Ömer Artun and Dominique Levin says, “Propensity models, also called likelihood to buy or response models, are what most people think about with predictive analytics. These models help predict the likelihood of a certain type of customer behavior, like whether a customer that is browsing your website is likely to buy something. This helps marketers optimize anything from email send frequency, to sales staff time, to money, including discounts.

For example: Online pet pharmacy PetCareRx has served pet owners for more than 15 years. It sells many products that customers have to reorder at varying times from three months to 12 months. Like most retailers, PetCareRx took a one-size-fits-all marketing approach, offering a set calendar of discounts and promotions to all customers. But not all customers are alike and many are looking to buy at different times of the year.

Using predictive analytics, PetCareRx was able to differentiate discounts across customers, leading to higher sales and retention without increasing costs. Customers were ranked according to their likelihood to buy“.

How to Use Predictive Analytics to Understand Which Consumers Are Most Likely to Buy

HubSpot

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