THINK Contributor

How predictive analytics empowers marketers

By , October 25, 2016

In a previous article, we saw how “predictive marketing” works: It unearths critical customer insights and helps marketers develop tactics to address the needs of individuals, rather than taking broad-based approaches that today’s audiences usually ignore. 

It does this by using analytics – advanced models and algorithms that analyze data to generate an almost intimate understanding of customer characteristics and demands. It infuses that understanding into the marketing process, so that each engagement is optimized for the individual customer or prospect. The data used provides marketers with a roadmap that allows them to invest marketing budgets in ways that appeal to specific customer segments and channels. That, in turn, drives marketing’s alignment with the brand objectives to acquire, grow and retain customers.

Of course, that roadmap’s value lies in the actions it generates. By themselves, analytics are like a screw without a screwdriver, capable of connecting components, but unable to accomplish anything by itself.

Today’s customers are demanding, impatient, specific, and not particularly loyal. We, as marketers, need to gain insights quickly, understand the customer’s level of attachment to our brand, and then take appropriate action.

Simplifying the Process

Yet in many companies, a number of hurdles stand between marketers and actionable insights. Sometimes, it’s a lack of reliable, comprehensive and up-to-date data in the first place, especially if analyzing data silo-by-silo with no or irregular integration, or if looking in the rearview mirror only, with no generation of foresight. Or it may be a process that relies on the availability of data scientists and puts your needs in competition with those of other departments. In addition, let’s just say it: Marketers today have too much to do and too little time to do it in. If we can’t get our hands on the insights we need quickly and easily, it’s nearly impossible for us to be proactive and keep our customers engaged.

In other words, marketers need hands-on access to intelligence about their company’s customer base, down to the level of individual customers. Looking not only at historical facts, but anticipating the future through an amalgamation of analyses. They need a system that analyzes their internal data, combines it with third-party information when necessary, helps them uncover new trends and empowers them to develop campaigns that target specific sets of customers based on their unique situation. And they need the ability to do this in as few steps as possible, without having to compete for resources.

A tool addressing those challenges would give marketers the insights they need to get in front of markets that are almost always in flux, a customer base that is demanding and impatient, and even identify which individuals are most likely to be engaged and satisfied, and which are likely to churn. The tool would combine speed, ease of use and continually refreshed data so marketers could get at customer intelligence quickly and directly, all so they can accomplish their goals more effectively, as soon as the need becomes apparent. And with that information, the marketer can take steps, if necessary, to reduce their customer churn rate.

To succeed, such a tool would be:

  • Designed from the marketer’s perspective: Easy to use and understand, able to provide a snapshot of customers and their behaviors at a glance, while also allowing for further exploration with no technical skills required.
  • Time-saving and timely: It would eliminate many, if not most, of the steps marketers now face to access and present the most important nuggets of what their data can tell them, even as the customer base changes on a regular basis. It would help them identify who to take action on, then feed that into their campaign system to execute right away.
  • Economical: If you’re with a smaller business, or a company that’s taking its first steps toward using analytics, you’ll need reasonable and predictable costs that reflect your business requirements. As your organizational readiness evolves, you want a solution that will grow with your needs, driving your customer engagements with ever-increasing sophistication. Or, even if you do have the data scientist resources in-house, they will be freed up to do exploratory analyses rather than supporting your standard yet priority needs.

Better Results in Less Time

Of course, it sounds great on paper. But how would this approach to predictive marketing play out in the real world?

Let’s say you’re the marketing manager for an online retailer, responsible for multichannel customer engagement. Despite your best efforts, customer satisfaction is falling and your customers are leaving before you can understand why. It simply takes too long to get at the data you need to develop better insights or is too difficult to compute.

The answer lies in having simple access to a snapshot of your customers that provides insights into things like their engagement, churn and lifetime value. 

For example, the tool might highlight the number of customers likely to become disengaged as well as the number of those whose risk of attrition has suddenly accelerated. With a few clicks, you’d be able to see details about the customers themselves and even generate a complete list of them for action taking. And, you’d do this at the moment you needed to – without putting in formal requests and waiting days or weeks for your answers.

Nowadays, that kind of speed and level of insight is essential. The marketing equation must be broken down into actionable components, so you can move from spotting a trend to getting ahead of it, matching the right offers to the right customers – fast.

Today’s marketers need a way to directly access advanced analytics. With it, they’ll increase customer satisfaction, grow customer lifetime value and improve retention rates, all while reducing time spent on analytics, leaving them to focus on their campaign strategies.


Learn how predictive analytics can be applied to turn your brand into a customer center organization at scale


Mark Feffer is a writer and editor who focuses on topics related to technology, analytics, technology, and workforce development. His most recent work on technology has been copywriting for the website of services provider INSYS Group (www.insys.com) and stories on the use of IT in recruiting and workforce management for SHRM Online and Dice Insights. Mark is a paid contributor to THINK Marketing.

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