Data-Driven and AI-Powered Marketing in 2019 and Beyond

By Daniel Raskin On Feb 20, 2019

The world of marketing has been shifting to a data-driven discipline for many years. Marketing Automation and Account-Based Marketing (ABM) have had a massive impact on how marketers implement strategies and have created a quantifiable approach to measuring marketing impact. For the most part, these approaches have analyzed data “after the fact,” providing a snapshot, which enables marketing practitioners to make assessments and derive decisions for the future. However, the next wave of marketing transformation will shift from having these activities occur after the fact to consistently triggering marketing events based on real-time transactions. This will require several fundamental changes in marketing approaches.

We live in the Extreme Data Economy, where we have moved from “point in time” analytics to continuous analytics that are constantly assessing customer activities. The next generation of analytics provides insights for business decisions in real-time, in the context of historical information, using Machine Learning for predictive analysis. Driven by the Internet of Things (IoT), next-gen marketing analytics will have to incorporate deep location intelligence and connect human and machine capabilities. To effectively achieve these things today, marketing platforms will have to undergo significant enhancements.

Data will become the centerpiece to the marketing function. As customer data come in, marketers will be able to apply campaigns to optimize engagement. They will have the ability to create rules and decision trees based on the analytics, compressing the time to get from data to insight. A marketer may have thousands of analytics constantly updating as someone uses their services, applying rules as the customer profile changes.

As customers engage with the marketing platform, the customer profile is constantly updating. The end result is the one to one marketing channel that enables organizations to do real-time engagement in-situ. For example, a customer, who liked a certain movie on social media, is now in store, and based on their location data, may receive a deal for the same movie’s branded merchandise. Real-time data analysis continuously yields new decisions based on the changing data.

To enable this new world, we will see the rise of the Marketing Data Scientist. This role will become an essential element of every marketing team. The Marketing Data Scientist will be focused on deriving detailed insight into customer behavior and producing reliable predictive and prescriptive insights based on complex data models and Machine Learning. These models will evolve from historical analysis to real-time applications that transform how product is delivered to customers.

For example, if the demand for rain boots spikes in usually sunny San Diego when unusual precipitation is in the forecast, marketing data scientists can build active analytical applications that trigger more products to be sent from warehouses in Nevada to stores in San Diego, instead of routing them to Portland as planned.

Additionally, incorporating AI will be an essential part of the marketing strategy. Trained models around predictive analytics, sentiment analysis, programmatic advertising, to name a few, will revolutionize how marketers automate more aspects of the marketing pipeline and develop highly targeted ABM strategies. This will require investment in new innovations and skill sets but will also lower customer acquisition costs by making marketing dollars more effective.

For example, in the realm of retail, having a real-time view of inventory can provide moment-to-moment insight on purchasing activity. A data scientist can use this data to run models that helps target demand generation by geolocation and product activity, and predict future trends that could impact inventory management.

By bringing AI, data science and continuous analytics to the marketing platform, organizations will not only have a snapshot of the customer, but also a sentient understanding of customer mood, actions and behaviors on a minute by minute basis. New advances in real-time customer analytics, location-based intelligence and AI will enable marketers to continuously assess complex customer data and automate complex queries with millisecond response times to serve up real-time advertisements, coupons, and promotions to customers in-situ in 2019 and for years to come.