“Good is never good enough”. We imagine it is a quote from someone even if Google does not help us to define who, but now it is a mantra, the title of many books with sparkling covers mistakenly inserted in the “Psychology” department of bookstores.
For us, the maxim “good is never good enough” is a way of representing the evolutionary path of a service offered by TSW that was already working. And it worked fine! But not enough. Not at least for all the contexts and the potential that we could / wanted to cover. We are talking about BARTT, acronym for Brand Association Reaction Time Task, the tool that allows us to measure (and then strengthen) brand associations, a primordial element in the people-brand relationship and an essential strategic asset to improve the user experience with the brand even before it starts.
Brand associations are mental connections between a brand and a concept, thoughts that unconsciously a brand is able to evoke when a customer approaches it, such as “simplicity” when talking about Apple or “performance” when talking about Nike. These “brand associations” are particularly strategic within a user experience because they are able to bring customers closer, if positive, or move away, if negative. Therefore, they represent an important strategic lever that brands have at their disposal to improve the user experience from the earliest stages.
Identifying and measuring the intensity of brand associations is possible: we do it thanks to the BARTT (Brand Association Reaction Time Task) and the IAT (Implicit Association Test), the famous cousin from which the first tool is inspired by the basic logic and scientific assumptions that make up its foundations.
The “Brand Association Reaction Time Task” or BARTT is a test that allows us to involve people and evaluate the intensity of the implicit associations that involuntarily and continuously create between brands, products, payoffs, but also values (eg, “sustainability”, “effectiveness”, etc.).
To quote a children’s song, to measure an associative intensity of this type, it takes milliseconds … and to measure milliseconds, you need software that does it, and there are some. The problem that characterizes these platforms, however, is that they are optimized for laboratory use, ideal for those who work in universities, but limiting for widespread use via the web, designed for large-scale data collection and / or with a longitudinal logic, especially if the participants are volunteers involved through sponsored campaigns and not through panel providers.
In this sense, it is fascinating and perhaps in some ways paradoxical, that the solution to this problem comes precisely from the collaboration implemented by TSW with the University of Padua.
The union of the two working groups has in fact allowed the creation of a new tool, built from scratch, designed and optimized with the aim of combining ease of data collection (eliminating for example the need for plugins), with the solidity of an instrument that cannot permit itself errors, even (and above all) if in the order of milliseconds.
Although it can potentially appear as a problem of simple solution, the problems are not negligible. Memory management, the resources of the different hardware, the connection, the peripherals and the flexibility of an otherwise monolithic instrument represented a series of obstacles that have been individually overcome bearing in mind the need not to accept compromises that would undermine the solidity of the final data collected.
We asked Michelangelo Vianello, Associate Professor of Psychology at the University of Padua, for his point of view on the work done together.
Professor, what was the added value given by the collaboration between the University and a reality like TSW?
Collaboration between universities and businesses is simply essential. Applied research must necessarily be carried out through the dialogue between scientists and professionals. The University gains in practicality, businesses gain in effectiveness. Protagoras said: “Practice without theory is blind, just as theory is blind without practice.”
What new research scenarios are opening up thanks to this evolutionary?
Some research shows that purchasing behavior is influenced by automatic processes that are measured by the tool developed in collaboration between UNIPD and TSW. However, the issue is widely debated, and specifically the conditions under which automatisms are more important than controlled and more aware processes must be identified. A tool for the evaluation of automatic associations allows to collect extremely precious data for research.
What do you think of a reality like TSW that brings research applications into a more commercial context?
My position on this is very clear, but perhaps biased: any company or professional who does not base their work on empirical evidence essentially relies on chance. In the absence of publicly verifiable evidence, when an intervention is proposed and you find yourself answering the question “Does it work?”, the only honest answer is “I don’t know”. In my experience, however, this answer is too infrequently given. Then there is a second category of professionals, those who base their actions on empirical evidence and can answer “Yes, it works” by explaining the basis.
So to recap: we had a tool that worked well. We have created one that works best, allowing us to expand the potential of use of the test to so far unexplored terrain and dynamics and which will provide a continuous and easily accessible photograph through the mapping of the forces of value association. Another tool at our disposal to design better experiences together with companies and people.