Monetising data
Why fresh thinking is needed

9th July 2021

It's often said that data is the new oil, and the end goal for any business is translating data into hard commercial benefits for their customers - and thereby growth for their own organisations. Doing that requires not only an appreciation of the value that lies in data and powerful technology to harness it, but also fresh thinking when it comes to its application.

According to Forbes, the decade leading up to 2020 saw the global output of data increase by almost 5,000% from 1.2 trillion gigabytes to 59 trillion gigabytes.

Meanwhile, a 2019 UN report showed that by 2018, the five largest companies globally (Apple, Amazon, Facebook, Google and Microsoft, together valued at almost $4 trillion) were all part of the data economy, compared to just one of the top five a decade earlier.

There is no doubt that the growth in both the volume and value of data has increased exponentially, and that the pace of growth is only accelerating, particularly as new technologies emerge that transform our ability to analyse and exploit data at scale.

Artificial intelligence and machine learning in particular are being applied in industries ranging from healthcare to the automotive industry and marketing to financial services, with dramatic impact, whether we think of diagnostic medical technologies or self-driving cars.

Gathering information, analysing it and then applying this insight for commercial gain are all discrete and vital stages in the journey towards data monetisation.

This could be something as simple as a fleet manager understanding how colour choice affects the re-sale value of a car years later (stick to metallic blacks, blues, grey or white if you want to play it safe) or as complex as analysing insurance quotes to see whether or how consumers are 'tweaking' their details from one quote application to the next (with the type and number of changes proving an accurate indicator of the likelihood of fraud).

Integrating additional data into customer journeys can be a valuable way of improving the customer experience at the same time as leading to better business outcomes.

For example, accessing third party databases to verify customer declared information, delivers a time saving for consumers by removing the burden of locating and entering various items of information, and at the same time, it ensures accuracy for insurance retailers, giving confidence to underwriters.

Data platform
As a licensed provider of extensive vehicle and property data sets, from MOT to finance data and car registration to valuation information, CDL is in a unique position to support insurance providers to access and harness data effectively for a range of applications.

And this information takes on even greater value when it is brought together. Taking data from a range of sources and integrating, orchestrating and analysing it through a unified data platform opens up significant opportunities for businesses, as it enables them to gain a single customer view, learning from interactions across a range of touchpoints.

Current quotes, past claims, credit scores, vehicle history and data from connected home and car devices can all be integrated to give a holistic view of the consumer, offering benefits to the retailer and customer alike.

On the one hand, data insight can be used to tackle fraud and identify suspicious patterns of quote manipulation to weed out potentially fraudulent customers and eliminate toxic risks; on the other, it enables insurance and finance providers to gain deeper customer insight and reward the 'good' consumer with better rates or levels of cover.

The pre-requisite from the consumer's perspective is that the benefits of data sharing are compelling enough to overcome our natural instinct towards data privacy. If social media has taught us anything, it's just how much information people are ready to give away in exchange for new, connected experiences that put them in control.

And the disruptive model of these platforms is their readiness to offer services 'for free', with the understanding of just how much value there is to be garnered from the information they are gathering.

Disruptive force
Equally, when it comes to insurance, it is data that lies at the heart of the opportunity to create a new model of engagement with the consumer, using proactive triggers to offer cost savings or add value when the profile or time is right; for example, adjusting the insurance premium as driving licence points expire or annual mileage decreases.

The key is again to earn consumers' trust through simple and compelling customer journeys, with the benefits of data sharing clear to see.

Moving away from the prevailing sales paradigm dominated by prescriptive and lengthy forms to complete, we see technology acting as a personal assistant, helping the consumer to save time, ensure the right levels of cover are in place, and that the price is right.

This new model makes it easy for shoppers to enter the items they wish to insure by snapping a photograph (of a pet or car for example), 'toggle' features on and off, design personalised insurance products and pay for them on a subscription/pay as you go model.

It sees a shift from traditional annual policies, where each line of insurance is treated as a separate entity, to a more integrated product portfolio psychology - one that better serves the needs of the consumer and the cross-selling aspirations of retailers.

And ultimately, it ensures that retailers are able to offer more compelling propositions in more proactive ways, creating added value to retain their customers for the longer term.

To find out how CDL's data, analytics and customer experience platforms can help you add value for customers, contact