Modern marketers often frame their role as developing customer-centric marketing strategies to maximize some metric of importance, such as response rates, ROI, or cost per acquisition (CPA). Predictive models are analytical tools that provide us a formal way for maximizing (or minimizing) those metrics. This post is Part I in a series offering a deep dive into how predictive models are developed and can be used in new customer acquisition.
Speedeon Data Blog
One of the common challenges facing today’s marketers is an abundance of customer data but the inability to translate that data into actionable insights. This is especially critical when deciding on which customers to focus your marketing resources. For most businesses, acquiring customers is at or near the top of their priority list. Acquiring new customers is not that difficult though. Acquiring profitable, long term customers is the real challenge. But where to start?
If you’re like most marketers, you’re probably trying to get greater visibility into the key factors that drive purchase decisions and impact customer behavior for your brand or product. This can be a challenge though as most of our purchasing behavior is habitual in nature. Shopping habits are likely to shift, however, while consumers are experiencing major life events such as college graduation, marriage, the birth of a child or purchase of a home. Ads featuring timely and relevant marketing messages can impact a person’s shopping habits for years to come.
New customers are an essential part of any business. For years, marketers have struggled to identify which group of people are best to direct their marketing efforts at. New technology has made that process easier than ever before.