While “pay per grain” beach vacations may not catch on, the idea of paying for incremental, and individual-based activity already has. As technology makes activity data easier and cheaper to collect and analyze, more companies are leveraging it to create personalized pricing. Examples include Amazon Web Services (AWS) that charges customers for its cloud computing service by the hundreds of milliseconds of computer use and Google’s pay-per-click search advertising charges.
Metromile is a leading technology startup ($191M in funding to date) applying this principle to the auto insurance industry by using individual driving data to calculate premiums. Historically, actuaries have relied on group-based statistics like age, gender and marital status to determine behind the wheel risk. Lack of individual data means that low risk customers are generating most of the profits and subsidizing the high-mileage drivers.  Metromile estimates that 65% of drivers are “overpaying” relative to their risk. Not only is usage-based insurance attractive for these 65% of consumers, it is also attractive to insurance companies as it improves customer segmentation, helping identifying the higher profit customers. It can also lead to social and environmental benefits by incentivizing more responsible driving and less unnecessary driving.
Although Metromile is not alone in testing usage-based pricing, its business model is unique in its industry. While competing programs, such as Progressive’s Snapshot, are based on many driving patterns such as speed, acceleration and braking, Metromile only focuses on one thing, number of miles driven. The company believes it is a superior model for a number of reasons.
- Accurate: Metromile CEO Dan Preston says that most of the risk drivers pose is associated with miles driven, rather than their behavior. 70% of the variation in insurance claims filed can be attributed to how much customers drive, with just 30% tied to driving habits. By only taking a single factor into consideration instead of others such as drive time or drive location, Metromile does not penalize consumers who, for example, work a late shift or live in a low-income neighborhood, unlike other companies. 
- Straightforward: Metromile attracts customers through a simple operating model. Customers receive a set base rate and per mile rate based on demographic factors and type of vehicle (up to 6 cents a mile). A small free wireless device called Pulse plugs easily into their car and the company uses telematics devices to track mileage only. While competitors create complicated driving score cards with multiple cost drivers, Metromile customers like the straightforward “drive more pay more” pricing. Customers can access the Metromile app at any real time, seeing real time cost accumulation and data visualizations. 
- Effective: Metromile is able to expedites changes in driver behavior by providing this immediate, and straightforward, feedback loop to the driver and a “drive less pay less” incentive. For example, if a commuter switches to public transport, consumers can immediately see lower insurance costs in the app.
Looking ahead, Metromile will face increasing competition in the usage-based insurance space as incumbents and new entrants test the model. Key areas of focus for the company should include:
- Device Safety: A recent UCSD research study exposed Metromile’s in-car device’s sensitivity to hacking. Although Metromile responded by sending a security patch to the devices, this incident reveals key security threats Metromile may face. Given the potentially life threatening risks of a hack, Metromile should make device security a top priority as another incident could jeopardize consumer trust and the entire business.
- Data Privacy: 1/3 of Progressive’s customers say they have no interest in entering the tracking program due to privacy concerns largely due to GPS tracking. Although location data could help Metromile create additional features, the company should continue to differentiate itself from competitors by allowing users to opt out of location data. In contrast to other insurance companies that require location data to calculate costs, Metromile’s mile only program does not rely on it. The company should also target younger consumers that are more comfortable divulging location data given that they’ve been using location-based apps for years.”
- Customer base: Metromile has the potential to expand its base by bringing insurance to underserved markets, forgoing reliance on factors like credit scores and education.  In order to moving into markets with minimal financial literacy, Metromile should ensure its products remain easily understood with clear-but-flexible payment schedules. 
- New Business Lines: As the company grows, it has the opportunity to move beyond insurance and help consumers save “time and money on things related to your car.”  Metromile already offers features such as sending a warning if your car is in a street-cleaning zone.  Future features could include remote diagnosing a car’s running condition and check engine lights or providing access to mechanics. Insurance companies can also learn drivers’ routes and warn them of potential weather risks, evening sending incentives through the app to wait out the storm.
 Hardy, Quentin. “Billing by Millionths of Pennies, Cloud Computing’s Giants Take in Billions.” Technology. The New York Times, 11 Apr. 2016. Web. 15 Nov. 2016.
 Friedberg, David. “Metromile Announces $191.5M in Funding.” PR Newswire, 21 Sept. 2016. Web. 15 Nov. 2016.
 Wingfield, Nick. “How’s My Driving? The Insurer Knows.” New York Times. Bits Blog, 10 June 2015. Web. 15 Nov. 2016.
 Hardy, Quentin. “Technology Transforms How Insurers Calculate Risk.” DealBook. The New York Times, 7 Oct. 2016. Web. 15 Nov. 2016
 Metromile. Metromile: Pay-per-mile insurance. Metromile, 2016. Web. 14 Nov. 2016.
 Nelson, Gabe. ProQuest – ABI/Inform Collection. 17 Nov. 2014. Web. 14 Nov. 2016.
 O’Donnell, Anthony. “What Startup-Up MetroMile Teaches About the Future of Insurance.” ProQuest. n.d. Web. 17 Nov. 2016.
 Newcomb, Doug. “The Next Frontier of Car Hacking.” ProQuest ABI/Inform Collection. 1999. Web. 14 Nov. 2016.
 Salinas, Erica. ABI/Inform Collection. 1999. Web. 15 Nov. 2016.
Word count: 798 excluding footnotes, sources and headers