How the data is analyzed and visualized for Tradeoff Ranking?

How the data is analyzed and visualized for Tradeoff Ranking?

How Tradeoff Ranking works?

Tradeoff Ranking is mainly used to test the attractiveness and competitiveness of different ideas, including concepts, messages, logos, features and other stimulus materials. It explores further why the customers like or dislike the ideas so that users can understand from their customers’ perspectives and iterate their ideas accordingly.

Tradeoff Ranking consists of three parts.

  • The first part asks the participants to rate if they like or dislike the idea presented in a series of popup cards. 
  • The second part asks the participant to make head-to-head comparisons among the ideas that they liked in the first part until we identify the one that the person liked the most (i.e. the Top Choice). 
  • The third part includes two follow-up open-ended questions as to why they like or dislike the idea.

Please see more details about What is Tradeoff Ranking and how to set it up here.

How the data is analyzed and visualized for Tradeoff Ranking

On the dashboard REPORT PAGE, users can see a visualization like the following screenshot for Tradeoff Ranking. 

The results displayed in the left section include the quantitative outputs from the first and second exercises of the Tradeoff Ranking question.

  • Firstly, we show an Overall Score beside each idea (in this example the overall score is 24 for Tesla which is the highest from the list). The score is calculated based on both absolute liking from the first exercise and the competitive advantages from the second exercise. The score itself is unimportant, what we need to pay attention to is the ranking – highest to lowest – and the gap in scores between the ideas.
  • In addition, we show a detailed chart including % of Top choices, Like, Not sure and Dislike for each idea.

 

The section on the right includes detailed verbatim from the third part of the Tradeoff Ranking question. You may click on any idea to see the verbatim of why people like or dislike this idea. In the following example, we can see why people like or dislike Tesla after clicking Tesla.


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