Meredith Nolan (MBA ’26) connects with Ayelet Israeli on how GenAI is transforming how companies and consumers connect.
What is the best boot for the fall? A fun restaurant to take a group of friends on a trip to New York? For years, consumers would simply “Google it.” Today, young consumers search in an entirely new way – on Tik Tok or ChatGPT. Said differently, we're in the midst of a consumer journey revolution. While every industry tries to understand the multidimensional impacts of AI, for consumer companies, there is no greater issue to understand than the changing nature of consumer acquisition and engagement. I had the opportunity to sit down with Professor Ayelet Israeli, who has spent over a decade researching the role of data and technology in marketing, to understand her perspective on the evolution of marketing for today’s consumer companies.
What was the journey that got you where you are today, and how did your background shape your focus on data and technology in marketing?
It started in 2009 when I was getting my PhD in marketing. I had moved from Israel where e-commerce wasn't that developed at the time. It was during the formidable years of e-commerce and omni-channel, and a general redefining of the retail experience. For me, marketing was such an exciting and interesting world to go into. Even between then and now, so much has changed. We have so many new channels to get to consumers. There is more and more technology that makes it easier, on one hand, for a marketer – and harder on another. This creates exciting opportunities, but also a number of challenges.
As we consider the technological changes of today, and specifically the new age of AI, does it feel like we are undergoing a more significant shift in how companies and consumers engage?
The introduction of even the earliest version of ChatGPT 3 was such a shift in technology relative to what was available before, and to our imagination of what AI can do versus what it actually does. Since then, the rate of innovation, and specifically, more creative, more exciting technologies, has been so rapid that it feels like we're entering an age of faster technological change. Will it continue to be this way? It seems different in several ways, compared to the digital marketing revolution of fifteen years ago.
What are some of the similarities and differences to the digital marketing revolution that can help contextualize how GenAI has disrupted the consumer landscape?
When digital marketing first started and when people started using Facebook, all of the traditional agencies had to figure out, ‘How do I deal with this new creature?’ And in some sense, that's similar to today. We are trying to understand the impact of AI and how companies can and should be employing strategies with it to better reach and serve consumers. But on the other hand, I think it's easier to imagine the replacement of a lot of different jobs that just a few years ago we believed can only be done by humans. In that way, it feels like more than just a shift in format. Today, I can imagine an entire creative process happening by itself that was not before, which has created a greater sense of urgency to figuring out these new technologies.
That said, pre-COVID, there was this strong belief, especially in the retail space, that retail was dead. However, what we found instead was that people still want physical, human experiences. At least in the medium term, there is still a craving of the human experience that GenAI cannot fulfill.
How has consumer discovery evolved with the popularity of new platforms like Tik Tok and AI chat bots like ChatGPT?
Consumers are shifting their discovery, leveraging either TikTok or AI assistants. The challenge for brands is the power that these platforms have. We do not know exactly how recommendations are being generated, which has created in some way a “black box” for brands to now try to navigate.
It is an ongoing area of research, with many considering how to ensure that the GenAI actually brings my product to the top. For example, research conducted by HBS’s own Aounon Kumar and Himabindu Lakkaraju tested how companies can optimize their content for large-language models (LLMs). Using the example of a fictitious coffee maker, they developed an algorithm that tells the company what to add to the description to increase its likelihood of being recommended by the LLM. So, there's going to be a whole new field, just like when SEO and SEM were popularized by Google, of, how do I optimize for these large language models?
What are some of the risks that brands must navigate with this shift in consumer discovery?
Companies must consider brand safety in the age of Gen AI. Because of hallucinations, because of user-generated content from IP imagery, it has become very important to think about brand protection. How do we think about metrics such as brand health in these large language models? In truth, this work is very nascent. How should marketers think about measuring metrics like conversation about brand? In the age of social media, there is social listening and scraping, but how do we do this with Gen AI? It is still all very uncertain.
GPT has also been changing inquiry. The questions consumers are now asking search engines – framing inquiries as questions – are a better fit with Reddit results. This presents an exciting opportunity for SEO and SEM. However, it also reiterates the importance for consumers to think critically about the results they see. We used to trust at least the top few results from Google. However, today, we need to re-learn and re-educate people that results may now be coming from a Reddit forum. These models are so good at giving you an answer, but are we becoming overly trusting of the answers? How do we ensure people employ critical thinking?
How can companies manage organic and word-of-mouth marketing as it becomes an increasing source of “truth” for consumers?
So, it's almost impossible for brands to manage (rather than react to). It's also becoming harder and harder to detect what is true and what is not true, especially when we're talking about language models and AI-generated content. Maybe the solution will have to be technological, something that is certified AI versus not. Similarly, with influencers on social media, there has also been a cycle. At first, consumers were skeptical, but now they have become a source of truth and authenticity (at least to some consumers).
How do you think about competitive differentiation in this new era?
A competitive advantage for companies can be creating a strong emotional connection with your customer. It is difficult for technology or AI to be your sustainable competitive advantage, because. the time and cost to create has been so reduced that it is difficult for technology or AI alone to be your advantage.
What is the opportunity in consumer discovery with these new technologies?
I think overall discovery is going to become more challenging, because of the power of the platform and the role that GenAI is increasingly playing in search. However, there is an opportunity for companies to better personalize their own websites that allows, through engagement, to figure out the right product for you. We have already seen some examples of this. Ulta Beauty allows consumers to take a picture and receive personalized recommendations for products. Companies can also consolidate reviews into insights thanks to GenAI.
As a result, GenAI allows companies to derive more power from the data that they already have, utilizing it in a way that provides more relevant recommendations once a consumer reaches a brand’s website. There is this promise of “segment of one,” hyper-personalization that hopefully we can get closer to with these new AI-technologies.
Can you talk about your own research on how GenAI can be used to derive insights on consumer preferences?
We have been thinking about how to leverage Gen AI for different parts of the customer journey. My particular research is around how I can use these models to learn something about consumers. They're mostly trained on user-generated content. Maybe this user-generated content actually has some signal about what consumers are interested in, and we can use it as a way to learn about preferences.
We essentially simulate a customer survey using GPT and other large language models, asking survey questions as if it is the consumer, to estimate willingness to pay and preferences. Then, we match it to human surveys and see how much they agree or disagree. We have learned that for several categories, we can actually get pretty meaningful and realistic measurements of willingness to pay.
I wouldn't say it's time to replace all wholly human consumer surveys with GPT. But I think it's an exciting opportunity. In brainstorming and ideation, you can use these models to gain at least a signal of which idea of five ideas, for example, is the best one if I emulate this conversation with customers. We conduct conjoint studies to estimate customers’ willingness to pay, and then figure out which idea is actually worth pursuing, helping innovation and ideation before investing in R&D.
Are all companies equally able to deploy these technologies, or are certain consumer companies better positioned than others?
All companies can technically do this. Different models have different results based on the data they are trained on. However, in general, you can get pretty consistent results across all three models. That said, if you give GPT early surveys of your own target market, it is better at predicting their future preferences. As a result, there is value to having your own unique data on your consumers. An example of a company doing something similar to this is Kraft Heinz, which has used a combination of social listening (scraping social media websites) with GPT to generate insights.
What is your overall outlook on the changing consumer landscape?
It is an exciting time. The speed of innovation is so fast, so I am not going to make too many predictions. There are a lot of risks, but also exciting opportunities. The fact that it is so easy to do things that used to be costly and difficult is exciting, but of course, companies still need to develop a compelling value proposition, an actual product, and figure out how to talk to and delight their consumers.
Meredith Nolan (MBA ’26) is originally from outside of Washington, D.C. She graduated from the University of Virginia with a BS degree in Commerce in 2020. Prior to the HBS MBA, Meredith worked in private equity in San Francisco on TPG’s Consumer team.
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