{"id":1975,"date":"2020-03-26T15:31:43","date_gmt":"2020-03-26T15:31:43","guid":{"rendered":"https:\/\/www.hustlermarketing.com\/?p=1975"},"modified":"2025-10-01T17:30:44","modified_gmt":"2025-10-01T17:30:44","slug":"email-marketings-sixth-sense-how-to-benefit-from-klaviyos-predictive-analytics","status":"publish","type":"post","link":"https:\/\/www.hustlermarketing.com\/blog\/email-marketings-sixth-sense-how-to-benefit-from-klaviyos-predictive-analytics\/","title":{"rendered":"Email Marketing\u2019s Sixth Sense: How to Benefit from Klaviyo’s Predictive Analytics"},"content":{"rendered":"

Predictive Analytics is an amazing way to surprise your customers and generate more sales. It predicts each customer\u2019s next order date automatically using an \u201cexpected date of next order feature.\u201d<\/span>
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\n<\/span>Use it as a trigger for the \u201cRepeat order nurture series\u201d. This is a great version of a win-back flow, but one that can be even more effective. Imagine that a store where you\u2019re a regular sent you a message just when you were thinking about buying again. Since much of marketing is about timing, the store would have a real advantage getting you to make a purchase….<\/span><\/p>\n

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Predictive analytics is a tool provided by several ESPs. It estimates results based on a mathematical model which utilizes Bayesian inference. That is, the model improves and learns over time as new data becomes available. It matches data from a single contact with data from the whole list.<\/span><\/p>\n

Let\u2019s say Customer A buys from you and buys again after 10 days. The model will use this information for predicting Customer A\u2019s next order date. Not only that, it will look into data from your whole list and search for patterns that match with Customer A\u2019s behavior.<\/span><\/p>\n

Of course, the tool is not perfectly accurate, just like any other statistical model that aims to predict human behavior. Nevertheless, you can\u2019t know your customers accurately either. They\u2019re never exactly who you think they are. There are thousands of them, and they buy for an unthinkable variety of reasons and factors.<\/span><\/p>\n

That\u2019s where predictive analytics enters the scene: the more repeat buyers you have, the more data you\u2019ll collect. Consequently, the predictive model will be more accurate and make you more revenue per recipient. When your ESP provides you with such powerful mathematics in a simple user experience, there\u2019s no reason why you shouldn\u2019t be testing it.<\/span><\/p>\n

So how do we adjust that Winback Flow so that it\u2019s based on more than just whether someone is engaged, unengaged, a buyer or a non-buyer? One way is to use the expected date of the next order as the trigger. You can also adjust the time frame, for example triggering the flow a week before the expected date of next order.<\/span><\/p>\n

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Another way to use predictive analysis for segmentation is to create a segment of people with the expected date of the next order within a certain period. It is possible to combine it with your current main segment in different ways.<\/span><\/p>\n

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For example, you can:<\/span><\/p>\n