Amazon Save is a new feature on that makes it easy for customers to accumulate savings by automatically transferring the difference between the actual cost and the Amazon discounted costs to your savings account.

Amazon is known as a discount retailer—that is, most of the items on the website are clearly discounted to offer customers a better value than other online stores. Most people presumably use the money they are “saving” from the reduced price to buy other things. But what if “savings” were actually saved?

Amazon Save operates under a similar premise as Bank of America’s “Keep the Change” program, which automatically rounds up purchases to the nearest dollar and transfers the difference to a person’s savings account. Amazon Save, though, would likely end up saving customers dollars instead of pennies, on average, as Amazon products are often discounted more than a few cents. Users will have the option of transferring the exact dollar amount of the discount or a percentage of the dollar amount (such as 50%) to their savings account.

To measure the behaviors of the customers, Amazon Save will keep track of how often people are using the service, and specifically what price differentials are more likely to motivate saving, such as bulk items. This can influence the suggestions that pop-up for the customer. There will be a feature that suggests an item through the frame of Amazon Save, meaning that the product has the most potential for money going into the user’s savings account.

The behavioral model behind Amazon Save assumes that people want to save some amount of money for the future, but they are generally reluctant to do so because of long-term/short-term tradeoffs. To change their behavior, we must have all three of Fogg’s factors: motivation, ability, and trigger. First, will assume that most people are motivated to save, particularly if they are Amazon shoppers because they are looking for online discounts. Second, Amazon Save itself gives people the ability to perform the behavior—to save in small increments whenever they make a purchase. Finally, Amazon Save is an effective trigger to perform the behavior because it only requires the user turn on the program one time. After that, the program saves money for the user automatically.

Amazon Save allows for the introduction of an automated behavior change. The service targets a behavior that people already use Amazon for—saving money while online shopping. This new method of savings only exaggerates the amount saved. At the end of each month, the user will be notified of the amount of money saved, creating motivation for months to come. This targets Fogg’s hope element of motivation; people gain hope each month for saving more money. Regarding Fogg’s elements of simplicity and ability, the Amazon Save feature is applied once through filling out a short form for setting preferences. The customer will never have to spend time on the feature, or think about it after this original set-up. This reduces time and brainpower spent; the simplicity and routinization of the process decreases a need for motivation.

For the users who choose not to apply Amazon Save to all of their orders, there will be a signal trigger at the checkout, allowing the customer to check a box to use the service. This serves a reminder during appropriate behavior, reducing the annoyance of some triggers.

This service can be used by everyone in Amazon’s vast customer base. Amazon will be motivated to use the service; it will further inspire customers to believe in Amazon’s money-saving abilities. Half of Amazon’s customers—63 million people—are Amazon Prime members, spending on average about $1,200 per year (Fortune). Amazon’s non-members spend about $500 a year. Amazon charges, on average, 6 percent less than physical stores (Seattle PI). Thus, a Prime member would be able to save $77 per year, on average, using this program. Amazon Save program has the potential to reach over 100 million people—a huge impact.

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