he autonomous car dropped Lori at her home and then left for its scheduled service at the dealership. It would be back in time to take her to the airport the next morning. On the way into her house, Lori gathered the drone deliveries from the drop box on her stoop. The familiar voice of Eve, a next-generation smart assistant like Alexa, greeted her in the foyer and gently reminded her of the travel plans for her upcoming conference in LA. Lori hadn’t bothered to learn the details, since Eve had taken care of finding the best flight, seat, and hotel room that her company’s expense policy would allow.
As she unpacked her grocery delivery, Lori saw that Eve had adjusted her weekly purchases, omitting perishables and adding travel-size toiletries and sunblock. Calculating that Lori was running low on detergent (and aware she’d be coming home with laundry to do), the bot had ordered more but switched to a new, less expensive brand that was getting good consumer reviews. And, knowing that Lori wouldn’t want to cook, it had arranged for her favorite takeout to be delivered upon her return.
Thank goodness for Eve, Lori thought to herself. In addition to managing her shopping and travel, the bot tracked her spending and kept her costs down. Each quarter, for example, Eve checked all the telecommunications plans on the market and compared them against Lori’s projected data usage. Her current plan gave her the best price for her mostly evening and weekend usage, but with her brother’s 40th birthday approaching, Eve had anticipated a lot of data traffic among Lori’s friends and family and found a deal from an upstart firm that would save her money. That offer was instantly matched by Lori’s current provider, a company that had paid to be featured on Eve and to have the right to meet competitors’ prices. Lori relied on Eve for similar help with buying insurance, banking, and investment products, too. Sometimes she had to instruct her bot about her criteria and the trade-offs she was willing to make (for example, to forgo higher returns for a greener investment portfolio), but more recently, Eve had begun figuring out what product attributes she was after—even aesthetic ones—without having to be told.
Lori didn’t know how she had ever coped without Eve. She had come to trust the bot not just for advice on complex purchases but also to make many of her routine decisions and to introduce her to new products and services she didn’t even know she wanted.
Does this scenario sound far-fetched? It isn’t: All the technologies that Lori uses to interact with her world are either currently in development or already available—and being rapidly refined. Amazon, Google, Baidu, and other tech giants have launched artificial intelligence platforms with increasingly skilled digital assistants. While none have yet attained Eve’s sweeping capabilities, that is clearly their goal—and it’s just a matter of time before they get there.
AI assistants are rapidly colonizing consumers’ homes. Analysts estimate that Amazon, for instance, has sold some 25 million Echo smart speakers, which people use to engage with its AI assistant, Alexa, and that number is expected to more than double by 2020. Once you take into account the millions of other devices that can already host Alexa through iOS or Android apps, Alexa’s market penetration looks even higher.
Google Assistant, accessed chiefly through Google Home cylinders and Pixel phones, is now available on 400 million devices. Earlier this year Apple launched a Siri-enabled HomePod, and Samsung has acquired Viv, an intelligent assistant company founded by Siri’s creators, to bolster its Bixby AI assistant platform. Microsoft and Tencent have platforms for their own AI assistants (Cortana and Xiaowei), and virtual assistants Chumenwenwen and Xiaoice (which is capable of uncannily human conversations and reportedly has 40 million registered users) are already popular in China.
Over the next decade, as these firms and others fight to establish the preferred consumer AI platform, AI assistants will transform how companies connect with their customers. They’ll become the primary channel through which people get information, goods, and services, and marketing will turn into a battle for their attention.
AI assistants will help consumers navigate their increasingly overwhelming number of choices. Every year people buy from thousands of product categories, deciding among dozens or hundreds of options in each. Even routine purchases can be time-consuming; nonroutine purchases often require sorting through the nuances of competing offers and are fraught with risk. While shopping for shoes may be fun, picking the right toothbrush from more than 200 products is pretty tedious. Choosing the wrong tennis racket can ruin your game, and buying an ill-considered cell phone plan or insurance policy can be costly.
AI assistants will not only minimize costs and risks for consumers but also offer them unprecedented convenience. They’ll ensure that routine purchases flow uninterrupted to households—just as water and electricity do now—and manage the complexity of more-involved shopping decisions by learning consumers’ criteria and optimizing whatever trade-offs people are willing to make (such as a higher price for more sustainability).
Consumers’ allegiance will shift from trusted brands to a trusted AI assistant.
The effects on the business landscape will be far-reaching. Technologies that revolutionize the way consumers interact with a marketplace also tend to reconfigure its dynamics and reshape the companies that sell into it. In the 1950s, for instance, the rise of supermarkets made scale and mass media much more important to marketers, triggering a wave of consolidation among consumer goods companies. AI platforms and assistants will likewise change the game for brands and retailers, altering the relative power of players in the value chain and the underlying basis of competition.
These predictions grow out of our ongoing research into the ways technology has been redefining relationships among customers, brands, and firms. In the course of it, we have reviewed hundreds of relevant academic, industry, and news articles, and held in-depth discussions and structured interviews with industry experts and executives at Google, L’Oréal, EURid, and other global businesses. (Ivey Business School graduate student assistants Gobind deep Singh and Vivek Astvansh helped us with the early literature reviews.) In this article we’ll outline in more detail the near-term changes we expect AI platforms to bring about and explain the implications they hold for marketing strategy.
Marketing on Platforms
Once the dust settles, we expect that just a handful of general-purpose AI platforms will be left standing. Most consumers will use only one, whose assistant will be incorporated into their homes, cars, and mobile devices. The platform will gather and deliver information, and the assistant will be the consumer’s interface with home systems, appliances, and other machines. The assistant will also be the portal to an infinite shopping mall of goods and services. The more consumers use a platform, the better it will understand their habits and preferences, and the better it will meet their needs—increasing their satisfaction in a self-reinforcing cycle.
The Coming Platform Shakeout
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. The concentration of those functions within a few platforms will give their owners enormous clout, and branded products will find themselves in a weaker position. Consumer companies that feel that large retailers like Walmart wield too much power today will be even more alarmed by the might of AI platforms. As a major—or even primary—means of communicating with consumers, and the repository of reams of data about their habits, preferences, and consumption, the platforms will have a lot of influence over prices and promotions and the consumer relationship itself.
Brands today owe their success to their ability to signal quality and win buyers’ loyalty. But in a world of AI platforms, marketers may find that consumers like Lori shift their allegiance from trusted brands to a trusted AI assistant. The activities that help brands cement relationships with buyers over time—understanding and filling people’s needs, assuring quality, and consistently putting consumers’ interests at the center—will in many cases be performed better by AI. In fact, we predict that AI assistants will win consumers’ trust and loyalty better than any previous marketing technology. We therefore expect the focus of many brands to shift from reinforcing direct relationships with consumers to optimizing their positions on AI platforms. However, in selected cases it may still make strategic sense for brands to maintain strong ties with consumers outside the platforms.
These changes will have an impact on companies at three critical levels: customer acquisition, satisfaction, and retention.
With consumer data now being used to create finely targeted marketing, customer acquisition has become ever more efficient. Still, marketers’ aim is far from perfect. Ads continue to be directed at consumers who aren’t good prospects—and don’t reach everyone who may be interested in an offering. Even when an ad does find the right audience, its message is often blunted by consumers’ cognitive limitations: People might need to see the ad many times before it registers or may forget it entirely. They may remember only the parts that interest them (for example, the humor) but not the product’s name or distinctive promise.
Those problems will matter less in the coming years, when the main target of the billions in annual spending on brand marketing will shift from forgetful, biased consumers to AI platforms that retain every last bit of information. Platforms will analyze that data, taking into account products’ pricing, characteristics, past performance, and reviews (weighted by authenticity and relevance) and the consumers’ preferences and past behavior. Customer acquisition will become even more of a science and will focus on a single channel—the platform—rather than on multiple channels.
In this universe, influencing the platforms’ algorithms will be the key to winning. It will be crucial for companies to understand the customized purchasing criteria that the AI applies on behalf of each consumer. Sellers will probably have to pay platforms to get that information—and to be “listed” on them, in much the same way that brands now pay shelving fees to brick-and-mortar retailers. Marketers can also expect to bid on or otherwise pay extra for preferential positions, just as hotels today bid to appear at the top of the results on Expedia, or marketers compete in Google’s AdWords auctions to come up first in searches. Though Amazon says it has no plans to add advertising to Alexa, CNBC has reported that the company is talking with several consumer goods firms about promoting their products on the platform. Experiments “in the works,” said CNBC, would allow Alexa to make product recommendations based on a user’s previous inquiries (“How do I clean grass stains?”) or past shopping behavior. We believe that product placement and recommendations on AI platforms are inevitable and will, in time, be a major source of revenue.
In different ways, all these payments will be for access to the consumer. Companies will essentially reallocate to the platforms what they spend today on advertising, listing and slotting fees, and retail commissions. Brands will shape their offers and innovation strategies around getting AI assistants to showcase their products.
Customer acquisition will become even more of a science.
The bustling ecosystem that now helps companies woo customers, including ad agencies and media buyers, will need to learn to market through AI platforms. Marketing services that target platforms will be even more accountable than media buyers are today and will need to show links to actual consumer behavior. Traditional market research may be supplanted altogether by the intelligence about consumers’ actual behavior that brands will be able to buy directly from platforms.
Customer satisfaction drives loyalty, word of mouth, market share, and profitability. No wonder marketers are fixated on monitoring it. Imagine, then, a world where reliable satisfaction data is easier to get from AI platforms than from consumers themselves.
A platform serves consumers by constantly anticipating their needs. To do that it must collect granular data on their purchasing patterns and product use and try to understand their goals: Do they want food products to improve their health, energy products to minimize their environmental impact, and financial products to increase their long-term returns? Or are their criteria taste, price, and short-term performance? Sophisticated AI platforms will go further and figure out the trade-offs consumers are willing to make: How much more will they pay for a more healthful product? How much room in a car will they sacrifice to get better fuel efficiency? AI platforms will even know whether consumers are likely to adapt their requirements in different contexts—for example, if a person on a diet will make an exception for dessert when celebrating.
Because of all this, AI platforms will be able to predict what combination of features, price, and performance is most appealing to someone at a given moment. Ultimately, AI assistants may be able to satisfy customers’ needs better than the customers themselves can. Relatively primitive recommendation engines are already moving in this direction, suggesting books, movies, and music that consumers didn’t know they would enjoy.
AI platforms will lead to more-efficient sorting and matching in the marketplace. Consumers who prefer the Four Seasons, for instance, will be unlikely to be offered reservations at a Trump hotel by their platforms. So brands will want to sharpen their positioning in ways that the platforms will register.
Marketers assume that repeat purchases indicate customer satisfaction and are a sign of brand loyalty. Yet many customers keep buying a product not because it delights them but because they can’t be bothered to explore alternatives if a brand is performing adequately. Put simply, most people have better things to do than evaluate the ingredients of laundry detergents. An AI assistant, however, does not. It can regularly reassess all brands in any category, whether laptops or chewing gum, and recommend a new one that might serve the consumer better. Some consumers may even like to switch things up just for the sake of variety—so their assistants, being aware of that, will periodically recommend new products they might like.
That routine reevaluation of purchases will force incumbent brands to constantly justify their positions. But it will also open opportunities for challengers. Competition will get more intense.
Though incumbents will need to innovate to hang on to customers, they’ll be able to buy information from platforms that will help them inhibit brand switching. If a brand knows that a consumer is likely to defect (say, because she has indicated a desire for change to her assistant), it can compute retention metrics in real time to see whether she’s worth keeping. If she is, the brand can make her a customized offer that reflects exactly what she needs to stay put. If the consumer accepts it, both she and the brand win: The brand keeps the business and the consumer gets a better deal. The AI platform is in the middle, serving both in ways that create value for each while generating revenue for itself.
On their part, challenger brands can use intelligence from a platform to acquire customers. Promotions through AI assistants will be the tool of choice for upstarts. Of course, once a challenger breaks in, it will be subject to threats from the incumbent and other rivals. The secret to competitive differentiation—and, hence, retention—will be constantly designing offers that meet a customer’s evolving criteria. For brands, this will become as much a focus of innovation as developing better products is.
The Imperatives for Platforms
AI platforms will succeed only if consumers have faith in them. As one platform leader at Google told us, “Building trust will be the most important thing we do.” To earn consumers’ confidence, platforms must ensure three things: accuracy, alignment, and privacy.
By continually learning each individual’s desires and requirements, the platform algorithms will hone their ability to please consumers. If a platform can recommend an alternative to a trusted brand that it thinks the consumer will like better, and the consumer is happier with the alternative, that platform will supplant the brand as the object of her trust.
There’s a built-in conflict of interest that platforms must manage carefully. On one hand, they must single-mindedly focus on meeting consumers’ needs; if they fall short, it will erode trust. On the other hand, they’ll have contractual arrangements to provide preferred placements and consumer data to brands. If people sense that an assistant is pushing a paying brand that isn’t aligned with their needs, that too will undermine trust. One solution might be for platforms to be transparent about their relationships with brands, just as Google is today when it identifies some search results as ads. Another may be to give paid and unpaid recommendations equal weight; if a consumer asks an AI assistant how best to remove grass stains, the response might include both a paying bleach and a comment that generic bleaches can be just as effective. The brand gets its plug, and the assistant demonstrates that it’s trustworthy.
Platform owners, as well as marketers, will need to strike a careful balance between the use of personal information and AI performance. The more data gathered, the more accurate the platform—but the more exposed consumers may feel. A solution here could be to offer customized privacy settings, as Facebook now does, giving users control over what information they share and how widely. Another, less satisfactory solution might be to argue, as Google sometimes does, that privacy is protected because consumer data is handled by machines without human intervention.
All consumer-facing firms can expect AI platforms to radically alter their relationships with customers. Their traditionally crucial assets, such as manufacturing capability and brands, will become less central as consumers’ attention shifts to AI assistants, and the value of consumer data and AI’s predictive ability soar. Push marketing (getting platforms to carry and promote a product) will become more important, while pull marketing (persuading consumers to seek products) becomes less so. The consumer will remain the target of brand-building efforts, but marketing that encourages trial and repeat purchases will be more effective when aimed at AI. Though the marketplace will be more efficient, companies will encounter intense pressure to offer consumers the best deal—the one most closely aligned with the preferences identified by AI gatekeepers.
For a long time, consumer goods companies, used to maximizing economies of scale because of their large fixed investments in production and brands, have zeroed in on one strategic question: How much more of our product can we sell? AI platforms will present a very different opportunity: to maximize the depth of the relationship with the consumer by offering a wide range of products—in other words, economies of scope. Investments in building trust with consumers and their AI assistants will be amortized by asking, What else does this buyer need? Superior marketing strategy will still matter—firms must acquire, satisfy, and retain consumers in the AI world—but what it involves is likely to change substantially.
A Product Manager with expertise in pharma marketing and sales operations