Using Customer Intelligence Data to Your Advantage in 2020
December 04, 2019 • 7 min read
Next year there will be 20x more data than there is now. With stats like these, it's no surprise that analysts have identified 2020 as the prime opportunity for financial services to digitally integrate with the masses.
Allowing that statistic to sink in, it’s a huge increase but not unrealistic. In all digital-led businesses, regardless of their sector, the gathering and analysis of data has rapidly increased.
That’s not an Orwellian commentary, but forward-thinking businesses have long realised the importance of data. This can allow a business to better market services to customers and effectively communicate with a wider audience, data can also help firms outmanoeuvre competitors and assume their market share. Specifically, the effective use of data could allow financial services to penetrate new generations of customers that incumbent firms have barely been able to scratch.
Although regulations such as GDPR have been introduced to bring some control to this era of mass data use, the pace hasn’t slowed. With some firms struggling to catch up, many are focusing on where they are best placed investing their time and resources to capitalise on future trends of data management.
In recent blogs, we’ve already touched upon the fast-evolving and fascinating world of digitisation within financial services (such as AI, aggressive SaaS adoption and the regulator’s use of tech). These trends are all leading to where data is taking us next and according to PwC, customer intelligence data will be the “most important predictor of revenue growth and profitability”. It will also unlock huge potential and help businesses to give customers what they really want.
'Customer intelligence will be the most important predictor of revenue growth and profitability'
Looking specifically at younger generations, there is greater adoption of technology already happening here. Stepping aside from lazy stereotypes of smashed avocado on toast and hipsters glued to their smartphones, younger generations have played a huge part in helping big brands disrupt. More likely to trust new business models and entrants to the market, these are the consumers who helped Uber take over the taxi industry, Airbnb undercut traditionally-costly hotels and Amazon effectively make large parts of the physical high street redundant.
At the same time, these generations – in the UK at least – are financially insecure. According to a 2018 report by the Resolution Foundation, UK millennials have suffered the second biggest reversal in finances after Greek citizens.
Those born in 1980 earned 13% less in their 20s than those born in 1970 at the same age. At the same time, the plight of homeownership among younger generations has been well documented. With rising house prices and low wage growth, only 30% of millennials own homes (compared to 60% of baby boomers at the same age). And that is not even taking into account the fact many young people are not contributing enough to their pensions. These younger generations are extremely easy to reach and financially insecure, therefore presenting a fantastic opportunity to financial services as a whole.
That said, according to the FCA, only 6% of the UK population has bought financial advice in the past year. For a number of reasons (money being a taboo topic, mistrust of the sector, lack of affordable advice, etc) the wider populace is not integrating with financial services. Technology can make a difference here.
By intuitive use of the ‘internet of things’, financial institutions should theoretically be able to take this customer intelligence and act upon it. Through analysis of how consumers interact with services and spend their money, what’s to say these firms can’t reinvent the way they market products to them? For instance, within asset management, hyper-connectivity could pave the way for greater product customisation – getting people to approach investment in a new and more educated way.
For life and health insurers, wearable computing (building on the technology already widely used in fitness sensors), could make the underwriting process more collaborative. And to some extent we have already seen the adoption of technology in the financial advice sector, allowing start-ups known as ‘robo-advisers’ to start talking to consumers in the one place they are looking – their phones.
There are obvious barriers here. Aside from the population’s inherent mistrust of the sector and overall lack of financial education, there are numerous regulatory constraints. Specifically, robo-advisers have faced difficulty in what they can offer customers (bringing about the semantic argument of ‘advice’ versus ‘guidance’). And even though technology allows for easier distribution and marketing of products and services, within financial services this still isn’t a silver bullet for success. Several large incumbents in the sector have been forced to write off expensive ventures into the digital realm, simply because they haven’t been able to gain the critical mass to justify the expensive overhead of coding. Remember, for every successful eye-wateringly profitable start-up, plenty others have failed.
In order to make successful use of data, firms must question why they need it and how it's going to help them achieve their business goals. With customers expecting a seamless online experience, collecting a huge amount of 'experience data' has become a focus for many. Firms must be careful not to measure for sake of measuring and they must challenge the metrics they use as indicators of success (for example, NPS, Csat or retention figures). Data therefore must be harvested and effectively managed – all at lightning speed and with all the regulatory boxes ticked. With so much data in the offing (remember, 20x more as of 2020) the opportunity can't be ignored for financial services as a sector.
What can we do now?
Here are a few simple things you can do to look at data in a more effective way that'll benefit your business.
Analyse the data you have
You probably already have customer intelligence data at your disposal but the odds are there’s a lot more you could be doing with it. Try and come at it with fresh eyes and objectively look at the data you collect and why. Are departments looking at their data in isolation? Can marketing, support, product and sales all see what's happening with their customers and as a result improve the engagements with them? A huge part of data analytics is challenging what you currently do and developing fresh perspectives. You might be surprised – without embracing any additional software or new systems – at the amount you could be changing already.
Consider what data could help you improve your service offering
Sit down and make a list of your ideal customers and try and describe everything about them. Not just the basics such as age, gender and so forth, but deeper behaviours or traits – what kind of TV shows do they watch? What are their biggest fears? What motivates them? Have fun and let your imagination run wild. Then, once you’re finished, take this list and do some research on how you can confirm this. The caveat here is that it's important to only capture data you need, this requirement is driven by GDPR and therefore anything you capture from customers should be tied directly back to a sufficient answer why. If this data goes towards improving the customer experience and service you offer, and you can even prove it, great.
Consider what doesn’t work and question why that is
A huge part of how the biggest disrupters did what they did was by bridging the gap from ambition to reality. That’s not a cheesy line from a TED talk, but a fact. Airbnb had to start somewhere and, after a few expensive learning curves, simply started arranging short-term lets for holiday goers. For example, you may have a wish for 10,000 new students to buy into a new ISA your firm is launching. That might seem ambitious but why? Because students don’t buy ISAs? Start challenging that assumption – how can you meet students halfway? Does your ISA need new branding? How can you get your ISA in front of them? Start challenging yourself and thinking how data can help you do this.