To drive growth, stop chasing intent and start building an intelligent engine to observe customer signals and predict what people actually want. Brian Solis is an award-winning author and influencer who has worked with celebrities including Ashton Kutcher, Shaq, and Oprah Winfrey.
Customers are connected and mobile-first, and they’re in control of their journeys and experiences. The pace of change for consumers and technology has never been faster. Yet, brands are still chasing customer intent through traditional means. The good news is that because of digital, customer signals give away exactly how to better serve them in every moment throughout their journey. Furthermore, in an era of machine learning, marketers can finally shift from trying to keep up with customer intent and instead, predict it.
Traditionally, marketers aimed to figure out what consumers want. They ran campaigns based on that research, tracked activity and improved on that experience. However, mobile has completely disrupted customer journeys as we’ve defined them over the years. They’re now mobile first, incredibly fragmented, with hundreds of touch points and micro-moments that make up the path to purchase. As a result, customers expect immediacy, personalization and assistance at every step.
If marketers want to win, if they want to grow, they have to do better than just chase intent on “demographics and remarketing.” That’s not enough anymore. With the right mindset, customer data and machine learning, brands can tap into real intent via search, across the funnel, across media, at any touch point.
For example, when someone reaches for their mobile device and begins to search for answers, they explicitly communicate intent. With so many touch points, signals and clues, combined with machine learning, brands can translate signals into predictive actions that deliver value-added personalization and assistance that customers expect.
Predicting intent via machine learning represents a game changing opportunity. And, this next-level digital transformation in marketing is already underway. In a recent research report published by Google and MIT SMR, for instance, nearly three quarters of marketers believe that their current functional KPIs could be better achieved with greater investment in automation and machine learning technologies. Looking ahead, 63% of organizations indicate they are making investments in automation and machine learning, while 85% of Measurement Leaders are prioritizing this technology.
Marketers must start with growth in mind and stop marketing to average. That means understanding customer value, and marketing to that value accordingly with unique messaging and experiences. By understanding true customer value over traditional metrics such as reach, views and conversions, marketers are positioned to directly drive growth rather than trying to connect the dots between traditional metrics and whatever business result they ultimately want to achieve.
Modern marketers are segmenting by value to acquire and retain the best customers. That takes real-time insights that translate evolving customer data points and signals of intent into value-added segmentation and engagement models. Marketers must also emphasize business-centered metrics, such as NPV (net present value), profit, and CLV (customer lifetime value).
Now, marketers don’t have to settle for just using demographics and waiting for remarketing. Consumers expect more, and brands can deliver more, by predicting intent throughout the journey, across media.
With the right formula or business frame (focusing on outcomes + customer value + automation/ML) marketers can optimize a growth engine in service of what actually matters to customers.
To drive growth, stop chasing intent and start building an intelligent engine to predict what people actually want.
