How to Use Predictive Analytics to Satisfy Customers

By Anasse Bari, Mohamed Chaouchi, Tommy Jung

Global competition drives companies to lower prices to attract new customers. Luckily, predictive analytics can help here. Companies strive to please their customers and gain new ones; customers increasingly demand high-quality products at cheaper prices. In response to these pressures, businesses strive to deliver the right balance of quality and price, at the right time, through the right medium, to the people most likely to buy.

Customers’ experience of a product, if publicized through the power of the Internet — essentially a vast medium of communications — can make or break a business. Businesses that use predictive analytics can take advantage of the data they have to better understand their customers — to increase positive customer experiences while reaching out to attract new customers.

The Internet is a two-way street; companies have been gathering valuable information about their customers through transactional data that includes

  • Counting the number of items bought by customers

  • Tracking methods of payment used

  • Identifying customers’ demographics

  • Collecting customers’ responses to filled-out surveys

To complete the picture, other sources of information come from business operations — for example, the amount of time customers spend on the company websites and the customers’ browsing histories.

All that data can be combined and analyzed to answer some important questions:

  • What are the demographics of your customers?

  • What drives the sales of your products?

  • How can your business improve the customer experience?

  • How can you retain existing customers and attract new customers?

  • What would your customers like to buy next?

  • What can you recommend to a particular customer?

Any information that can shed light about how customers think and feel can bring insight to understanding them and anticipating their needs. Such insight has a direct impact on creating marketing campaigns. It helps shape the message of those campaigns and keeps them on target. Analyzing that data, businesses can provide their customers with personalized experiences, serve them better, and attract prospective new customers.

Such are the practical goals of predictive analytics. Guiding the pursuit of these goals with the company mission in mind will help your business and guide you every step of the way — from data collection about customers to data analysis, providing you with insights about your customers allowing you to make relevant recommendations, and identify potentially wayward customers whom your company will have to make an effort to retain.

Predictive analytics can also help improve your customers’ experience by enhancing such processes as these:

  • Creating successful marketing campaigns

  • Building programs to reward customers’ loyalty

  • Building recommender systems

  • Reducing operational costs

  • Delivering relevant service and products to your customers

Predictive analytics can also help you focus on identifying significant segments within your customer base — and make accurate predictions about their future behaviors. It can allow you offer relevant products to them with competitive prices, build targeted marketing campaigns, and enable you develop strategies to retain your customers and attract new ones.

Many online businesses use predictive analytics to manage customer relations. They harvest information about their customers, identify attributes that are the best predictors of customer behaviors, and use that information to make recommendations in real time. The result is that their customers get specialized and personalized service and attention, from marketing and cross-selling to customer retention.