Over the summer I spent 12 weeks in Amazon working on shoes. Although Amazon is not that good (and they admitted it) at digital marketing, I'm still impressed by how they built up the email campaign system. 4 weeks of my work were dedicated to analyze the customer pool and pick up the right persons to send the right messages based on their history behaviors. Below is an article about how it works.
Amazon’s approach to email is centered on data and understanding the customer. This involves a number of steps. The first is to look at pace and frequency. If a customer has purchased every book in a particular series, Amazon will send that customer an email to alert them that the latest title in the series is out. But if that customer doesn’t open or respond to any of these messages, Amazon will slow down the frequency.
“You need to build in some filtering that captures those counts that speeds up or slows down based on customer receptivity to it,” said Donald Parsons, director of global email at Amazon, in a keynote at the Email Insider Summit today.
Cadence is also important to Amazon’s email program. While data might suggest that a customer is interested in ten different messages, Amazon won’t send all ten to the customer because it would be too much. “If I talk to you about them all at once they get garbled,” said Parsons.
To get it right, Amazon tries to combine multiple conversations under a common theme (otherwise it might seem random). For example, an email pushing good deals for the day could get away with selling TVs and toothpaste. “Get the conversation into the right context, so that it sounds like a chord rather than a bunch of keys on a piano,” said Parsons.
Relevance is also central to Amazon’s email program, but one of the challenges is figuring out what the right message, the right timing, and the right customer really are. “If I send you a great deal on a television set the day before you buy a television set, then that is a relevant message, but if I send it the day after you have purchased, it is the wrong message,” added Parsons.
Amazon is also big on throwing a wild card item into the email. While the company prides itself on using customer data to send relevant product recommendations, they also throw in something new to see how the customer reacts. “I don’t just recommend what I know you’ll like, I throw in one wildcard to see how you respond, to get to know you better,” said Parsons.
Amazon’s approach to email is centered on data and understanding the customer. This involves a number of steps. The first is to look at pace and frequency. If a customer has purchased every book in a particular series, Amazon will send that customer an email to alert them that the latest title in the series is out. But if that customer doesn’t open or respond to any of these messages, Amazon will slow down the frequency.
“You need to build in some filtering that captures those counts that speeds up or slows down based on customer receptivity to it,” said Donald Parsons, director of global email at Amazon, in a keynote at the Email Insider Summit today.
Cadence is also important to Amazon’s email program. While data might suggest that a customer is interested in ten different messages, Amazon won’t send all ten to the customer because it would be too much. “If I talk to you about them all at once they get garbled,” said Parsons.
To get it right, Amazon tries to combine multiple conversations under a common theme (otherwise it might seem random). For example, an email pushing good deals for the day could get away with selling TVs and toothpaste. “Get the conversation into the right context, so that it sounds like a chord rather than a bunch of keys on a piano,” said Parsons.
Relevance is also central to Amazon’s email program, but one of the challenges is figuring out what the right message, the right timing, and the right customer really are. “If I send you a great deal on a television set the day before you buy a television set, then that is a relevant message, but if I send it the day after you have purchased, it is the wrong message,” added Parsons.
Amazon is also big on throwing a wild card item into the email. While the company prides itself on using customer data to send relevant product recommendations, they also throw in something new to see how the customer reacts. “I don’t just recommend what I know you’ll like, I throw in one wildcard to see how you respond, to get to know you better,” said Parsons.
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