Guessing what individual customers want, via researching large demographic populations, is no longer a viable marketing strategy. Right now, some of the largest tech companies, such as Amazon, Facebook, and Google are investing money in machine learning and artificial intelligence (AI) to predict what each of their customers want—even before they know. And with the consumer more connected on more devices at all times of the day, there’s more data available to collect and analyze.
Today’s marketers have more opportunities to analyze content and data to deliver campaigns that would benefit the marketer, but more important, the consumer. Smarter marketing strategies should also make room for more hypertargeted services offered to the consumer. Creating well-informed, relevant, and timely options that don’t interfere with private digital spaces and respect the consumer’s time and consideration will be a demand that will only increase.
Convergence of virtual assistants and AI-based advertising
Marketers can better reach their audience via virtual assistants that would learn a great deal about customers. AI integration in the virtual assistant will allow for a smart lens while people shop in their favorite apps. For example, the “related products” feature in mobile shopping apps will become a new opportunity for brands, as they are able to aggregate and analyze how, when, and what a shopper was looking at over a period of time to understand their interests with more precision. AI can help marketers create the following types of virtual assistants:
Human-like mobile recommendations. Asking your mobile shopping app for recommendations typically results in offers that are motivated by advertising and marketing goals, which often doesn’t benefit the mobile shopper. A mobile shopping app that mimics the qualities of a seasoned salesperson would allow users to express their personal needs, wants, and constraints with a highly graphic, interactive interface that provides the best possible recommendation.
Personalized mobile discovery. Discovery solutions vary tremendously. A mobile consumer may find a new product by conducting research, using referential past searches, or taking other consumers’ recommendations. One discovery method for mobile apps with AI is based on a series of questions and answers, resembling an interactive social process we do when talking to an expert or a salesperson. Another method might be using multiple signals based on past and current behavior for the customer and even other customers’ behaviors powering a deep profiling effort that provides instant results without any research needed.
Virtual shopping assistants. A significant amount of mobile users don’t have the time to shop, keep up with trends, or monitor good deals and opportunities. By combining deep personalization, advanced recommendations, and discovery with a virtual assistant that can keep track of individuals’ preferences, needs, and wants, mobile apps would be equipped to alert the shopper precisely when something relevant turns up and advise them when shopping. This type of “smart” retail app, in turn, makes it possible for brands to create a personal relationship with customers and is perhaps the beginning of an increasingly brand-focused Internet.
This way it’s also possible to create better ads through more intelligent profiling of users in an anonymous way. This wouldn’t necessarily take existing ad technologies out of the equation for some time to come, but it would vastly improve relevancy and trust in ads. This is especially true for ads coming from a virtual assistant—they might not even be considered ads if they were relevant enough and wouldn’t be shown to the user too often.
Building trust in advertising via virtual assistants
There’s a potential for building more trust in advertising and it lies within the AI-powered virtual assistant. We’re already seeing marketing-driven apps powered and managed by individual consumers who self-serve by doing all the work a salesperson would help them with in-store. New AI-powered virtual assistants will exist to make consumers’ individual lives more organized and improved—to take advantage of every discount, say, or to alert them when they’re hitting their monthly spending limit. By using a Virtual Assistant app for advertising, the app can function as educational to consumers rather than feeling invasive, like other outdated forms of advertising, transforming the platform into a valuable service for the customer.
Because users will want their assistants to help them optimize their lives, they’ll be willing to share lots of information with it. This way, marketers will be receiving a current, steady stream of relevant information while the assistant collects and learns how consumers behave, what they’re doing, and what they want. Once this assistant has proven its relevance, users will trust it as an authority on the possible opportunities for themselves. When such rich context is incorporated into the virtual assistant relationship, the possibility of marketing and advertising strategies being delivered in small doses will be immensely impactful, because of the deep understanding our assistants will have in place. It will take a while for advertising to become as mature and thoughtful as this, but the AI virtual assistant tool is a key to its future.
Martin Rugfelt is CMO at Expertmaker
