When I first sat down to write this blog, the world was very different to where we find ourselves today. Nevertheless, the need for personalised customer journeys seems just as important in times like these, as consumers demand customer experiences based on an understanding and empathy of what they need right now, as we all navigate this ‘new normal’. Who knows, for some companies it may even be a perfect time to try new things and take more risks.
A great customer journey can be achieved in a myriad of ways, but one strategy still riding high is personalisation. This strategy uses clever tech to present customers with offers and services tailored to them, all by using big data and AI (Artificial Intelligence). Doing personalisation well is all about data. The way you collect it and how you use it in harmony with tech, algorithms and more. It improves engagement, reduces costs and can create major boosts in revenue. Cha-ching.
Here’s the thing. When I began to think of my favourite examples of companies using personalisation in the last few years, it quickly dawned on me: none of them were financial services organisations. Of course, those examples do exist and some of them are great (see below). But given their access to enormous amounts of rich data, dedicated digital departments, all with AI and advanced data analytics at their fingertips, you would expect financial services to be thriving in all things personalisation. So why isn’t it?
Some obstacles standing in its way could be:
- Some customers are not fully digital and still rely on the branch
- Legacy tech holding it back
- The regulatory environment creates barriers
- Gaps in omnichannel technology needed to support personalisation
According to The European Survey of Financial Services Executives, 51% said that IT challenges were the greatest barrier to personalised customer experiences. Closely followed by 34% citing ‘complying with Government/industry regulations’ and 31% listing fragmented data as a significant obstacle.1
As Monzo’s CEO, Tom Bloomfield said “The problem that I see with traditional banks and when they speak about personalisation is that it is always a way of selling more financial products. They never seem to think how can we use this to really help our customers?”
Some successful examples of personalisation in financial services:
- Direct Assurance’s YouDrive’ programme which connects a DriveBox device to customers’ cars
- Capital One’s use of location analytics platform FourSquare
- HSBC’s use of AI to give US credit card customers a personalised service
- Monzo’s application of customers’ spending habits data to advise them how they could save money.
Let’s stop a moment and remind ourselves of some great examples of personalisation:
This streaming giant’s secret is its consistently developed and improved algorithm. With no two user homepages looking the same, Netflix is entirely data driven and shirks focus on traditionally important demographics data such as gender and age, instead concentrating on user behaviour, and with the number of paying subscribers worldwide jumping from 21.5 million to 158 million between 2011 and 2019, something is clearly working.
Amazon’s use of big data and a recommendation algorithm to suggest products not just for the specific customers but for particular aspects of their personality, also encouraging impulse buying by suggesting key products to match. A whopping 89% of buyers agree they are more likely to buy products from Amazon than any other ecommerce sites.
If you can’t remember visiting your local supermarket and eagerly looking for a coke bottle with your name on back in the summers of 2013 and 2014, then you may have been hiding under a rock, or are perhaps merely a spring chicken. For its famous ‘Share a Coke’ campaign, Coca Cola replaced its logo on bottles with a huge variety of first names and also terms such as ‘family’, ‘friends’ and ‘BFF’, encouraging consumers to spread love for the brand and #shareacoke.
For its end-of-year campaign #2018wrapped Spotify made the most of its in-house user data. Each user received a personalised email revealing insight into their listening habits throughout the year, such as the songs they listened to the most and how many times – the user could then click through to a microsite which would give them more info and suggest songs they might like based on what they had listening to that year. Clever stuff.
In 1995 Tesco launched its Clubcard, the simple reward system where customers collect points for purchases that can then be exchanged for cash vouchers to spend with Tesco again. By having a card that tracks your activity, Tesco has access to a wealth of data on its customers’ preferences, and can therefore create products and advertising campaigns that are based on their customers’ changing tastes and preferences.
With more data recorded in the last decade than in the whole of human history before (yes, you read that correctly), surely the innovative ways businesses use data to enhance customer experience is only just beginning. Of course, the next year in particular will be very interesting. Given how significantly everything has changed since the global pandemic, financial services will have to shift their focus. The question is, will they set their sights on creating better, more personalised, customer journeys – or will their attention be drawn elsewhere?
Only time will tell.