During my time at Invoke, I have consistently told clients – and they have been consistently delighted with – how our Live platform and tools successfully merge the deep, emotive responses of qualitative research (and those little nuggets of insight that may otherwise be hidden in traditional quant) with base sizes (usually between 100-300) that can support quantitative findings and percentages.
And many clients see what we offer as “covering the bases.” After a project is done, clients very often walk away with multiple insights that can help them drive important business decisions. In some cases, however, clients feel the need to add some larger-scale quantitative work either before or after a session, for different reasons. As a researcher, I understand this. I believe what we have traditionally offered at Invoke is unique and valuable to my clients and can work as a stand-alone solution. In many cases, however, adding large-scale quant can provide additional functionality to foster a more holistic research engagement.
Some specific use cases I see for combining large-scale quantitative research with a qual/quant offering like Invoke’s are:
- “Pre-vetting” – All researchers have been there. It is time to move into the concept testing phase, but even after understanding internal guardrails and roadblocks, there are just too many concepts to test if you really want to dig deep and get those qualitative insights. Without the addition of large-scale quantitative research, clients often vet the list on their own. This approach goes against the purpose of doing research in the first place. Making these decisions internally takes the consumer or customer out of the process, which to me seems somewhat counter-intuitive.
- The Gut Check – Sometimes, after conducting a session, I have heard clients say they wanted to check in with a larger group of consumers to ensure what we learned from our smaller (though statistically significant) base holds true. This is usually due to one of two reasons. Either they have an internal need to hit a specific base size or because our tool is so unique, they want to double-check to make sure the data holds up to something they are familiar with – large-scale quant. I consider myself dedicated to delighting my clients so I say, “Go for it!” If it makes my clients happy and more confident in our data, then I am all for it. Plus, I have never been in a situation where our data didn’t pass muster.
- Going Mobile – In-the-moment research (shop-a-longs, at-shelf feedback, etc.) has become a valid point in the research spectrum. This type of research can get instant feedback on products, services, etc. before thoughts fade and hindsight comes into play. Mobile devices have been the key driver in facilitating this type of research. However, due to our focus on getting deep, emotive and insightful responses from our clients, our tool does not lend itself easily to access through mobile devices.
So, when these use cases are in place, what is a researcher or client to do? In many cases, my clients have facilitated a separate quant project before or after an Invoke session. Doing this, however, can be costly for sure and add quite a bit of time into a project lifecycle. Additionally, this creates two sets of disparate data that can be tough to reconcile on the back-end.
When the need for large-scale quantitative comes up, I can offer a promising solution for my clients that not only answers their need, but can also offer something preferable to the old way of doing things.