3 Survey Analysis Techniques for Ad Concept Testing

Ad concept testing is a critical part of any serious marketing campaign. 

If you’re going to make a big investment to run new ads, consider a much smaller investment in marketing and advertising research first. Doing so ensures confidence in your marketing strategy. 

While conducting marketing research is important, the survey analysis is just as critical to ensuring you are relying on quality data. 

In this post, I’ll cover three excellent techniques for ad concept testing analysis. Each of these options will get you one step closer to optimizing your ad campaign.

Rather watch a video? See an overview of these three ad concept analysis techniques below.

The Importance of Proper Ad Concept Testing

Once you make the wise decision to test your ads before a campaign launch, be sure to also do it right. Don’t settle for simple and informal ad testing.

This is especially true if your company or client has plenty at stake with the campaign. If you are thinking about hiring a marketing agency for ad concept testing, be sure to also read this first.

The first approach that may come to mind for ad concept testing is a head-to-head comparison or “A/B testing” of the ads you are considering.

Perhaps you show some of your target audience a collection of the ads to test and ask them to pick their favorite. Or running both of the ads for a few days to see which offers the better return. 

Would this give a quick answer for your campaign? Yes, but at a serious cost: oversimplifying the decision.

The Benefit to You:
A full ad concept testing survey is a better solution that can give you the key context and details about each individual ad and how they compare to one another.

You can expect to understand
why respondents like or dislike certain ads.

This information is invaluable when you consider that each ad may be more effective with a different segment of your target audience.

The resulting research may guide you to target different audiences for each ad, revisit the design of an ad, or scrap a poor ad altogether.

In any case, ad concept testing helps you make a better business decision and can save you significant money from running an inefficient ad campaign.

If you are looking to learn everything you possibly can about this topic, be sure to bookmark and read the ultimate guide to ad concept testing surveys

Survey Analysis Technique #1: Heat Maps

A heat map analysis can be a powerful tool for testing still ads. Instead of just having a respondent tell you they like or dislike your ad, you see what parts they like and how much.

Here’s how it works - a survey question displays the image of your ad and respondents are asked to select points of interest.

They can indicate whether they like or dislike the point, then leave a comment to provide context.

The end result for reporting is an image of the ad with a layover plotting all respondent selections.

Frequently selected areas are warm colors (red, orange, yellow), and infrequently selected areas are cool colors (purple, blue, green).

See some great examples of heat map survey questions in this post

example of a heat map

This visualization gives you a quick understanding of which ad components were appealing (or unappealing) to your target audience.

For the reasoning behind respondent selections, it is often worth diving into the individual comments. The comments especially come in handy when an area of the ad receives a similar amount of likes and dislikes.

This technique instantly proves its worth if you learn that only one or two elements of your advertisement need to be adjusted instead of the whole image.

It provides helpful direction and takes the guesswork out of what exactly needs changing for success.

Need some help designing your survey first? Read these five steps to conducting an ad concept testing survey.

Analysis Technique #2: TURF Analysis

Another useful technique in an ad concept testing survey is TURF analysis.

No, this isn’t the turf you might find on a football field (although turf fields could be the subject of a TURF analysis). 

What is TURF analysis?

Broadly speaking, this technique tells you how to reach the maximum amount of people with limited space for offerings. To explain it a little better, let’s look at an example within an ad concept testing analysis.

Example of Using TURF Analysis for Ad Concept Testing
Pretend your company or client has developed five unique still advertisements for an upcoming campaign.

They all hit on the same underlying message in different ways, and you know each one is at least somewhat appealing to your target audience.

You only have the budget to run three of the five ads, so you need to understand which combination of three will appeal to the highest total percentage of your target audience.

Before you can conduct a TURF analysis, you need to ask a multiple-response question in your ad concept testing survey.

In our example above, you may ask respondents to select all displayed ads that they find most appealing or give them a positive impression.

On the back end, TURF analysis will evaluate all possible combinations of three ads from the tested five to see which one gets you closest to 100% of respondents. 

It is worth noting, however, that you may not always receive a clear-cut answer in the end. This could occur because multiple unique combinations of ads have the same total reach.

Even if there is no obvious winning combination, the results will still assist you in making an informed decision on which ads are worth using.

example of TURF analysis

Analysis Technique #3: Text Analysis 

Sometimes the best way to capture insight in an ad concept testing analysis is to hear from your target audience in their own words.

This is often done through open-ended questions in your survey where a respondent can elaborate on their rationale and thoughts behind an answer.

The trouble is, not every researcher has the time and human resources to read every single response or hand-code responses into buckets for analysis.

This is where the text analysis technique shines.

What is text analysis?

Text analysis uses automation and sometimes artificial intelligence to efficiently and effectively find the main topics in your open-ended questions.

The process groups respondents’ answers based on similar keywords, synonyms, and other contexts.

The Benefit to You:
The goal is to walk away with a list of the top themes or topics in the responses to see what is really driving respondents.

You can even analyze other key metrics in the ad concept testing survey by text analysis topic.

This additional layer of analysis may tell you which topics are associated with a higher willingness to purchase your product, for example.

When the frequency of topics is not enough, you can also look at sentiment.

Using assigned values for nearly every English word, a net positive, neutral, or negative sentiment can be calculated for a respondent’s answer. 

From here, you can assess what percentage of answers for a topic was positive, neutral, or negative as a whole.

This may reveal which individual topics around a tested ad elicit positive reactions or negative reactions.

Your company or client can then focus on leveraging the positive topics and minimizing the negative ones for better ads.

If you still aren’t quite sold on the research, read about six unique benefits of ad concept testing with surveys.

Conduct Ad Concept Testing with Drive Research

Drive Research is a national market research company specializing in ad concept testing. We partner with brands across the country to design, program, field and analyze ad concept testing surveys.

To learn more about our services, contact our team today!

  1. Message us on our website
  2. Email us at info@driveresearch.com
  3. Call us at 888-725-DATA
  4. Text us at 315-303-2040

tim gell - about the author

Tim Gell

As a Research Analyst, Tim is involved in every stage of a market research project for our clients. He first developed an interest in market research while studying at Binghamton University based on its marriage of business, statistics, and psychology.

Learn more about Tim, here.

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