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How Data Science Is Advancing the “Nudge” to Influence Mobile Behaviors

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How Data Science Is Advancing the “Nudge” to Influence Mobile Behaviors

Have you added two dollars to your grocery bill to benefit a local charity? Decreased your power usage after being shown how much your neighbors were using? Had better aim when using a urinal with the image of a fly etched into the porcelain? If you answered yes, then consider yourself “Nudged.” And yes, the urinal approach is actually being used in Amsterdam’s Schiphol Airport restrooms.

Attributed to Richard Thaler and Cass Sunstein in their best-selling book “Nudge: Improving Decisions about Health, Wealth, and Happiness,” a “Nudge” is a signal — which could be contextual or environmental versus written or verbal — that changes the behavior or decision that a human will make.
The original test of this theory was in a Chicago school district where they changed how food was laid out in the school cafeteria. This had a 35 percent positive impact in the consumption of healthier foods, without actually restricting the overall choices of foods available.
Leveraging a variety of different strategies, such as default settings, information as incentive and right context, companies have proven the ability to change someone’s behavior through a successful Nudge.

Automated decision making: So many decisions, so little time

So why do these Nudges work? Essentially, we don’t have time to process each decision that we make in life. Instead, we use cues and heuristics to guide our decisions — an automated decision making process.
The basis of Nudge theory is to apply an understanding of predicted behaviors to shape and influence that automated process. While standing in the checkout line, most shoppers will not weigh all of the pros and cons of donating two dollars to the charity at hand. The retailer can easily drive the results it wants by predicting that most shoppers will be in a hurry, and willing to accept the two dollar price point.
Now let’s consider how many decisions are made by a mobile user each day. Should I use an app or a mobile site? Should I forward this to my friends? How much should I top up my prepaid account?

Each individual’s decision is a unique, personalized Nudge opportunity.

And herein lies the challenge of applying an understanding of predicted behaviors to the mobile space. Although the traditional Nudge approach, which leverages trial and error, has proven successful for influencing the masses, it does not allow for the creation of timely, individualized Nudges for millions of dynamic customers.
So how can a mobile operator with six million subscribers making 200+ decisions per minute apply the Nudge theory to effectively discover, learn and optimize how to engage with each customer to truly change their behaviors?
Discovering the who, when and how of nudging mobile customers
Leveraging data-driven technologies such as pattern recognition, behavioral clustering, social graphing and predictive analytics, mobile operators are turning to data science and machine learning to advance the application of the Nudge theory — moving from a broad-brush approach to one of micro-targeting.

 

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