Brand strength survey: analyzing perceptions

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In previous posts I explained how to build a brand strength survey using audience questions and perception questions, and how to then distribute your survey using Survey Monkey. After you conduct your survey, you’ll have both audience and perception responses. With this data set, you can ask a wide array of questions about the audience that you surveyed.

Survey Monkey does include built-in data analysis tools. These are fine for smaller surveys and smaller data sets. I prefer using Microsoft Excel for data analysis. Survey Monkey easily exports data in Excel format.

Some questions can be purely about the characteristics of your audience and their perceptions,such as

  • What level of education does my audience possess?
  • What types of media does my audience pay attention to?
  • What percentage of my audience has a favorable impression of my product?

Other questions will look at the interaction between audience characteristics and perceptions, such as

  • Does product usage vary according to age, gender, income, location, or other variables?
  • Does perception of my brand vary according to education, usage, media consumption, or other variables?

Both of these categories of data can be illuminating.

You can also create a third category of data by grouping your survey respondents according to their perceptions.

One way is to analyze groups of respondents who share the same perceptions. For instance, how do all those who have a very favorable impression of your public health agency compare in age, income, location? You can look at the audience responses and the perception responses of just this sub-group, to better understand them.

Another way is to calculate and assign a brand score to each survey response. Here’s how:

  • Determine point values for the answers to perception questions. For instance, you might assign two points for the most favorable response to a perception question, and one point to the next most favorable response.
  • Score the individual survey responses based on your point values.
  • Add up the point values for each survey response. If you asked five perception questions about unaided recall, aided recall, reputation, knowledge, and usage, and if each of those five questions had a maximum value of two points, then each survey response could score from 0 to 10 points.
  • Group brand scores into meaningful cohorts. If responses could score up to 10 points, you might group responses for zero points, 1-3 points, 4-6 points, 7-9 points, and 10 points.

Once you have responses grouped by brand scores, you can look at each of those groups as another audience subset. For instance, what do all those who scored 10 points have in common in terms of education, income, location, or other factors?

You can also analyze the variations from one brand score group to the next. For instance, how does media consumption vary between the different brand score groups? Are there discernible patterns as you move up the brand scale you’ve established?

Using the Pivot Table feature in Excel makes it very simple to aggregate various types of data. Pivot tables let you drag and drop types of data to create the tables you need. Of course, you can display your tabular data as charts in Excel as well.

This post gives you the big picture of the types of analysis you can do with audience and perception questions in a brand strength survey. If and when you undertake a survey like this for your organization, you’re bound to have questions. Allow time in your project schedule to answer those questions through additional research or interactions with support personnel within your organization or at companies such as Survey Monkey and Microsoft.

Also, I’d be happy to answer questions you might have about the specifics of your brand strength survey. Just fill out my contact form–that’s probably the easiest way to reach me.

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