The perfect storm – mainstream adoption of Telematics is coming
Brittany Detamore 270006ARTU email@example.com | 2013-06-18 17:45:25.0 | Tags:  analytics progressive big-data telematics big-data-analytics | 0 Comments | 7,140 Visits
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In my last blog entry, I discussed how data is at the core of a telematics solution first and foremost to price a customer’s policy based on how they drive.
However, data is also an essential aspect for the mainstream adoption of telematics. If Insurers are going to pursue the mass-market in addition to the niche segments then leveraging the existing data they have is key. That said, data is only part of the answer. Insurers need to have a clear strategy on the segments of customers (and associated risk) that they are looking to take on board before they embark on marketing and advertising). Insurers should also consider the priority order with which they target customers – is it to convert existing customers first or to target new customers?
We all know that Telematics isn’t new to the industry; it has been around for approximately a decade now – so what has prevented the mass-market adoption to date?
In addition, there lies an even bigger challenge, the public’s knowledge and perception of what telematics is. I recently heard that 1 in 3 people don't know what a telematics policy is. I would be surprised if it isn't in fact closer to 2 in 3 people based on conversations I have had with people who aren’t in the insurance industry. Therefore Insurers need to also think very carefully about two additional factors:
Converting Existing Policyholders
Insurers will currently have a number of policyholders that could be a good fit for converting to a Telematics policy. These customers could vary in age, location, driving history, claims history etc. This is where Big Data Analytics can provide insurers with the ability to use their existing internal, structured and unstructured data to score existing policy holders based on home location, car and engine size, number of points on license, number of claims, existing premium, age, miles driven to identify a sub-segment of existing customers that could be targeted with a Telematics offering. Insurers will then need to price a Telematics policy for their existing policyholders to assess the viability of offering that customer a policy.
Targeting New Customers
Insurers will be keen to add new policyholders to their customer base, which is where a combination of internal structured data (quote history and previous customers that have churned) and external unstructured data (from sources such as Twitter or Facebook groups) can be combined. This data can be analysed to identify new customers who may either be looking for a new policy or a Telematics policy due to an event such as a bad claims experience or a first accident which has increased their premium. This data can be used to again identify potential customers to market with an offer.
Let’s be clear, analytics is not the silver bullet for Telematics. First and foremost the price of a Telematics policy has to be less than a customer’s existing traditional policy, otherwise they will not switch. In addition, insurers need to have the right marketing plan and execution mode and will need to raise the profile of their product through advertising correctly, but analytics can support all of this and assist insurers in boosting the number of customers with a Telematics policy.
The combination of SmartPhone technology, improved data architecture and big data technology might just be the perfect storm to kick start mass-market adoption of Telematics.