Flo Is Hungry for Your Driving Data

More than 10 billion miles of driving data collected by Progressive since 2008

With the launch of its Snapshot driving tracking program in 2008, Progressive, an insurance company, has become a pioneer in the fast-growing segment called telematics and has since relied on data analytics to gain advantage over its competitors. The term telematics essentially refers to “a range of different features, options and devices that are brought together by a single principle – data and communication.”

How Progressive’s Snapshot works

It all starts with a small driving tracker device called Snapshot that Progressive has been distributing to its car insurance customers since 2008. You plug the device into your car’s onboard diagnostic port. Snapshot collects data at one second intervals and at the end of every trip, sends the collected driving data to Progressive via AT&T’s wireless network. Customers need to opt-in to begin participating in the program.


This video provides more color on the Snapshot program: https://www.youtube.com/watch?v=kddVgOvPQMY

Data as a value creation tool

The core value that Progressive creates for its customers is essentially a peace of mind in case of an occurrence of a qualified event. The problem is that the core value creation model is similar across competitors. Therefore, to be the winner, a company needs to find an effective differentiation strategy, for instance through a marketing strategy or use of technology. Through the collection and analysis of data, Progressive can enhance its customer value creation capabilities in a variety of ways:

  • Through a better understanding of customer demographics as well as customers’ needs and driving behavior Progressive can optimize and tailor their product suite.
  • Customer data analytics interface offers a wide range of insights into customers’ driving behavior. It alerts customers to hazardous driving thus promoting safer driving habits.
  • A customer’s consistent, good driving record is a tool in obtaining better insurance rates.

Needless to say, data analytics creates significant value for Progressive itself:

  • Data analytics offers a powerful risk management tool for the company. Insights into customers’ driving habits, and more broadly risk tolerance, help Progressive predict who carries more risk.
  • Self-selection: Not signing up for Snapshot is a signal that a customer might not perceive its driving as safe.
  • Data analysis improves customer segmentation and pricing strategy.

Progressive’s value capture model

Progressive rewards those who sign up for Snapshot with a promise of a 30% discount on their car insurance. The idea behind the concept is simple: the better the driving, the less risky the customer is and deserves cost savings.

It appears though that Progressive itself also captures many benefits of the program. First of all, it can better optimize its pricing strategy and create more accurate risk management system. Second, by promoting safe driving habits it reinforces an image of a safety conscious company. Third, customer data make for a more effective marketing strategy.  Finally, there is also a question of whether Progressive would consider selling the data to third parties. For now, the insurer has no intention to do that.

Developing data-driven operating model

From the Snapshot program, Progressive collects two main data elements: time and speed. It feeds the speed readings into algorithms to calculate events, such as hard braking. Driving tracking is just one of many different initiatives at Progressive that utilizes a deep technical team and advanced capabilities around data analytics. As an example, Progressive’s tools for harnessing big data range from version 2.4.1 of Hadoop, R and the full spectrum of SAS software to Excel.


Examples of Snapshot reports

Advanced data analytics capabilities allow Progressive to get ahead of other players in the highly competitive insurance industry. Data analytics-based approach to product development and advertising strategy creates more targeted products and allows for a more efficient use of resources. Driving analytics is just one of many initiatives. As an example, Progressive deploys open-source data analytics software to optimize its ad strategy to gain new customers. Quite unexpectedly for an insurance company, Progressive even launched Innovation Garage, a lab that promotes development of new technology solutions.

Current position and challenges ahead

Progressive exhibited early commitment to data analytics, which can be attributed to the vision of the insurer’s executive team. Progressive CIO Ray Voelker said: “(…) we have expanded into big data, and Snapshot helped us with that. (…) as the technology has emerged over the last four or five years, we certainly didn’t wait for the integration between traditional and big data to emerge before we jumped into the big data (…).”

This is not to say that competitors like Geico or Allstate are not acting on this opportunity. Besides competition, there is a threat that data will become commoditize. There are also obvious privacy concerns and threat of regulation. Despite these challenges, the telematics industry is projected to reach $15B by 2020 and Progressive is well position to benefit from its robust data analytics capabilities. Being the first mover, created a long-term competitive advantage for Progressive. Early start on data collection resulted in a database of more than 10 billion miles of driving data, which cannot be easily replicated.


Zara Leverages Data Analytics to Understand Consumer Tastes


Nielsen: Unique Opportunity with Big Challenges

Student comments on Flo Is Hungry for Your Driving Data

  1. I think is a really cool tool that Progressive is offering. Providing real-time warnings to drivers as well as feedback as to risk over a period of time is quite informative to both the driver and Progressive. On Progressive’s side however, I would think there is some level of self-selection bias among safer drivers choosing to use the tool versus riskier drivers who prefer not to have all actions monitored. Do you think there is a way Progressive can overcome that?

  2. Very interesting, thank you for sharing. Grace brings up an interesting point on selection bias. I do think people who are generally safer divers will opt-in for programs like that. One way to overcome it would be to avoid reporting on metrics that are incriminating such as the seep limit. Instead, they could avoid speed at all or maybe an average for every trip? In the end it will depend what data Progressive will need to make better and more informed decisions.
    There is also room to cooperate with the public sector here. If Progressive gets a lot of data on how people are driving in a particular city, they will be extremely valuable to transpiration officials and could inform how the traffic can be managed in a better way to avoid accidents.

    1. But the metrics progressive is the most interested in are inherently the most incriminating ones; otherwise there’s no point in doing this at all. Progressive can counter the selection bias by weighting participants by their previous driving history (#claims, severity of accidents). Customers that drove well before signing up will be the gold standard for good drivers, and customers that drove poorly before adoption (assuming they do adopt) will be the gold standard for reckless drivers. The differential can be used to adjust the likely positively-biased results towards the true population mean.

  3. Really cool tool. I agree that the selection bias exists. I don’t think it is a problem though. If this service is already providing an incentive to opt-in by offering discounts to people who evidence a lower risk driving behavior, Progressive could automatically assume that everyone who did not opt-in will be a riskier driver and hence, should have a higher price. This only becomes a problem if by making the default option more expensive to compensate for discounts, we stop being competitive compared to other players in the market. This would create a positive selection for Progressive and would push riskier drivers to the competition. If the resulting volume can still make the economics of the business work, then it is not a problem to have a selection bias.

  4. This is SO COOL! What a smart technology for Progressive to use -> they can use the data to adjust insurance rates, it incentives drivers to improve their driving, and it serves as a record in the case on an accident. I almost think this should be a requirement on all cars! That feels a bit Big Brother, but the data could be anonymized for people who choose to opt out. How much could this help in the advancement of self driving car technology? If we could figure out why accidents occur and then stop them proactively – that could have huge positive implications for traffic and congestion in major cities.

  5. A really interesting post about the future of the insurance agency. This is certainly a risk mitigation tool for Progressive and, in the not so distant future, I imagine we could see premiums that vary in real time and at the individual level – e.g. a lower premium when your car is parked in the driveway and a higher premium when you are driving above the speed limit. The implications for other insurance categories are interesting too – maybe health insurers will start tracking FitBit and Jawbone data and adjusting premia accordingly. Health insurers already reward good behavior like vaccines and gym memberships with rebates and this would function in a similar, but far more granular, manner.

Leave a comment