A Researcher's Viewpoint on Where Mobile Growth Will Come from in 2020

What psychological and economic theory principles can you leverage to perfect your marketing collaterals? What works today? What will work tomorrow in a world of AR/VR, voice search, and AI?



To find out, in this episode of #GrowthHacking is Dead, Long Live #GrowthMarketing, I interview Harikesh Nair, chief business strategy scientist at JD.com and professor of marketing at the Stanford School of Business.

Nair got into marketing because it "is essentially now a field in which you can succeed only by bringing the analytical smarts, creativity, and data together."

At Stanford and JD.com, he has been applying scientific analysis to discover what makes users transact on mobile: "One way to think about the problem is to go to theories on how humans behave, to the applied psychology of engagement, to human-computer interaction models . . . ."

Both the academic community and the smart practitioner community have thought about these theories deeply for a long time, but a different paradigm has emerged with the collection of data at scale through digital models.

"Now, we don't need to rely fully on our gut feelings, or our intuitions, or our theories. We can simply look at data at the micro-individual level and see what this individual has liked, engaged with, disliked, said no to, shared, not shared, etc., in the past. Those touch points and behaviors are collected at scale and not aggregated but collected at the micro level."

"By looking at what you've done, I can essentially bring in the old economic idea that revealed preferences are superior to preferences. What you do is more powerful than what you say you'll do or what you'll express you'll do. So, by collecting that kind of data history, I can do intense personalization."

"Aggregating that data through machine-learning algorithms and large-scale, high dimensional, statistical algorithms, I can borrow some information across consumers. This information helps me understand what cuts across contexts, cuts across consumers, and does well for the average consumer."

In the future, Nair believes "we will get content that is not meant to be ads. We'll get content that is useful, tailored to you, completely non-annoying, and valuable, and AI is going to help us do that. "

"This evolution takes us toward a world of predictive advertising. For example, we will predict products and services that someone will need based on recent behaviors. We won't just say, 'This person likes casual games, so I'm going to show them another casual game because I've seen they use casual games and that puts them in a casual gaming category.' Be a bit more specific and say, 'This person likes casual games, and I'm noticing they're getting tired of playing the current casual game. Now is the right time to advertise a new one to them.'"

"Along that line are two other points," Nair adds. "What is content? What is advertising? That distinction is fast going away with native and things like that. It's important, of course, that what is paid for is appropriately labeled in a salient way as the FTC wants. They're sponsored, but I'm okay consuming sponsored content as long as it's useful for me."

"So, content is advertising, and advertising is content, and I don't think we need to worry about the distinction of which is which as long as it's disclosed appropriately and there is no deception."

"The other point is that the unit of analysis typically was a user, and the underlying assumption behind that is that a user is defined by a set of tastes. I'm a user. I'm Harikesh. I like black. I'm a price-sensitive consumer, so I would like to see value ads in every different context."

"But that notion is flawed. The real unit of analysis is a user-occasion combination. Me, Harikesh, on one occasion can like black and, on some other occasion or context, can like red. In one situation, I might be quite price-sensitive, but when it comes to my daughter's health, I'm completely price-insensitive; I'll pay anything to help that out."

"The power of digital is you can move the analysis away from a user to a user-occasion context, and you can see, "How has Harikesh acted in this context before?"
You can start to micro-target advertising content and other stuff to that level of the unit. Micro-targeting is imperative. It's already there in "best in class" forms, or it's coming."

This article was originally published on LinkedIn.

Aurelie is the founder and CEO of Akila One, a growth-focused consultancy helping CEOs of digital companies like IAC Applications, Deloitte, Rakuten Viber, Cheetah Mobile, and many others scale their businesses from 50 to 500.
Earlier in her career, she ran Cheetah Mobile's global B2B marketing and business development organizations, was instrumental in building QuinStreet toward its IPO, and brought SendMe to $120M annual mobile revenues. McKinsey-trained, she holds an MBA and an MSc in Engineering Chemistry.

Opinions expressed by the author are not necessarily those of WITI.