When you don't know what you don't know.

Regardless of what sector you’re working in, what product or service you're offering, at some point in developing your marketing strategy you're going to have to figure out what is it that your end-user is valuing about your offering. How do you go about figuring that out, figuring out what you don't know when you don't know it? What is the scope that that can encompass? This is a challenge that's faced by almost all our clients, at some point.

In the past, the options clients had were this trade-off between going the quantitative rout or the qualitative rout.

The quantitative rout is scalable and means you can talk to a lot of people, across segments and markets. But, the challenge with the traditional quantitative approach is that the structure requires you to decide what you think might be important to your audience. You put your choices in front of them, but you can only get feedback on those specific factors. The problem is that you miss attributes and risk making inaccurate decisions.

The other option is to go the qualitative rout. The benefit of qualitative, of course, is that it can be more open ended, so there’s not as much of a risk of missing the most important attributes. But, we still have to remember that we have interviewers who are conducting that qualitative research and their own biases and expectations are still going to direct the conversation and direct the insights. Assuming you have perfectly objective moderators (and that’s not going to happen) the other challenge is that, when you’re doing qualitative, it’s not quite scalable. The risk here becomes you have to extrapolate the really small sample size to your larger audience and, again, this is a risky way to make business decisions.

Some innovations in this space are scalable qual but the problem isn’t quite resolved yet, and the reason for that is, whether we’re talking about the scalable qual or traditional qual or quant, they are still resting on explicit measures. Directly asking people “what is it that you value?” “what’s important to you about this offering?” And what we know from Behavioral Science is it’s not very easy for people to 1) access what’s actually important to them and/or 2) actually communicate that to us.

To tackle the problem we’ve developed the Attribute Elicitation Task. This method is scalable, so we don’t have to risk extrapolating from small to large markets. It’s structured in terms of the task, which means we don’t have the risk of the interviewer directing or biasing the research, but it’s open-ended in terms of the responses we get back. What this means is respondents are able to tell us what’s important to them. And, finally, we use an implicit measure that gets over the traditional rationalizations we get when we’re using direct line inquiry.

This method operationalized in four stages. In the first, all we do is present them with three products (what we call triplet sets) and ask them to decide which two are similar, what makes them similar, and how the third one is different from the other two. As you can see, there is structure here and there’s no value judgment. We’re not asking them “what’s most important to you?” or “what’s driving your decision making?” Instead, we get the answer from this implicit measure of just seeing how they’re naturally categorizing.

Because this is completely open-ended, there are a tone of different ways respondents can put these together, based on whatever attributes are important to them. Once we figure out what that attribute set is, by giving them a bunch of these triplet sets, we then ask them to explicitly tell us which one of those are important to them. But we don’t just take their answers at face value, we analyze how often an attribute came up and how quickly they answered paired with their explicit responses.

Once we know what’s important to them, we then have respondents benchmark how the brand/product/offering is fairing on these attributes, compared with competitors and compared with an ideal. This allows us to measure how the brand/product/offering is performing, how it’s performing relative to competitors and oftentimes also highlights where the whitespace is. Once respondents have completed this task the output is this grid.


We essentially have a list of attributes that are important, relative to your product, and we know how you’re delivering, or not, on those attributes. With the attributes plotted, you have a principled understanding of where to invest.

Many of our clients, across a wide range of industries, have benefited from the AET. If you would like to learn more, give us a shout!

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