- AI is becoming increasingly popular among product managers and is being used by companies such as PepsiCo and Toyota.
- Generative AI can be used to brainstorm product ideas or help create marketing materials.
- This article is “CXO AI Playbook“Business leaders speak openly about how they're testing and using AI.”
A product manager's job focuses on understanding what consumers want, creating products that meet those needs, and ultimately increasing sales for the company.
To help with this, many companies are adopting generative artificial intelligence to sift through and analyze vast amounts of data to extract insights that can help them develop faster and more compelling products.
“Broadly speaking, they're taking big data about consumers — their demographics, their values – and matching that with product design,” Alex Burnap, an assistant professor of marketing at the Yale School of Management, told Business Insider.
Burnap said AI can also be used to predict which product features or designs will be most appealing and likely to generate profits. Burnap's research also includes developing machine learning algorithms that can understand customer needs and translate them into product features. He also consults for large companies, including General Motors, and startups.
Several companies, including consumer goods brands such as PepsiCo and Kraft Heinz and automakers such as Toyota, are already using AI to support product development.
Burnap said the technology will be increasingly used in product development, helping product managers do their jobs more efficiently and developing products that drive business.
BI spoke with Burnap about what companies need to know about AI to understand consumers and inform product design.
The following has been edited for clarity and length.
How can businesses use AI to understand consumer needs and wants and design products accordingly?
There has been a lot of research into how to identify customer needs, or overlooked needs and market opportunities, and create new products that were not previously addressed. Early efforts seem to be very successful.
For example, you can use a customized version of ChatGPT to search all Amazon reviews for a particular product category and find reviews that say, “This product was great, but it could have been a little better.”
This is definitely being used to tap into customer needs and I think we'll continue to work in that area.
How can companies use this information to help design and develop their products?
The product design lifecycle starts with an initial idea for a product that people want. It goes through various design stages, engineering, manufacturing, and marketing until it is released.
At almost all of these stages, generative AI models play some role. One is the very early stage of understanding what people really want, and this stage will continue to evolve.
These models will continue to help designers enhance product development, although full automation may be difficult, as a lot of human creativity is still required, at least very early in the design process.
One of the first advances we'll see for successful product design is on the back end, the marketing side: coming up with ads that tell people what's out there and personalizing them to fit exactly what the user likes.
Personalization is a big difference with many models. The current ad serving paradigm is highly scalable. Think of companies like Google AdWords. They are very good at targeting ads created by publishers to the right customers. We will see advertisers generating personalized ads for users, rather than just targeting existing ads.
What advice would you give to company leaders considering leveraging AI in product development?
First, consider whether you really need generative AI: In the product design world, is this a technical imperative or a real need that AI can solve?
Companies need to understand real customer needs. If product managers are using ChatGPT, is it helping them understand customer needs that were overlooked? Many questions are not very clear unless you do a pilot test.
Next, consider whether to use your own engineers and data scientists to create the AI models, or to use an existing service like ChatGPT. Consider the pros, cons, and limitations of each.
Companies also need to establish best practices for their industry and consider the risks and regulatory constraints associated with using AI – and are those risks worth the benefits AI may bring?
