By now, we’ve all heard the phrase “on both sides” innumerable times. It generally means giving equal time and space to “both sides” of an issue. Though we usually hear about in terms of gender, ethnicity, and identity, it has important bearing in the research world too.
Let’s say you’re running an IHUT to evaluate three new package styles. You want to understand which package is generally easier to open, whether people with arthritis find it challenging to use, and whether people end up storing it in their fridge or forget about it in the cupboard.
You launch the IHUTs, gather 200 survey completes, and complete 25 online IDIs from Victoria, Moncton, Brantford, Saguenay, Regina, and Whitehorse. You now have extensive data showing the strengths and weaknesses of each of the three package styles.
As you write up the report, you realize that the three slides for the 3 packages are unbalanced. Package A has a moderate number of both strengths and weaknesses, but Package B has few strengths and Package C has few weaknesses. Package C is obviously the most accessible, easy to use, and memorable package.
Do you hunt through the data to tease out teeny tiny strengths of B and teeny tiny weaknesses of C so that all the packages have an equal portions of strengths and weaknesses? No.
Do you remove some of C’s strengths to equalize the space and create more balance? No.
You apply the same threshold of success and failure to all three packages.
“Both sides” doesn’t mean a poorly designed package gets the same consideration as a well designed package. It means each package is subjected to equal standards for success.
And, it means is you have space to add images of happy product users next to Package C.
You might like to read these:
- What exactly is the IHUT research methodology?
- What are the key features of a perfect package test?
- Launching High Quality IHUTS and Product Tests for Marketing Research Studies