Two Use Cases for Leveraging A.I. to Level Up Market Research
By Tristan Shook
From pioneers like GeoCites and Google, to the latest trends in the metaverse, Web3.0, and ChatGPT, the internet is evolving at warp speed. These advances in technology don’t exist in a bubble- they help marketing research evolve, too! Before the internet, qualitative interviews and focus groups were gridlocked to physical location, and quantitative surveys needed to be taken either by phone or good old-fashioned pen and paper.
So, what’s next?
Generative A.I. has recently emerged as a potent tool that has the potential to revolutionize research workflows in fascinating ways. At W5, we are actively experimenting with these tools and have identified several potential use cases.
W5 is exploring ways to combine human-driven research insights and primary data to rapidly generate innovative results. Here are a few examples:
Speeding Up Concept Testing with Agile Ideation
Generative A.I. is especially useful in the initial phases of research, where it can be used to generate concepts for participants to evaluate. These tools allow researchers to generate multiple concepts in a fraction of the time previously needed by using research data to inform the A.I.'s understanding of a target audience's preferences, pain points, and needs.
A common criticism of these tools is that they can flatten content and ideas, giving generic and expected responses. The fix? Specificity and intention. By creating prompts that are highly specific and based on primary research data, the tool can generate more compelling and relevant product concepts, brand positioning statements, taglines, or other initial creative. Then, researchers can quickly test these concepts, refining and iterating upon the most promising ideas. This agile approach allows teams to move faster from insight to activation.
Storytelling with Detailed Persona Development
Using the same principles as our concept testing example, generative A.I. can help organizations understand their audience more comprehensively. For example, persona development aided by A.I. learning can generate comprehensive and detailed personas that reflect the unique attributes of a target audience.
By prompting an A.I. tool with highly specific, human-driven research data, these tools can open up new pathways, help visualize an audience, tell stories about segments, and otherwise generate creative content that helps to build a story around your target audience that is narrative-driven and relatable.
By incorporating A.I.-driven agile concept creation and testing or persona development into the research process, market researchers can unlock the full potential of their primary data and enhance their insights and deliverables.