Analytics has long been the backbone of marketing success. Analytics enables marketers to make data-driven decisions, improve marketing campaigns and understand important customer behaviors. But analytics has evolved. And descriptive, or even predictive, analytics is now only a partial approach to true, data-driven marketing. While descriptive analytics helps brands understand the history of data and predictive analytics illuminates behaviors and flags patterns and opportunities for marketers, prescriptive analytics has become the real competitive advantage for marketers. Here's why.

Gain a Competitive Edge With Prescriptive Analytics

Prescriptive analytics is directly actionable by giving marketers recommendations on what steps they should take. For example, by identifying a trending product in a specific region, such as red wool coats, and recommending a red coat campaign to the marketer. Prescriptive analytics not only flags the trend but also gives marketers a “prescription” for what to do with the insights. It requires nimble responsiveness to data. If marketers aren’t leveraging prescriptive analytics in their marketing processes, they are definitely missing major opportunities to make a positive impact on the brand’s bottom line.

Marketers can leverage prescriptive analytics to create highly actionable campaigns that are much more relevant for their customers. Not only does this improve the overall customer experience, but it allows brands to launch highly targeted and timely campaigns, for example, campaigns that focus on trending products in certain regions of the globe so those red wool coats that might sell better in chillier climates don’t take up valuable shelf space. 

With prescriptive analytics you can also do things like:

  • Better manage store inventory by optimizing which and how many products are in a given store.
  • Help determine how to price and discount products and categories for different segments of customers.
  • Help marketers understand the optimal engagement mix for different customers (e.g., across email, direct mail, SMS, etc.).

Related Article: Bridging the Gap Between Data Analytics and Personalization

Don’t Discount Descriptive and Predictive Analytics Just Yet

Even though prescriptive analytics is the hot new trend, descriptive and predictive analytics are still important because they help organizations better understand customer behavior. If you don’t hear or address what your customers are telling you, you’re most likely missing out on opportunities and potential revenue as a consequence. Gettting a tighter grasp on customers' browsing behavior, purchasing trends, likes and dislikes, and more will help you predict and address their needs in advance, thus, enabling you to make individual customer’s experiences even more delightful.

Learning Opportunities

With advanced insight into your data, you can predict when a customer is about to churn, disengage or unsubscribe. Predictive analytics can also help marketers lower churn rates and unsubscribe rates. Knowing this in advance allows you to apply targeted and personalized reengagement campaigns to decrease churn and retain customers. However, as mentioned above, prescriptive analytics makes the data truly actionable. It can suggest how to take advantage of campaign opportunities, as mentioned in the “red coat” example earlier and mitigate risk of future decisions. Putting prescriptive analytics to work allows marketers to continually process new customer data to improve the accuracy of email and ad campaigns, personalization initiatives and more.

Advances in machine learning, AI models and algorithms have made prescriptive analytics possible, by analyzing very large data sets, making sense of the data and proving data-driven campaign recommendations to marketers. While no technology is perfect or fool-proof, without the right data, which has been cleansed, deduped, and stitched into a master customer record, prescriptive analytics can go haywire.

If marketers haven’t already integrated prescriptive into their analytics mix, they should definitely do so in order to deliver more relevant and effective campaigns that help make the retail supply chain more efficient, productive and financially rewarding.

Related Article: Artificial Intelligence Is the New Business Intelligence

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