It’s Tuesday morning and you’re running late. The good news is, you’ve been commuting for five years to your job so you know all the options for getting there fast. You quickly decide to drive a slightly longer route that you know usually doesn’t have a lot of traffic at this time of day. Sure enough, you arrive at your office just in time for your first meeting.
You made the right decision on how to get to work because you’ve learned from experience which routes to take on certain days of the week and at what hours of the day. That kind of thinking – discovering patterns in past events to predict future outcomes – is called predictive analytics. It’s what computers in the era of Big Data are doing every day and it’s revolutionizing the way we buy health insurance, find entertainment, and even predict presidential elections.
For digital marketers, predictive analytics promise to change forever the way brands target and interact with customers. Until recently, digital marketing data has mostly looked backwards. Entire campaigns were built around prime time TV ratings, clicks and, more recently, tweets. At a time when marketing to customers is customer-led and no longer campaign-led, predictive analytics help brands to design programs that are forward-looking and highly-targeted.
More data, fresh insights
This level of targeting is made possible by cloud-based data analysis software that just about anyone can leverage – not just highly specialized experts. Marketers can now easily experiment with sophisticated out-of-the-box predictive models, thereby gaining better insights faster through a more holistic analysis of various cross-channel data about user profiles and interactions.
With this new data in hand, marketers can collect and analyze the right measures (e.g., reach, conversion, loyalty) and user attributes (e.g., demographics, location, interests) that are relevant to their objectives. They can now focus their analysis to learn insights about what works and what doesn’t. For instance, with predictive analytics marketers today can:
Some Responsys customers are already using predictive analytics to gain better insights from historical data to increase the performance of their cross-channel marketing programs.
For example, an online retailer is using predictive analytics software, in combination with the Responsys Interact Marketing Cloud, to analyze user profile data and behaviors across email, e-commerce and other websites to generate propensity scores. These propensity scores are then used to identify customers who are more likely to purchase a product, and the marketing channels that are most likely to get their attention. A person with a high propensity score, for example, may receive a coupon via email, while a person with a lower propensity score may get a display ad to introduce a new family of products.
In closing, predictive analytics is fast becoming an integral part of every company’s digital marketing program. Here are a few points to keep in mind when incorporating predictive analytics into your digital marketing strategy: