For all the change we talk about happening in the market research industry, a lot of what we do really hasn’t changed much. Qualitative techniques are tried and true, and still have a prominent role in providing insights in both consumer and B2B settings. And while there seems to be a lot of momentum around big data and social listening, the survey is still king.
That’s not to say we haven’t seen some evolution in how surveys are done, how we design them or how we can improve the insights, though. Here are some trends that are going a long way toward improving how we do survey research.
Automation has perhaps had the biggest impact on the market research industry over the past decade. By automating routine tasks, we’ve benefited by shorter timelines, fewer errors and more efficient budgets. Maybe more impactful, automation has given rise to an increasingly sophisticated DIY research industry.
No longer does a researcher need to have programming skills, data processing experience or even have to know how to make a chart. DIY tools leave these tasks to the technology, allowing the researcher to focus on analysis and developing actionable insights.
At least for now.
With AI and machine learning, analysis is also increasingly becoming automated, leaving the researcher more time to spend on insights and their implications. Machine learning AI has huge promise for analyzing and taming big data and unstructured data like text, video and images in a fraction of the time a human (or a whole team of humans) could and at a fraction of the cost.
As in other industries, those of us in market research will need to adapt to this increasing level of automation, as many of the tasks previously handled by trained teams no longer require manpower to complete.
Behavioral Economics Theory
Think back to your microeconomics class and the utility theory. This theory assumes that consumers consider several factors when making a choice in order to maximize utility. It assumes a very rational decision-making process. But consumers don’t always make rational decisions.
Enter behavioral economics, which recognizes that consumers often make choices that are not based on a rational decision-making process. There is an emotional, non-rational aspect to decision making that a traditional survey can’t measure.
How can we account for this in market research surveys?
- Design considerations: context and framing are important. The way you set up the exercise and word questions has a big impact on the answers you get. Try to get close to the actual context to let subconscious decision making enter into the choices being made in the survey. Mobile research has long been viewed as a potential means to get closer to the truth when a survey is pushed to a consumer who is experiencing a product or decision “in the moment”
- Interpretation considerations: use behavioral data to model survey data. Consumers generally overstate purchase interest in a survey. Calibrating survey results using actual in-market sales data, can get you closer to the truth. Volume forecasts frequently use sales data to calibrate their models.
- Measurement considerations: attempt to measure the impact of emotion on the decision making process. A whole new area of subconscious measurement is rapidly growing with good promise to better understand the subconscious associations consumers have with products, brands and other stimuli.
Which leads us to our final topic, implicit research techniques.
Implicit Research Techniques
Implicit research techniques are indirect techniques that don’t rely on self-reporting. There are a number of emerging techniques that access or offer insights about how the subconscious mind reacts and responds to stimulus, whether it is a concept, advertisement, brand logo or something else.
Some of these techniques measure your body’s involuntary responses. With the right equipment, researchers can measure biometric changes (e.g., heart rate, electrical conductance or a participant’s skin, eye movement, and breathing rate) to understand unconscious responses that respondents can’t (or won’t) articulate in a survey. (Think of a lie detector test – even the most cool and confident liar can’t control the physiological changes the body undergoes when exposed to certain stimuli.)
There is a lot of buzz around Neuroscience techniques, which use Electroencephalography (EEG) to map emotional response, attention and attraction based on the areas of the brain that are stimulated. This is increasingly used in advertising, packaging and brand testing to maximize the emotional reaction that is so important in behavioral economics.
The Implicit Association Test (IAT) is one of the most popular methods of implicit research. The method simply measures how quickly and accurately a respondent sorts words or images into categories after being exposed to a stimulus (a prime). The impact that the prime has on speed and accuracy of the sorting exercise reveals the strength of the respondent’s feelings about the prime.
Each of these trends have been important to the evolution of the venerable survey. While we recognize that this method has flaws and weaknesses, it doesn’t mean we have to give it up completely. More than ever, it’s become an extremely cost-effective means to get insights quickly. And by designing with the principles of irrational decision making in mind, and augmenting with implicit techniques, it’s a good bet that the survey will remain an important tool in the market research toolbox.