In a few years when we look back at 2022, I believe it will primarily be remembered as the year of scalable artificial intelligence. The year that everything changed.
As the pioneers of automated research, we at Zappi led the way in bringing automation to the research industry over a decade ago. AI will surely be the next major disruption this industry faces. In this article, I’ll share my predictions on how I expect AI to affect insights teams in the not-so-distant future.
In their 2015 book, The Future of Professions, Richard Susskind and Daniel Susskind predict the decline of professional work:
The end of the professional era is characterized by four trends: the move from bespoke service; the bypassing of traditional gatekeepers; a shift from a reactive to a proactive approach to professional work; and the more-for-less challenge.Richard Susskind & Daniel Susskind, The Future of Professions
I expect we will see these four trends apply to the consumer insights profession as well. AI will:
Turn consumer insights from a craft to a product, one that anyone in the organization can leverage.
Facilitate the democratization of insights, which will remove traditional gatekeeping of consumer data. Insights teams will no longer “own” the consumer.
Help companies be more proactive, rather than reactive, by serving up useful information whenever it is needed. Research will no longer be produced solely from specific business questions.
Cut many of the costs associated with consumer research.
AI will make consumer insights easier to acquire, access, understand and act upon. As a result, organizations will have rich consumer insights at their fingertips — faster and cheaper than ever before — with nothing to stand in their way of making better decisions based on consumer truth.
In short, AI is an amazing advancement for consumer centricity. That future should be thrilling to you as an insights leader. But you are undoubtedly looking ahead to what it will mean for you and your team.
You have an opportunity to act now to prepare your team and your organization for what’s to come with AI.
AI will likely play a role in every aspect of research. Here are some of the big ones that come to mind for me (and I strongly recommend watching this webinar from Mike Stevens for more information and examples on many of these):
Desk research: Desk research is time consuming and most researchers don’t have enough time to dedicate to it. Thankfully AI can dramatically cut down the time it takes. AI can quickly surface the top brands in a market, the strengths and weaknesses of those brands, how the brands are positioned and what their marketing strategies look like. As a result, I predict that desk research will become a lot more common across organizations — and that it can be done by anyone with access to AI.
Research design: Historically, writing surveys has been a time-intensive task for insights teams. AI can make it easier by suggesting different methodologies based on your research question and even designing questionnaires for the type of study you decide on. For example, you could ask it to design a brand tracking study and include screening questions relevant to your industry. This can take a lot of time out of the process and move the research craft from wordsmithing a survey to recommending how to take action on the results.
Conversational surveys: A personal interview with a respondent can often generate more meaningful open-ended responses than a typical survey because the interviewer can ask more personalized questions and probe for more information. But interviews are costly and time intensive. AI can bring a bit of that approach into the traditional online survey format. For example, AI could be used to power chatbots that ask consumers questions as part of a conversation and then probe for additional information. This approach tends to generate more meaningful open-ended responses that uncovers more of the “why” behind a consumer’s reaction. In the future, this interaction could even be done by AI-generated video avatars to feel even more like a face-to-face interview.
Synthetic respondents: Imagine if you didn’t need to ask humans what they thought about your ideas — if instead you could simply predict how people will respond to concepts. That would save you a lot of time and money. It’s something that AI will be able to do for you. I’ve heard a lot of complaints about this from people who believe that you can’t replace real people, but it doesn’t have to be about replacing them entirely. It would be a bad move to launch a new product entirely based only on AI saying it was a good idea. Real consumer feedback should be gathered throughout the process. Instead, this approach could act as an initial layer of research so you can explore many more avenues than you could in the past.
Concept creation: AI can be used to create the concepts you test with consumers for their feedback. It can generate the ideas (pulling from all the data you have on what works), put together the concepts with text and images, write any ad copy, claims, etc. AI generated ads or innovation concepts often perform decently — at least around average. But AI is unlikely to create anything truly groundbreaking because those ideas are based solely on the past. What AI can do, however, is help you create many more ideas and iterations from your initial idea — so you can test a lot more to find the version that works the best.
Analysis: Looking through large quantities of data to pull out the most important takeaways can take a lot of time, and you’ll often wonder if you missed something important. AI can help you take a first pass through the data. In the future, you’ll be able to ask questions of your data set and use AI to summarize the answers and point you to the right data. For example, you could ask it to tell you the top three takeaways from the study or to tell you how a specific audience reacted to one element of the concept.
Summarization: Condensing a lot of information into something digestible by the business is a time-consuming task for insights teams. But this is where AI is very strong. AI can summarize paragraphs of information into just a few bullets. Or it could create a digestible presentation of research findings complete with slide copy and AI-generated images. It has the potential to make research a lot more accessible for your organization and save your team a lot of tedious work.
Knowledge management: How do you make sure your organization knows what it already knows? Global organizations run so much research every year in every market — it’s a common struggle to stay on top of all of it. There’s a lot of waste in the system as people in different areas run similar studies to answer similar questions. AI will give you the ability to query large datasets (like all of your existing consumer research). In the future — assuming your data is organized — anyone in your organization will be able to ask a simple question about how a consumer segment feels about a specific trend or what are the key characteristics of all your top-performing ads and get a concise answer as a response. Any non-expert can start there before conducting new research to save everyone time and money for more value-add work.
There are two key areas where I recommend focusing today:
Start thinking about your data strategy: Your consumer data can be your competitive advantage, but it must be managed appropriately because the volume of data will grow in an AI future. Your consumer data needs to be accessible by your whole business — it cannot sit in individual PowerPoint decks on one team member’s desktop. Start thinking today about where the data comes from, where it sits, who manages it and who can access it.
Get everyone leaning in on AI: You may have team members who are excited about the possibilities of AI. You may also have team members who are skeptical of the idea or resistant to it. As a leader, you can give those who are excited the opportunities to explore and build new roles for themselves in your team. And you can foster excitement in the laggards. Paint the picture for them about the future of insights and help them see the role they can play in the future. Help them see the benefit AI brings. Make sure everyone on your team has access to different AI tools and encourage them to use them. Celebrate successes and share those stories with the rest of the team. If you make it something exciting the team can explore, they will be more likely to adopt it.
I think the best researchers thrive on change because they want to be on the cutting edge of their industry and of technology. So when something like generative AI rolls around, their first reaction is not how will this impact my job? Their first reaction is how can I get my hands on this thing because I have three ideas on how to use it in my job already?Oksana Sobol, Insights Lead at The Clorox Company
It can be daunting to be faced with certain change and yet so much uncertainty around what exactly that change will bring. I recommend embracing the opportunity. Insights leaders who lean into AI now will be the ones who define what the future of insights looks like for their organization.
To recap, here are the main points to remember:
Artificial intelligence will fundamentally change the way insights teams operate in the future. Everything from the way data is collected, to the way it’s analyzed and distributed through your organization will be affected by AI
This presents an amazing advancement for consumer centricity in organizations, as AI will make consumer insights easier to acquire, access, understand and act upon.
To start preparing your team for an AI future, start getting your data strategy in order and inspiring your team to start incorporating AI into their daily work.
If you’re interested in staying on top of insights trends and future-focused insights leaders, subscribe to Zappi’s podcast Inside Insights.