Predictive Marketing involves using sophisticated algorithms and cloud-based computing to make smarter marketing decisions and deliver personalized content to users based on their browsing history, goal-based actions and demographic data.
According to eMarketer’s “Predictive Marketing Roundup,” nearly 70 percent of U.S. marketers said predictive was the primary technology they planned to use in 2017. In addition, roughly half of marketing and media executives surveyed in North America said they believe predictive analytics and modeling to be one of the most helpful technologies for getting more value out of data.
Though still relatively new, Predictive Marketing is making waves because a whole gamut of leading companies in a wide variety of verticals are beginning to share their success stories from this approach. In fact, IBM’s data & analytics team feels that ‘predictive analytics will steal the show at the NRF’s 2017 Big Show. Examples of brands exploring targeted campaigns and behavior-based marketing abound all around us.
For example, in this article, L'Oréal USA’s CMO shares how the realization that consumers are looking for more personalized digital experiences led to the launch of Makeup Genius, a mobile app that allows customers to virtually try on makeup before buying one or more products.
A Harvard Business Review case study shares how an NYC-based Harley Davidson dealership boosted its qualified lead collection from one per day to 40 by using creative advertising content to target ‘look-alike’ customers using AI-driven technology.
On similar lines, in a pilot program, Macy’s is tapping into an IBM AI-assisted app that provides personalized guidance on product location and inventory at ten physical stores.
In the next few years, when processing capabilities are expected to increase exponentially and better techniques will become more accessible to digital marketers, intelligent marketing will probably become the hub of customer engagement. It’ll have a large role to play in the events industry as well since there is a huge potential to deliver meaningful, personalized experiences to participants using machine learning and intelligent matchmaking.