Predictive analytics and marketing go hand in hand. With predictive analytics, businesses can take massive amounts of data and transform them into actual insights which they can later use to improve their business results and make better data-driven decisions. For example, predictive analytics enable marketers to predict which customer will leave for a competitor or know which type of campaign to create to maximize conversion rates. By leveraging the power of their customer, advertising, and sales data marketers can understand what’s going to work and what’s going to fail. In turn, they can reduce A/B testing, improve conversions, and increase their overall ROI. So how exactly does predictive analytics enable marketers to reach their goals easily?

Firstly, marketers can use predictive analytics for campaign performance, where they aim to increase their marketing ROI and profitability by understanding which campaigns will work best, which campaign parameters will work best, and which customers and prospects to target in order to bring the highest conversions and sales. 

Next, marketers can use predictive analytics for retention. It is important to remember that retention is more than just retaining your most valuable customers; it’s also about acquiring more customers with the same characteristics and tendencies as your most profitable segment. 

When we leverage the power of predictive analytics for assessing and monitoring our CLV, we get insights that helps us increase retention, increase CLV, and optimize our customer acquisition. With predictive analytics, we not only understand but we are also able to maximize our results and profits. 

The three main reasons you should apply predictive analytics towards customer behavioral segmentation are personalization, influence, and results. True segmentation isn’t about what your customer buys, it’s about WHY they buy it. 

Lastly is sales forecasting. Predictive analytics technology helps digest and process massive amounts of historical customer data to help businesses predict sales outcome- whether the customer will make a purchase or not. 

When it comes to choosing the right predictive analytics platform there are three things you must always remember:

  1. Ensure the platform is easy, intuitive, and doesn’t require a single line of code
  2. Make sure the platform provides you with actionable insights in minutes, not months
  3. That the platform needs to be built on solid AI technology

Predictive analytics is key for businesses to improve customer experience, make better data-driven decisions, and gain the competitive edge they need in today’s flooded markets. But like diamonds, raw data must be processed correctly to be valuable. But when you do find the goldmine in the data, it’s worth everything. 

To read the full version of this article, download our e-book Predictive Analytics for Smart Marketers 101 today!