Niraj Dawar is a professor of marketing at the Ivey Business School and the author of Tilt: Shifting Your Strategy from Products to Customers (Harvard Business Review Press, 2013). He is the author of Marketing in the “Age of Alexa,” Harvard Business Review, May-June 2018.
How does marketing change in the “Age of Alexa”?
Right now, worldwide, the top 6 food and beverage companies spend close to $40 billion advertising to individual consumers to remind them to buy their brands at the grocery store. The consumer consumes these products at a regular rate, reminded periodically by brands through media to consume and enjoy the product, and to stay loyal to the brand.
That’s one model of marketing.
With AI in the picture, we begin to see the automation of shopping. AI starts discerning patterns of consumption, the contextual needs for different products, and starts adjusting inventory based on consumption rates. This allows the 200 to 300 products that consumers use at a regular rate to start flowing to their houses like electricity.
What we are saying is that AI “assistants” will control access to your customers, and brand recognition will play less of a role in product selection than AI algorithms will. Brands will have to decide if traditional advertising model is worth it, or should that $40 billion be spent elsewhere, on AI platforms for example.
How do AI platforms create value for consumers?
AI platforms will help customers navigate the increasingly complicated landscape of consumption. The AI platform will be our loyal companion as we navigate through this endless shopping mall – it will become our sextant, our navigation tool. We cover this in detail in our article, which your readers can access online.
What do brands have to do to stay relevant on these platforms?
Brands will have to understand that they are not just marketing to humans anymore. Simply doing consumer research to understand consumer behavior is not sufficient anymore. The first thing brands must recognize is that platforms have available a lot of highly relevant data related to their consumers – past purchases, history of consumption, history of choices, history of preferences – information like: What did they buy when their favorite brand was not available? What did they buy under different types of contextual cues? That’s the sort of information now stored, analyzed, and available via AI platforms. Brands will need to learn to plug into this data in real-time to serve their customers. We explain that marketers’ current obsession with creating an omnichannel customer experience will fade as AI platforms become a powerful marketing medium, sales and distribution channel, and fulfillment and service center—all rolled into one.
So what happens when the platform decides to “private label” everything?
That’s a very likely risk for brands. One of the fastest growing consumer brands is Amazon’s private labels, a huge risk for brands. What happens when the AI assistant becomes the trusted navigator? Brands have to ask: will consumer allegiance shifts from trusted brands to a trusted AI assistant? As private labels have shown the ability to siphon-off margins in the physical space, we have to ask how much worse will this get in the digital world? The AI assistant can sway consumer opinion at the moment of sale.
What are the issues facing AI platforms after the Facebook scandal? What happens when AI can predict what you want better than you can?
There’s a tradeoff in privacy issues – that consumers give up some data in exchange for convenience. So this tradeoff is amplified on the AI platform. We will hear about privacy more and more. And we will be faced with this question: Do you really know the tradeoffs that you are making?
Is there room for customer-centric AI, where the platform works for the customer (as an infomediary), and not for the vendor (Amazon, Apple)?
I think what you are getting at is that as the privacy tradeoff becomes more important, there will be some segments of consumers that will continue to share data, and their will be others who pay to not share their information, and still others that say I want benchmarking data from 400 million other consumers, but I don’t want my data to be part of that pool. So you’ll have different levels of membership, with varying degrees of participation.
So some consumers will stay anonymous and still get the benefits from the crowd… Thanks so much for your time.
INTERVIEW by Christian Sarkar