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HBX Business Blog

Dashing for Data

Posted by Jonathan Williams on July 7, 2016 at 2:15 PM

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Out of laundry detergent? Just press an Amazon Dash Button. Out of trash bags? There’s an Amazon Dash Button for that too. What might appear like a seamless way to allow users to order common household products is a new source of data for Amazon to better understand consumer behavior.

How? By using predictive modeling. Predictive modeling is a statistical modeling technique that forecasts an outcome or behavior. This type of modeling often uses historic or current data to predict a future outcome, which can be validated as more data becomes available.

The data collected by the Dash Button is valuable to both Amazon and the manufacturers of products. Dash Buttons give insight into individual patterns of frequency of purchase into a sample of Amazon’s users. Pair this consumption data with Amazon’s rich demographic data, and Dash Buttons are giving new insights to fuel future growth for Amazon.

With this type of data available, perhaps a predictive model could anticipate future consumption and ordering behavior of customers. The future of shopping for household items could mean enrolling and letting predictive modeling take over from there. What if Amazon could accurately predict the amount of laundry detergent and trash bags to ship to you based on your past behavior? This is the future of retail with predictive modeling. 

While the verdict is still unclear if Dash Buttons are a viable, profit-producing technology for Amazon, the data they produce may be more valuable than the products they sell. Every product sold through a Dash Button is a valuable data point that will contribute to Amazon’s next generation of services and products.

To learn more about Amazon’s Dash Button’s data here, check out this article from Fast Company.


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About the Author

Jonathan is a member of the HBX Course Delivery Team and works on the Business Analytics course for the Credential of Readiness (CORe) program. He has a background in mathematics, statistics, and design.

Topics: HBX CORe, HBX Insights