We discussed the importance of analytics to customer retention in a previous post. This post is a deeper dive into the subject. Research shows that consumers have higher probability to become more loyal customers to the brands / businesses they purchased from. For the businesses, if they are able to take advantage to collect and analyze important sales data, they can gain valuable insight to better their retention marketing strategies.
Following the STP strategy, which refers to segmentation, targeting and positioning, companies develop products and marketing initiatives to attract the most promising segments of consumers. But when it comes to customer retention, much less effort has been put to reach this goal. Having customers’ email addresses are simply not enough, businesses must learn to leverage additional customer data, such as browsing history, purchased items, and other demographic data that might be obtained to create a more tailored customer experience, which will then lead to better customer retention. To help our clients achieve long-term business profitability, we analyze over 300 different unique attributes so we can better predict customer churn, optimal engagement frequency to increase repeat purchase rate. We help them develop individually-targeted campaigns and avoid one-size fits all campaigns based on our machine learning algorithms. By marrying behavioral, demographic, sales and social data sets, our goal is to identify the most valuable customers and automatically provide the most relevant and personal engagement based on individual attributes. As a result, we are able to significantly increase conversion by more than 133% (measured against a control group) for our clients.