labelled Specifically, at least one item that is among top
  • Always include all of these: Items selected in this option will always be included in combinations in the output. Use this option when looking for combinations that always include certain items. For example, if an item has already been released and therefore must be included
  • Always exclude all of these: Items selected in this option will never appear in combinations tested in the output. Use this option when looking for combinations that will never include certain options. For example, if an item has been determined to be underperforming

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