7 Project Ideas For Generating Advanced Insights Using Reactor
A lot of market research is tactical: it is aimed at measuring responses to specific new initiatives such as new packaging designs, new advertising concepts, etc. However, there are many opportunities for uncovering valuable insights by stepping back and conducting more general research to better understand your brand, product or service.
The following are ideas for uncovering more general, strategic insights using Implicit testing on Reactor.
- Understanding how consumers group concepts together
Implicit response tests measure the strength of connection between a concept (e.g. expressed as a word or short phrase) and a construct like a brand or product. Understanding these connections can be useful. However, there is, potentially, a more complex and rich understanding of these connections that can be mapped.
For example, imagine you are researching a food brand and are mapping the connections between your brand and a range of concepts. Imagine you find that the concepts of ‘Natural’ and ‘Healthy’ are both strongly connected to your brand, yet the concepts of ‘Fresh’, ‘Feel-good’ and ‘nutritious’ are not.
First, by testing a wider range of seemingly similar attribute words like this you can get a more nuanced understanding of your brand perception. Second, you can run a mathematical analysis such as factor analysis on these results to better understand which attribute concepts seem to behave similarly and which behave differently. This could uncover underlying ‘super-attributes’ that explain the associations within a range of attributes.
For example, perhaps the very similar scores on ‘Natural’ + ‘Healthy’ reflect an association with a broader concept that one might call ‘Natural health’, whereas the contrasting lack of association between your brand and ‘fresh’, ‘feel good’ and ‘nutritious’ might reflect a separate concept that one might call ‘Feel good nutrition’. Becoming aware of these underlying concepts could be very useful in better positioning your brand with consumers.
- Factorized experiments to uncover the ‘levers’ of design
When designing new creative material for your brand—be it logos, advertising, packaging or product design—you can test each design option as a whole, to measure the associations it triggers. However it can be even more valuable to understand exactly which elements within each design are driving people’s associations.
For example, perhaps your pack design’s strong association with ‘Sweet’ is mainly due to its use of the color red. Or, perhaps it’s a shape or image in your design, such as a bowl of fruit, that is driving that particular association.
While sometimes it is the ‘chemistry’ of multiple elements placed together in a unique arrangement that is evoking a particular reaction, there is often one or more design elements that are the most influential.
This kind of research project can be run by systematically testing variations on a design, with only one design element changing in each variation. This type of ‘factorized’ test design is often best thought about in terms of a grid. For example, imagine there are just three design elements that you are interested in varying: the color, shape and size of an icon on your packaging, and for each element there are two or three options. This would result in 12 possible designs to test and analyse for Implicit associations:
| Design # | Color | Shape | Size |
| 1 | Red | Square | Small |
| 2 | Red | Square | Large |
| 3 | Red | Circle | Small |
| 4 | Red | Circle | Large |
| 5 | Red | Triangle | Small |
| 6 | Red | Triangle | Large |
| 7 | Green | Square | Small |
| 8 | Green | Square | Large |
| 9 | Green | Circle | Small |
| 10 | Green | Circle | Large |
| 11 | Green | Triangle | Small |
| 12 | Green | Triangle | Large |
By understanding the relative importance of each element in driving reactions, you can make more informed design choices. You may discover, for example, that your design could be more effective if you removed certain elements while enhancing or changing other elements.
- Database building
Building your own database of Implicit association results can be valuable. If you are interested in packaging, you could collect data on an array of Implicit associations with both your product’s packaging and those of your key competitors, perhaps among both buyers and non-buyers, or among different demographic groups. If you are interested in advertising, you could do the same for a range of print, video or audio ads for both your brand and your competitors.
This could help generate insights into your brand’s strengths and weaknesses across products and compared to competitors. It would also help contextualize the results of any new stimuli that you test.
- What drives a particular emotional response?
Similar to the factor analysis and factorized experiments recommendations, you could investigate in more depth a particular emotional response or feeling. For example, there may be a particular feeling that you think is important to evoke in order to evoke desire for your product. It may be ‘Joyful’ or ‘Safe’ etc.
By testing a large number of stimuli on this one attribute word, it could yield insights into what types of stimuli might be more effective at evoking this feeling.
Equally, by testing lots of related attributes you could gain insights into what your base attribute means in consumers’ minds.
You could also investigate the differences between buyers and non-buyers in a range of associations with your brand/product/service. By analyzing these associations, and also comparing them to associations with other brands, you could derive insights into which associations drive people to your brand, and which to competitors.
- Tracking
Reactor’s ability to save tests and easily re-run them makes brand tracking easy. By regularly running Implicit measurements against your brand you can compare them with more standard, traditional conscious tracking. The Implicit sentiments towards your brand may differ from the more consciously expressed ones. For example, changing sentiments towards your brand might first begin to appear Implicitly before people consciously express them, making Implicit brand tracking a potential ‘early warning’ measure.
- Brand extensions
Using Implicit tests, you can explore how automatically connected consumers feel your brand is to product areas and markets that you are not currently in. This could provide valuable information on which new areas consumers would naturally accept your brand operating in, and which areas might be more challenging to penetrate.
- Language: testing alternative words
The specific words you use to describe a product or service affect the associations it creates in people’s minds. By testing a range of alternative words used to describe the same thing you can gain powerful insights into how best to describe your product or service. You could also get insights into why certain words might work better than others. For example, often the benefits of a product can be alternatively described as gaining something, or avoiding losing something. Or the product might be described as making you feel unique, or promoting participation in something that’s widely popular. Discovering which approaches are more effective can be very valuable.
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Each of these strategic project ideas goes beyond the more common tactical use of tests and could help you generate valuable insights.
