According to David Sackman, CEO of Lieberman Research Worldwide, in the coming years, artificial intelligence (commonly referred to as “AI”) will facilitate field engagement, survey, and questionnaire development (notably through chatbots). Data scientists will play an important role for companies as they gather a specific amount of data on consumer behavior patterns and preferences to better understand the behavior of their customers. Sackman expects that AI will help with market analysis yet won’t completely eliminate traditional research methods.
San Francisco-based marker research company InterQ has been successful using real-time market research. InterQ notes that “capturing a customer’s feedback at the moment yields the most honest data”. For example, if you wish to discover how a customer engages with your app. Interacting and capturing real-time feedback leads to “very different responses than having a customer try and remember exactly what they were experiencing a few days or months later in a focus group or during an interview”.
Furthermore, real-time market research is flexible and can be quickly adapted to how users are responding. Since companies are constantly launching new products, it’s “more important than ever that capturing customer feedback be in the moment.”
Although big data remains a priority for many market research firms, others have recently gained interest in “microdata”: the insight of data regarding the behavior of individual customers.
Sometimes it is important to gain an in-depth understanding of the market and customers, which can be hard to obtain through macro-level data patterns.
Statistics Canada provides resources on modern microdata collection frameworks such as “public use microdata files”, “direct access to detailed microdata in a secure physical environment” and “remote access solutions”.
Nowadays, consumer research surveys can require substantial time investment and concentration for the responder. Meet Attest, a UK-based startup that has built a market research platform to enable companies to get “market insights quicker and more often”.
Attest surveys are “bite-sized” and can be done on mobile devices, similarly to casual gaming or checking social media profiles, and are designed to play on five emotions that Attest beliefs increase the likelihood of market research participation. These are: “contributing, learning, enjoying, rewarding and feeling valuable”.
Augmented reality could unleash market researchers’ creativity by adding unusual elements into common retail environments.
Imagine a survey task in which respondents are asked to go into a supermarket and rate packaging and point of sale, receiving prompts as they go around the store using a dedicated augmented reality app a la Pokemon Go. Or what about a transit check-in system, where participants can move around the area to show where they would expect to see specific elements rather than where they actually are?
There has been a number of retailers using digital co-creation tools in recent times. A good example is Glossier, an online-only cosmetics company. The company has a very engaged, loyal community of users and Glossier has done a great job of asking questions, listening to feedback, and then creating products or services that are a result of this exchange through its platform.
While some companies will probably stick to a more traditional product development framework, others may work with a marketing research company to help develop good questions to ask, guide the customer engagement journey, and collect the generated data.
Internet of Things (IoT) devices are already producing huge amounts of data about many aspects of our lives and such a trend is expected to dramatically increase in the next few years.
Picture an energy company that wants to understand its customers’ energy use over Christmas or New Year’s Eve. Historically, it could only see how much each customer was using when a meter reading was submitted, and maybe analyze this in conjunction with a survey about energy use over the period.
Evidently, smart meters and wirelessly connected central heating controllers can generate a much richer stream of consumer data.
Behavioral economics has shown that we “don’t always make rational decisions and that many of our decisions are driven by rapid, nonconscious, intuitive thought (also called “System 1” thinking)”.
A set of early-stage methodologies to measure these thought patterns have been under development and continue to evolve such as applied neuroscience, facial coding, biometric response, eye tracking, and Implicit Reaction Time (IRT). The latter measures “the length of time it takes for a respondent to answer a specific question; the faster the response, the stronger the presumed conviction”.
According to Marketing Daily Advisor, a recent, significant trend has been the implementation of deeper analytics integration. It is now possible to combine website analytics data, behavioral insights, and emotional responses to online ads “into a single personalized picture of the consumer”.
Deeper back-end integration on the analytics side “allows marketers to put their market research into a broader context and better understand more fully how to apply those insights to their business”.
There is a lot of data you can collect from wearables such as Fitbit fitness trackers or the Apple Watch (with the users’ permission that is).
Heart rate data could tell you about users’ reaction to a product, marketing contact, or a service encounter, “how much exercise someone really takes part in during a week” could give you more truthful information to understand their shopping and eating habits than traditional survey methods.
There are approximately 4.48 billion social media users worldwide (and the number just keeps climbing). That equates to about 57% of the current world’s population and that’s where most consumers are spending their time nowadays.
Social channels have become one of the most effective, time-efficient, and inexpensive tools for recruiting target respondents and collecting data on their consumption habits. This is a natural evolution from the more passive social scraping and social listening tools that are used to gauge sentiment and drive analytics. It’s a proactive and targeted method we call social sampling and it borrows from the highly effective playbook of advertisers who have recognized the precision and effectiveness of targeting niche audiences on a global scale.
The main advantage of social sampling is the ability to target a specific population. This considers age and gender, but also interests, language, geographical area, and even brand and product preferences. By surveying consumers virtually, it is possible to effectively target the different participants by their known niches –whether those are buying behaviors, personal interests, unique demo- or sociographies, location, or other criteria important to build a highly relevant sample. On top of that, the inherent precision of targeting via social allows for participants to be surveyed on topics they care about, resulting in higher response rates. To learn more about how we do social sampling at Potloc, read this article by our CEO Rodolphe Barrere.
I hope the above list gives you a sense of some of the fascinating, emerging technologies in the ever-changing discipline of consumer research.