Ricardo Prieto-Ortiz, Omnichannel Brand Director at Nestlé Purina PetCare Europe, has immersed himself in behavioral science to design more effective marketing strategies. We spoke to him to learn more and discover how AI is improving his work now and in the future.
Can you give us an overview of your priorities at Nestlé Purina PetCare Europe?
Our number one priority is to work to create richer lives for pets and the people who love them. We try to do this in many ways – with our products, through education, and by partnering with other relevant stakeholders in this area.
How important is behavioral science in achieving your objectives, and can you give examples of this in practice?
Behavioral science is hugely important. It’s one of the reasons we chose to work with Fractal. With the help of behavioral science, we can overcome many of the challenges we face regarding our processes, our thinking, and our people. It gives us a great opportunity to become more persuasive in what we do.
For example, one of the biggest challenges we face is getting people with senior pets to choose products that are better suited for them. Because of the work we have done with Fractal, we have established that this isn’t a product innovation problem, it is fundamentally a behavioral problem.
Hence, having that understanding helps us tackle our challenges a bit differently. It means we can better deliver on our mission to bring better products to pets to help them through their life journey and, as a result, enrich the bond between pets and their owners.
Can you tell us a bit about the work you are doing with Fractal and the value you hope to realize as a result?
Fractal has made the process of applying behavioral economics to our work very easy to grasp. Just being able to bring it into our organization and make it easy for all relevant employees to understand is a major win.
There’s a famous quote that ‘90% of solutions can be found by clearly defining the problem statement’. Fractal’s work has truly helped us to get faster organizational alignment on where the problem lies – as I mentioned before, we are working on a behavioral problem rather than a product problem.
Now we have a general acknowledgment of what needs to be done. And so that is already a huge milestone. Next, we can get into the execution part based on our learnings. Watch this space!
Where does AI come in, and how does this add value to the business?
AI is present throughout the full cycle of activities that we carry out, so the value we can get from it takes many different shapes and forms. It helps us identify ideas and improve the efficiency of our processes. It gives the ability to make faster and better decisions. It can also help validate specific perceptions of marketing concepts.
For example, I think AI could fundamentally transform how we conduct our research in the future. The notion of synthetic personas (virtual models that mimic a real person’s characteristics and behaviors) can have a huge impact on our work. This is an opportunity that we are exploring currently.
Are you finding any challenges in embracing AI? If so, how are you tackling them?
We need to get much better at understanding how to extract the value from AI. At the moment, our usage is very much at a surface level. Simple things like better prompt engineering will help.
What advice would you give to other businesses that are adopting AI, behavioral sciences, and design in their businesses?
The adoption of behavioral science and AI can often challenge established ways of thinking. Its effective use requires a big shift in understanding – and this means buy-in from the top is essential to democratize its use throughout the organization. You need people who understand these principles, who see the value in it, and who are willing to endorse the results that come from it.
With AI in particular, there’s still significant reluctance to adopt it. People worry about what it might say about them if they admit they have used AI assistance. So top management needs to make it very clear that it is not only OK, but often incredibly beneficial, to use AI tools. If we can make progress in these two areas – endorsement and adoption – then usage will exponentially increase.
