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Topography is turnkey solution created to explore a number of entities, such as brands, that can be rated on a list of attributes. This methodology will give you an important understanding of consumers' perceptions of each entities, perceived similarities between them, each entity's most differentiating attributes, and a visual comparison of ratings among the entities in aggregate as well as individually by each attribute.
 


 

Star Rating vs. Sliders

You'll have to choose whether you want respondents to rate each brand with stars (which is the default mode on our platform) or sliders. If you choose to use a star rating, you'll be able to use 5, 7 or 9 stars for each attribute. Choosing sliders will give you more flexibility. You'll be able to choose from our library of pre-written Likert scales, edit the answers, write your own custom answers, and even adjust the scores from 1 to 99, which are provided automatically for you when an answer is chosen. By default we assume 10 points for one star OR the lowest answer on your Likert Scale, and we go all the way up to 50, 70, or 90 for a top rating. If you decide to edit the Likert scale OR adjust the scoring, please make sure you know exactly what you're doing, since it may drastically affect your model and data visualization.

 

 

Grouped by entity vs. Grouped by attribute

The last important decision here is to choose how to group these two lists. By default, we'll group them by entities - or brands, in our example. That means that each brand will be presented as a separate question, with attributes listed as sub-questions below. This grouping may be easier on respondents since it helps them to activate memories of all their experiences with a given brand or entity, enabling respondents to rate each brand or entity by all attributes you're testing.

If you switch to 'group by attribute', each question will ask about one attribute at a time, such as "Food healthiness", and will contain all compared brands on the page. It might introduce a higher cognitive toll on respondents, since they'll have to access a lot more memories across brands in order to answer each of the questions. Even so, in some cases this might be more valuable, since it'll help focus attention on comparing all brands across a given attribute. Please note that this experiment will take as many questions as there are items in the list you're presenting.

 

 

Results

On the Results page, there are several ways to view your results. We use Bayesian Averages (BA) to calculate 

  • Perceptual Map treats each of the attributes you added as a separate dimension or axis in a multidimensional space. It looks for a balance among all the forces and puts your tested entities into specific positions in relation to one another within this space.
  • Topography view is an interactive 3D model of the perceptual map, where score averages are expressed as height—great for visual presentations to represent your data.
  • Quadrant view visualizes the aggregate data on a simple graph to compare entities. Customize your plot view by clicking the respective drop-downs to assign an attribute to the x-axis, y-axis, size of dot, and color of dot.
  • Excel exports contain the raw data for Topography results.

 

Respondent View

 See how this question type looks for respondents

 

In Your Results

 See an example of results

 

Additional Resources