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Big Data’s Impact on Online Pricing Strategies

November 12, 2013

Big data is being used to drive business on many fronts — from in-store sales to customer personalization strategies. One current study set out to determine whether the advent of big data collection also can reveal more about online buying and price points for retailers than in the past.

Specifically, Benjamin Shiller, an Assistant Professor of Economics at Brandeis University, is studying “First Degree Price Discrimination Using Big Data”–the effects of discount offers and how much they can raise profits for a product and a company.

Shiller described his research at a recent lunch seminar sponsored by MIT Center for Digital Business’ Initiative on the Digital Economy (IDE). His group looked at the online sales of Netflix and determined that tailored customer discounts do provide incentives to sales and can be customized to specific buyers based on detailed web behavior.

Shiller explained that:

[While] “second and third-degree price discrimination (PD) receive far more attention than first-degree PD, i.e. person-specific pricing, because the latter requires previously unobtainable information on individuals’ willingness to pay,” big data is offering new insights.
Shiller’s research demonstrates that “web behavior data reasonably predict Netflix subscriptions, far outperforming data available in the past.”
He also presented a model to estimate demand and simulate outcomes versus older methodologies. “Simulations show, that using demographics alone to tailor prices raises profits by 0.14%,” he said. Including web browsing data, however, increased profits by a much larger, 1.4%.”

Increasingly, the appeal of tailored pricing will be critical in online competition and in understanding the motivation of online buyers. Big data will have a big role to play in this new marketplace.

The full presentation and slides can be viewed here.