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Enhancing customer interaction in financial services: The role of behavioural analytics

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By Dave Hendry, Regional Sales Director, Fanplayr

Personalisation is set for a major change as Google and other web browsers plan to cease use of third-party cookies next year. The restriction of data that has previously facilitated optimised website interactions and internet advertising will mean a major re-adjustment for financial services organisations. Concerns about potential infringement of legislations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have led browser companies to take this drastic action.

For financial services organisations in the UK, this development will have ramifications for how they interact with their customers. Three times more Britons now have a digital bank than in January 2019, while four in five use some form of online banking. So it appears that just as swathes of people go digital, financial services organisations will no longer have access to information they need for personalisation, as they will be unable to track where customers go on the internet after they have visited a bank’s website.

While on the surface this may seem detrimental to financial firms, the reality isn’t quite so concerning. Financial organisations now have a new opportunity to radically improve how they interact with web visitors and customers. AI-powered behavioural analytics offer far superior, real-time capabilities, using the data from the first-party cookies on their own website domains and where available, data from customers’ transaction histories.

In contrast to conventional technology relying on cookies for third-party businesses to store data, this method is faster, more accurate and more responsive. Instead of relying on such data for relatively rigid profiling and personalisation, behavioural analytics enables real-time interactions based on a more dynamic picture of how an individual’s requirements are changing.

From number of page views to time spent on a site, the technology can determine the most specific browsing actions by users, along with features such as deciphering a particular interest in a service or product. Historical data added to the analysis includes what customers did on previous visits and the interval between those visits, establishing patterns where possible.

The numerous benefits of behavioural analytics hubs

Utilising segmentation allows banks to split customers into new or existing ones once they arrive at the site. Their behaviour then indicates what they want and dictates how the bank should react. Knowing what customers are interested in is important. Customers visit financial services websites for a host of reasons, from seeking information, to opening accounts and exploring loans and mortgage offers. They may also want advice about investments and savings, pensions or small business finance. Almost all of these requirements involve quite complex mental processes which financial organisations can influence while consumers are on their sites.

While data collection is the easy part, the true challenge is making the data actionable and reflective of how an employee can anticipate a customer’s state of mind. Banks can do this by setting up a behavioural analytics hub to understand what a customer’s behaviour means and how it can be optimised.

With parameters that can be customised accordingly, the hub can send a notification to a web visitor to fill in a form that leads to booking an appointment. In the case of existing customers, the technology can correlate health insurance offers with spending on fitness, and, in general, savings and investment recommendations can be tailored to the client’s concerns or goals as revealed by their navigation of a bank’s website or mobile app.

For visitors that are about to close their browser tab, analytics can even be programmed to recognise when they’re set to leave the website, allowing banks to send a notification with an offer before they do. This provides a positive outcome and avoids the blanket use of offers that undermines profitability.

Employing a more sophisticated approach means a move away from irritating pop-ups or recommendations that can affect user experience and fail to meet individual preferences. As part of a single AI-powered segmentation platform, the technology enables banks to personalise marketing content in SMS messages and emails sent to consumers (who consent), which deliver far better results through precise targeting.

Facilitating last-mile interaction

Utilising a single platform approach also brings another major benefit for banks, with implementation much simpler, more efficient and streamlined when compared to separate solutions for different phases of the customer journey. The advantages associated with AI-powered segmentation solutions should form part of wider strategy for the financial sector as the open banking era comes to an end with the ceasing of third-party cookies. For many banks, it’s been the case for a while that system complexity has put a barrier in front of high-quality last mile delivery, but these technological developments have helped clear the path.

Financial services organisations that fall behind will ultimately be lost in a sea of data and lose track of their customers. Behavioural analytics will provide unprecedented insight into customers’ behaviour, with actionable, accurate and real-time data. For banks to remain profitable and support their customer base, employing AI-powered behavioural analytics is the way forward.

Global Banking & Finance Review

 

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