How top brands are using AI for consumer insights

Earlier this month, Zappi held a panel in London with leaders in the insights industry — including Tony Costella, Global Consumer and Market Insights Director at Heineken, Christian Niederauer, Global Head of Insights at Colgate-Palmolive, Nic Umana, Global Agile Innovation Human Intelligence Director at Mars, and our very own Steve Phillips — to share how they use AI for insights and what they predict for the future.

And what a turnout we had! This was our first time hosting a Breakfast Club event and it certainly did not disappoint. 

If you missed it or are looking to share details with your colleagues, here’s some of the key takeaways.

“Don’t be afraid to ‘make yourself obsolete’ because the people who do that are the ones who will experience the next new challenge. Do you really want to be doing 40 concept developments a year? No. That can be automated, so leave that and you can spend more time doing the super exciting stuff.”

- Tony Costella, Global Consumer and Market Insights Director at Heineken

After sharing some of their experiences using AI with insights so far, from shaping hypotheses to building target consumer profiles to discovering new ideas, the panelists were asked what they think the role insights will take in an AI integrated world. 

While no one truly knows what the future holds in terms of the reach of AI, all three panelists agreed that we will always need a human in the loop. But that human touch will largely come into play when making the big decisions and connecting the dots.  

“AI helps spark ideas, giving you ideas you haven’t yet thought of…So don’t use it to validate or predict but to help you be more creative and more open.” 

- Christian Niederauer, Global Head of Insights at Colgate-Palmolive

With AI integrated into the research process, insights teams can remove most of the menial and time consuming tasks from their plate and be freed up to dive deeper and think bigger, as well as simply speed up the process of ideation. 

“AI is phenomenal at taking masses of unstructured data and summarizing it very well. So it’s super easy [for AI] to scroll through the tens of thousands of pieces of research we have and pull out some of the key insights to help you find what you’re looking for.” 

- Tony Costella, Global Consumer and Market Insights Director at Heineken

For example, in early stage research, insights teams are used to starting at zero or with a relatively blank page. AI can generate multiple concepts and rough ads quickly and easily, which can help insights teams put ideas in front of consumers earlier in the development process. 

So with AI in your toolkit, insights teams have the advantage of starting at 30% (for a fraction of the cost) and then optimizing and validating the concept from there.

“It’s the job of AI to diverge and the role of humans to converge…If you let AI open up our minds and open up the possibilities, then we’ll converge in a way that is right for us and right for our business.”

- Nic Umana, Global Agile Innovation Human Intelligence Director at Mars

Christian shared that it’s similar to what accountants experienced when Excel was first created. Were they suddenly less valued? Not at all. In fact, they were freed up to do even more once that tool was integrated into their processes. 

“Now we can actually do the research we wanted to do.”

- Christian Niederauer, Global Head of Insights at Colgate-Palmolive

As AI continues to integrate into our day-to-day, there will be certain skill sets insights teams will need to develop or strengthen in order to excel.  

Nic stressed that as tools change, skill sets will need to change, and she couldn’t be more spot on. During their conversation, there were three skills that kept coming to the surface as key areas to develop: foresight skills, human skills and prompting skills.

1. Foresight skills

The job of insights is to keep testing the boundaries. And to make the right moves for the future, you need to have good foresight.  

Foresight can help you create multiple possible future scenarios and explore innovative ideas. In one of our recent podcast episodes, Joanna Lepore, Global Director of Foresight and Capabilities Exploration at McDonald’s, defined foresight as: Intentionally observing people and the world to try to see where we'll be in the future (so that you can get there before your competitors do).

“It’s really about having the courage to face a changing world. So going into the future with your eyes wide open, knowing that things are not going to be the same as they always have been.”

- Joanna Lepore, Global Director of Foresight and Capabilities Exploration at McDonald’s

Foresight will play a huge role in unearthing deep insights about humans and understanding where the world is headed. So it will be key to develop it as we take on the future with AI by our side.

2. “Human” skills

“The future of insights is not less human. It’s actually using us as humans in a better way. It’s having humans understand how to partner with machines and working out how humans give you that competitive advantage.”

- Nic Umana, Global Agile Innovation Human Intelligence Director at Mars

Adding AI to your toolkit isn’t about using humans less, it’s about putting people where they can have a greater impact. And how humans interact with machines will ultimately be what provides a competitive advantage.

“The perfect model is always the hybrid model. Use the machines for the right jobs and use the humans for the right jobs. It’s that beautiful blend of machines and humans and understanding where you may be able to automate and save time, but also where it's important to use deep empathy and insights that you can feel…is where to err on more human than machine.” 

- Nic Umana, Global Agile Innovation Human Intelligence Director at Mars

After all, it’s humans who understand empathy and the depths and power of emotions and deep understanding. So we need to own that space. Which may mean that you have to spend time upskilling your emotional and communication skills to strengthen your understanding even further.

In other words, we need to land our specialty as humans so when it’s time to bring in machines, we can pass the baton and AI can take care of what machines excel at.

3. Prompting skills

“Being a great insights person isn’t just about answering questions, but asking the right questions. Getting the answers is not difficult, it’s asking the right questions.”

- Tony Costella, Global Consumer and Market Insights Director at Heineken

Developing the right prompting skills will without a doubt be extremely helpful when leveraging AI. As insights professionals, chances are you’ve already spent years turning business questions into research questions. So it’s more about working that muscle in other ways to determine the right questions to ask and the data parameters to point AI to.

Tony advised that it will do insights teams well to maintain that relentless curiosity, as it will help you discover the right questions to ask. 

“You need to be a prompt engineer now. If the machines learn well, you’ll be able to ask them questions using natural language. But if we keep on prompt engineering and asking the machines in the way that machines ask questions, then it will stay that way and it won’t learn.”

- Nic Umana, Global Agile Innovation Human Intelligence Director at Mars

The better you’re able to speak to AI tools through your prompts, the more it will learn and understand, ultimately giving you the best answers to what you wish to uncover.    

“Synthetic samples can be great to help understand and create and develop new ideas, but we will always need to refresh that data set with data from testing with real consumers.” 

- Tony Costella, Global Consumer and Market Insights Director at Heineken

A major point from the discussion was that data will remain your greatest asset in an AI world. 

It’s important to keep in mind that while synthetic data is great for use in early stages, it can potentially cloud databases. Which is why you'll still need to make sure you’re using data from real consumers to validate your ideas. 

And as AI-generated responses are fed into databases, refreshing your datasets will become even more vital for brands so you aren’t working with stale data that’s no longer relevant. 

“Where we should really be using synthetic samples is in the design phase, which is pulling on the data from years and years of research and thousands of concepts tested with real people, optimizing and developing based on that, but then going back and testing with real consumers afterwards.”

- Tony Costella, Global Consumer and Market Insights Director at Heineken

On top of that, if AI is democratizing that data, where is your business’s competitive advantage going to come from? That’s where building and evolving the right data assets for your brand can go even further. 

“We as researchers are in an incredibly brilliant position because we can be the data asset that is being used by AI to create new ideas and products. But the critical piece is that we are the ones who manage and worry about that data.”

- Steve Phillips, founder and CEO, Zappi

So as you weave AI into your processes, make sure you’re keeping the data fresh, harmonized, organized and reusable.

“The worst thing we can do is tell people not to use these tools. Everyone in every function should be experimenting, they should be understanding the capabilities, and they should understand the risks.”

- Nic Umana, Global Agile Innovation Human Intelligence Director at Mars

For those of you who attended this event — thank you! We hope it provided valuable insight into how AI can be used to increase the impact of consumer insights and marketing. 

For those of you who did not attend, we hope these highlights provided tangible insights into how to better work with AI and look forward to seeing you at the next Breakfast Club event coming to a city near you! If you’d like to learn more about Zappi events, talk to us.