Big news! Last week saw the first-ever edition of W.UPdate, our new invite-only talk series on how to transform banking data into bottomline results. Attendees from four continents tuned in to the webinar to hear W.UP digital banking experts. We discussed Netflix’s The Social Dilemma and what it means for banking, strategies and approaches to behavioural data analysis, the rise and fall of PFM tools and more. Here are three key takeaways for getting banking personalisation right. 

A dilemma for the modern ages

Ever since The Social Dilemma dropped on Netflix, social networking sites and their harmful effects on everything from users’ mental health to democracy have once again come under the spotlight. In case you haven’t seen it yet, the thought-provoking docudrama takes a close look at how a handful of firms – and engineers – make decisions that impact billions and how they monitor, analyse and predict our every tap, scroll and swipe. 

The dilemma part comes in because, in terms of social value, these data mining strategies can range from somewhat questionable to downright sinister. And yet, people are completely consumed with the social world. In fact, most of them are so busy watching, liking and commenting on what others are doing that they lose focus on what they should be doing. Taking care of their finances very much included. 

If there’s anyone who’s well-positioned to turn the tide on this, it’s banks.

Just like Google, Facebook, Instagram and Twitter, banks have access to tremendous amounts of information. Not just any information: banking data, such as payment details and transaction history, which is much more accurate, reliable and valuable than anything social networking sites can get their hands on. With the right technology, banks can use this wealth of behavioural data in a way that benefits both their customers and their bottomline.  

It’s a marathon, not a sprint

Building banking personalisation capabilities is not a project. It’s a journey. And banks must make sure they have the right building blocks in place before they set off. 

W.UP’s money insights module serves as a solid foundation of personalisation strategies, basic, complex and anything in between, allowing banks to highlight and explain key spending patterns to customers. Taking personalisation one step further, they can offer guidance on how to overcome financial hardship and break bad financial habits to improve financial fitness. 

In certain cases, of course, the solution to a financial problem or situation will be a banking product. If offered to the right customer, at the right time, through the right channel, these interactions can quickly turn sales pitches into win-win deals. 

Finding never-never land between PFM and CRM tools

Banking personalisation platforms are not fancy PFM apps. Or CRMs dressed up to look new. 

When they first came out, personal finance management (PFM) tools were seen as a revolutionary means to help people better manage their finances. But they soon became a lacklustre affair. They weren’t automated, customised or proactive, showing nothing but basic charts and spending data and leaving the lion’s share of data analysis to users themselves. 

Most customer relationship management (CRM) solutions, by contrast, have proactivity among their key features. Yet, according to Gartner’s newly published Marketing Data and Analytics Survey, more than half of CMOs and marketing decision-makers are disappointed with the results of their analytics investments. Especially when it comes to data and campaign analysis.

Personalisation platforms combine the best of both worlds. They run on pre-built, industry-specific algorithms that translate customer data into actionable insights. Plus, they come with campaign manager functionality that can turn these insights into perfectly-timed nudges or offers. All this can result in a 120% growth in mobile app users, 70% more time spent in-app and a 20% increase in in-app transaction volume. 


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