We all have been there: Craving for a meal or snack after a tough day at work: "Shall I prepare a nutritious balanced meal, full of vegetables and environmentally-friendly meat-replacing pea-protein?" or "Will I surrender to the temptation of that juicy double-cheese hamburger with extra french fries?" In spite of good intentions and resolutions, much of what we eat we choose by impulse. Even when ingredients and nutrional values are the same, the package familiarity, the portion size or even the package color drives the impulse choice.

In traditional consumer research, people express preferences by checking boxes or rating scales. In the case of comparing products that are all socially desirable, all responses would appear acceptable. Ratings would then reflect true product preferences. However, when adding highly endulging yet calorie-rich foods to the comparison, consumers may tend towards choosing the socially acceptable healthy alternative. Clearly, such outcome does not predict product success: Product success depends on choice impulses in the store, not on socially desirability.

In recent years, alternative consumer measures have been developed that reveal hidden choice impulses towards products. Applegg applies these measures, named Applegg Attract, to complement regular consumer measures in regular consumer studies. When people feel compelled to give a socially desirable answer, Applegg Attract measures will still signal the products that they really feel attracted to.

Imagine comparing very similar, healthy products of competing brands. Would product brand and package still influence purchase behavior? And, would Applegg Attract measures still predict purchase behavior? Which consumer measure would predict that behavior best: the classical consumer test, Applegg Attract or a combination of both?

A team of scientists including Applegg 's Harold Bult studied these questions with a large population in Helsinki using three different brands of fruit-quarks.

Consumer test: Fruity quark lovers (n=134) participated in this study. Besides a variety of classical consumer measures, we collected brain measures and involuntary hand movements. On day 1, participants evaluated three quarks using classical consumer test measures. On day 2, a random selection of these consumers (n=52) watched images of the three quarks, while producing EEG brain measures and joystick responses.

Purchase behavior: During the month following the consumer tests, participants kept a diary of supermarket purchases.

Results: Brain-measures predicted purchase behavior very well (see figure below). This is remarkable, considering that the compared products differed only in brand and graphic design. In fact, portion sizes, package shape and ingredients (high-protein) were all the same. Explicit consumer measures like brand-loyalty and willingness to eat also predicted purchase behavior very well. Yet, the best predictions resulted from classical and Applegg Attract measures combined. This is truly remarkable considering the lack of reasons to produce socially desirable answers.

Food purchases are best predicted by a combination of (1) unconscious brain responses and joystick responses to food images and (2) a set of classical consumer measures.

This technology allows for more reliable testing of healthy and sustainable foods, utilities and services that usually receive positive socially desirable evaluations.