CASE STUDY

Developing a Profitable IoT Platform

 

THE CHALLENGE

The Hartford, a Fortune 500 insurance company, partnered with Peer Insight to establish a platform that enables dynamic insurance pricing based on real-time sensor data.

The platform would need to expand The Hartford beyond its fixed-premium business, ideally with B2B sensors and IoT solutions.

THE OUTCOME

A validated revenue model, new sensor-and-software providers, and proven business APIs that helped an insurance platform scale profitably.

The Problem

The possibility of usage-based insurance was becoming a reality in consumer insurance (e.g., Progressive Snapshot). Would IoT solutions based on telematics threaten the fixed-premium business for The Hartford and other B2B fleet insurers?

The Hartford envisioned a B2B brand around dynamic insurance pricing, based on real-time sensors. If dynamic pricing could work for fleets, perhaps it could extend to other property and casualty applications including warehouses, cold-chain, restaurants, and beyond.

First, The Hartford needed to create a successful first use case, including a scalable business model and business terms with its technology partners.

 

The Approach

Peer Insight worked with The Hartford to study the journey and pain points for drivers, dispatchers, and fleet managers across several possible segments. The team selected medium-sized over-the-road fleets as the early adopters; insurance claims and fleet operations costs were a pain point for that segment.

The first in-market Alpha test, however, was run with a school bus fleet, to allow The Hartford to understand the technology and user experience in a tightly controlled — and under the radar — environment. This 60-day validation test was done without collecting revenues.

At the same time, Peer Insight and The Hartford conducted in-market experiments with several different revenue models. Using simple simulations, user feedback led to to a gain-sharing model that was both attractive to fleet owners and profitable for The Hartford. A second Alpha test was conducted with three over-the-road fleets of less than 200 vehicles.

In addition to platform user tests, the team collaborated with software companies that provided the sensors, in-cab feedback system, and software interface. The original pilot software provider received one year of exclusivity, then the platform opened to two additional technology providers. This decision was key to enabling future competition (which became a control point for The Hartford as the convener).

 

The Impact

The launch of dynamic pricing was quickly successful for The Hartford, and became the first instance of dynamic pricing based on IoT telematics. They were successful in large part because they de-risked the project carefully. The school bus trial let them vet the data flows and technology partnership. Simultaneously, their in-market revenue model experiments showed them how it could scale profitably for an early adopter, the medium-sized over-the-road fleet.

The gain-sharing revenue model we created let them have their cake and eat it too. Fleets signed on at a fixed rate — the business arrangement they were used to — and then earned gains as their driver behaviors improved. Moreover, by opening their platform to new sensor-and-software providers, we proved the business APIs that helped this platform scale profitably.

This project gave The Hartford a new, dynamic insurance product that has enabled the insurer to remain competitive in an emerging segment that continues to develop rapidly.