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less is moreMarket Researchers are constantly being asked to do “more with less”. Doing so is both practical (budgets and timelines are tight) and smart (the more we ask respondents to do, the less engaged they will be). At TRC we use a variety of ways to accomplish this from basic (eliminate redundancies, limit grids and the use of scales) to advanced (use techniques like Conjoint, Max-Diff and our own Bracket™ to unlock how people make decisions). We are also big believers in using incentives to drive engagement and with more reliable results. That is why a recent article in the Journal of Market Research caught my eye.

The article was about promotional lotteries. The rules tend to be simple, “send in the proof of purchase and we’ll put your name in to a drawing for a brand new car!." The odds of winning are also often very remote which might make some not bother. In theory, you could increase the chances of participation by offering a bunch of consolation prizes (free or discounted product for example). In reality, the opposite is true.

One theory would be that the consolation prizes may not interest the person and thus they are less interested in the contest as a whole.   While this might well be true, the authors (Dengfeng Yan and A.V.Muthukrishnan) found that there was more at work. Consolation prizes offer respondents a means to understand the odds of winning that doesn’t exist without them. Seeing, for example, that you have a one in ten million chance of winning may not really register because you are so focused on the car. But if you are told those odds and also the much better odds of winning the consolation prize you realize right away that at best chances are you will win the consolation prize. Since this prize isn’t likely to be as exciting (for example, an M&M contest might offer a free bag of candy for every 1000 participants), you have less interest in participating.

Since we rely so heavily on incentives to garner participation, it strikes me that these findings are worthy of consideration. A bigger “winner take all” prize drawing might draw in more respondents than paying each respondent a small amount. I can tell you from our own experimentation that this is the case. In some cases we employ a double lottery using our gaming technique Smart Incentives™  tool (including in our new ideation product Idea Mill™ ). In this case, the respondent can win one prize simply by participating and another based on the quality of their answer. Adding the second incentive brings in additional components of gaming (the first being “chance”) by adding a competitive element.

Regardless of this paper, we as an industry should be thinking through how we compensate respondents to maximize engagement.

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We are about to launch a new product called Idea Mill™ which uses a quantitative system to generate ideas and evaluates those ideas all in one step. Our goal was to create a fast and inexpensive means to generate ideas. Since each additional interview we conduct adds cost, we wondered what the ideal number would be.

To determine that we ran a test in which we asked 400 respondents for an idea. Next, we coded the responses into four categories.  

Unique Ideas – Something that no other previous respondent had generated.

Variations on a Theme – An idea that had previously been generated but this time something unique or different was added to it.

Identical – Ideas that didn’t add anything significantly different from what we’d seen before.

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What Does the Fox Say?

Posted by on in Market Research

Nate Silver’s much anticipated (at least by some of us) new venture, launched recently. In his manifesto he describes it as a “data journalism” effort, and for those of us who have followed his work over the last five years – from the use of sabermetrics in baseball analysis through the predictions of presidential politics – there is plenty to look forward to. Apart from the above topics, his website is focusing on other interesting areas such as science, economics and lifestyle, bringing data-driven rigor and simple explanation to the understanding of all these fields. It follows the template of the blog he ran for the New York Times as well his bestselling book, The Signal and the Noise: Why So Many Predictions Fail, But Some Don’t. As a market researcher, I found much to like in the basic framework he has laid out for his effort.

In critiquing traditional journalism, Nate describes a quadrant using two axes – Qualitative versus Quantitative, and Rigorous & Empirical versus Anecdotal & Ad-hoc.

qual quant market researchSource:www.fivethirtyeight.com

He is looking to occupy the mostly open top left quadrant, while arguing that opinion columnists too often occupy the bottom right quadrant and traditional journalism generally occupies the bottom left quadrant. For someone with such a quantitative background he is not dismissing the qualitative side at all. On the contrary, he argues that it is possible to be qualitative and rigorous and empirical, if one is careful about the observations made (and cites examples of journalists such as Ezra Klein, who occupy the top right quadrant).

For those of us in market research the qualitative versus quantitative dimension is, of course, very familiar. Somewhat less so is the second dimension – rigorous and empirical versus anecdotal and ad-hoc. But this second dimension is especially important to consider because it directly affects our ability to appropriately generalize the insights we develop. As practicing researchers, we know that qualitative research is excellent for discovery and quantitative is great for generalizations. But we also know that is not always the way things are done in practice.

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fruplaitWe recently conducted an online survey on behalf of a national food brand in which we displayed various images of a grocery store’s shelf space and asked consumers to select the product they would purchase from among those shown on the shelves. This project was successful at differentiating consumer choice based on how the products were packaged, and gave our client important information on package design direct from their target consumers.

That project got me thinking about how shelf space is a limited resource, and in some cases purchase decisions are influenced as much by what’s not on the shelf as by what’s on it.

For example, my Yoplait Fruplait yogurt has gone missing. And I blame you, Greek yogurt.

Fruplait is a delicious (to me) yogurt-fruit concoction that’s heavy on the fruit. There are four single servings to a pack and there are four fruit flavors from which to choose.

I had a wonderful relationship with Fruplait up until the time Greek yogurt started hitting the shelves. With Greek yogurt muscling in and shelf space at a premium, suddenly, the number of flavors in a given store was reduced. Then some stores stopped carrying Fruplait. Now, none of the four stores at which I typically shop carries it at all (it’s still available at some retailers).

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survey questions be clear on choicesI’m happy to work for a research company that embraces the philosophy that the respondent experience should be as close to the consumer experience as possible in order to elicit the most useful and actionable information. To that end, we employ different techniques that allow our survey participants to make choices – similar to what they would do in the real world. In so doing, we can provide results that are informative and actionable.

But enough of the sales pitch. I recently faced a problem that made me think of choice in an entirely new way: what if a consumer has a choice but doesn’t realize it? What are the potential consequences?

In my case, my physician ordered a treatment that required pre-certification by my insurance company. When I called for pre-certification, I inquired about the cost (my doc had warned me that the treatment can be very expensive). I was told it would be covered under a $250 co-pay.

I got the treatment and several months later the facility that administered my treatment sent me a bill for $1,500. After a lot of phone calls to my doctor, the facility and my insurance company, we finally determined what happened: my treatment can be performed either in a physician’s office (subject to the $250 co-pay) or at an outpatient facility (subject to a $1,500 outpatient deductible). Yet when I iniitally asked about the cost, the representative only told me about the in-office cost – without informing me that this cost only applied to in-office treatments. I was never told that where I received the treatment had a bearing on what I would pay. So I blindly made my appointment at the treatment facility recommended by my doctor.

We know that decisions should never be made in a vacuum. As researchers, we need to pay attention not only to the choices that we’re putting in front of our survey participants, but also to their awareness of whether or not these options even exist. For example, we’re about to launch a survey about an add-on to an existing technology. But we need to take into account whether the respondents even know that the existing technology is available to them – let alone the add-on. Defining and describing the existing product will help us put how interestested participants are in the add-on into context for our client. The more our participants know about their choices, the less likely they are to make a “mistake” in the choice task we put in front of them, and the better the data for our clients.  

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