Access to additional funds in seconds, guidance on how best to spread out payments on a big purchase, promotions and special offers that are personal to you and reach you just as you arrive at the mall … welcome to the age of micro-personalization in banking. Your bank probably isn’t offering you this level of personalized service today, but this type of micro-personalized targeting of customers is what banks can achieve if they learn how to master behavioral analytics, big data and artificial intelligence (AI). Adam Kępa, VP and Head of Growth at ITMAGINATION and with more than 15 years’ experience helping leading banks and providers of financial services transform through technology, helps us navigate the next frontier in the digital banking battleground.
Customers today expect more from their banks. The ‘in branch’ experience has been replaced by an online banking platform and/or mobile app. And whereas, in the past, banks might have competed on interest rates or the type of cards they could offer you, today, they’re fighting their battles in the digital space and competing through the technological sophistication and the features that they can build into their online experiences and mobile apps.
But with the emergence of start-up ‘banks’, FinTech companies, and also the expansion of retail and technology giants into the banking space (GAFAA: Google, Amazon, Facebook, Apple, Alibaba), banks know that they need to up their games further still. These new entrants to the market either already have an established place in users’ lives (as a favorite retailer, a preferred way to interact with friends, or as a preferred provider of technology that we interact with every day) or – as is the case with new ‘start-up’ banks – they use the ‘digital only’ model as a way to offer a differentiated experience that is fast, convenient, hassle-free and easy to deploy.
For banks, some of the features that were only recently rolled out – such as secure and convenient payments through a mobile app – have quickly become little more than the norm. As the industry continues to evolve and transform, the ability to effectively fight for the custom and loyalty of customers will largely depend on a bank’s understanding of how, where and when its customers spend their money and which factors influence their decisions.
Put differently …
How can banks become even more relevant to their customers? How can they make life easier and more convenient? And how can they add value to their customers’ lives in ways that are pleasantly unexpected, relevant and satisfying?
Enter the age of the micro-personalized customer experience.
According to research conducted by McKinsey, today’s consumer expects banks to be proactive and value-adding in the services and information they provide. For example, imagine if your bank could:
All of these ideas offer compelling benefits to customers and banks alike. But they also require for banks to be able to analyze huge volumes of data that come from a variety of different sources in real time, and to develop and use intelligent algorithms that predict behaviors and recommend to banks the next best actions (NBAs) and next best offers (NBO) that they should be proposing to their customers. All of this needs to happen in real time in order to increase the relevance and usefulness of the service to the customer at that moment in time.
An ability to process big data and behavioral analytics, and generate insights that can be used by artificial intelligence to create and propose customized offers and promotions to customers – all in real time – is the holy grail for banks everywhere. If banks can achieve this, they can take their customer experiences to the next level.
ITMAGINATION recently delivered a product that made use of big data, behavioral analytics and artificial intelligence to a major provider of financial services operating on the Polish market. This custom solution has empowered the company to improve the effectiveness of its marketing and promotional activities and has improved the service it provides to customers.
The aim of the project was to get to know every type of customer that the bank served and to increase the relevance and usefulness of the service provided. We sought to learn their habits, needs and preferences, and we sought to do all of this through the perspective of the bank, its products and services and the channels that customers used to interact with the bank. Today, the bank benefits from a machine learning solution that operates across the bank’s website, mobile app, contact center and through its email interactions to create personalized special offers on short-term loans for its customers in an automated manner. The solution developed by ITMAGINATION also effectively analyzes and manages the level of risk associated with each loan by making use of a predictive analytics model that is based on anonymized data on user activity. This affords the bank valuable insights about important variables such as the trustworthiness of customers or the risk of irregular repayment of loans.
The solution built by ITMAGINATION for this client is based on ITMAGINATION’s Behaviolytics® platform, which makes use of real-time analysis of customer behavior to empower banks to prepare custom offers and services that are personalized to the real and current needs of each individual customer. By making use of big data (clickstream data from Web and mobile channels), banks are able to process huge volumes of data at lightning speed. This enables faster responses to applications for loans or the faster proposal of a solution that is optimal for the customer. The result is the provision of services that are more relevant for customers, which in turn should lead to greater uptake of services and higher customer satisfaction.
Let’s imagine that your bank is able to inform you that you could be paying too much for certain services or suggest ways in which you could save money. Isn’t that something we’d all appreciate?
Consider the following example:
You have a smartphone and you pay a bill every month for making calls and data. Your bank knows your age and it knows how much you earn. It also has access to data about the earning and spending patterns of thousands – perhaps millions – of people. Without divulging information or accessing anything resembling private personal data, it’s possible for the bank to detect that you’re paying more to your phone provider than other people in your age and earnings bracket. Based on this information, the bank could proactively inform you that you could be paying too much, and that you should consider re-negotiating your contract or moving to another provider. Take it a step further and imagine that your bank could find you the best deal and facilitate an easy switch to a provider that offers better value. Imagine the time and effort that you could save by not having to speculate on how much you should really be paying or scouring the market for the best deal.
Or, imagine that you’d like to make a rather large purchase, say a TV set or plane tickets for a family vacation. Your mobile app shows you that you have the funds right now, but you know you have some bill payments looming. Your bank is aware that you tend to pay your bills at a certain time of the month and it knows the average value of these bills. As such, it knows how much you need to put aside and when exactly you’ll need to access the funds. By processing all of this historical behavioral data in real time, the bank can tell you if a) you really do have the money to complete the purchase you’re considering (i.e. you’re not going to be caught short in a few days or b) whether you should consider making the purchase using instalments or c) whether you could benefit by taking a low-interest, short-term loan or by using your credit card. Such solutions have the potential to remove much of the on-the-spot calculations and stressful situations that we can encounter when considering a purchase. In fact, these solutions will allow customers to elevate themselves above the pressure of pushy salespeople or complicated calculations and will empower them to make informed, better-quality decisions about their purchases.
By analyzing user behavior, banks and other service providers are able to provide their customers with a wealth of personalized offers and solutions. Today, it’s relatively easy for a bank to offer free or discounted tickets to the movies to all of its customers. But such scatter-gun approaches are ‘old hat’ and show a lack of the sophistication and personalization that is needed to succeed in today’s marketplace. Some customers might enjoy the movie theater but for some, the promotion will seem arbitrary, unsuitable or even impossible (e.g. the customer does not have reasonable access to a movie theater). Without proper context, such promotions can seem like little more than spam. The delivery method needs to be more sophisticated, and more personalized. Offers and promotions need to be relevant to the specific customer (i.e. his or her likes and dislikes), and, importantly, they need to be relevant to the context and surroundings that that customer finds him or herself in at a given moment.
Imagine, for example, that you’re at the mall on a Saturday afternoon. Your banking mobile app detects that you’re there and sends you a notification that you can benefit from discounted tickets for showings that start in the next two hours. Or maybe you’re a regular visitor to the theater. Your bank knows this from your transaction history and ‘rewards’ you with a free ticket to a screening after you’ve done your shopping.
This approach could apply to the whole ‘in mall’ experience. Perhaps your bank could help you plan your route within the mall by making you aware of a number of stores where you’ll benefit from discounts on that day if you pay by card. Or imagine if your bank’s mobile app is aware that you’ve recently been evaluating different television sets online and lets you know that there’s a special offer on one of the sets you’ve been looking at in a store nearby and the bank will offer you a low-interest loan if you buy today. This hypothetical bank can do all of this because – without needing to delve into personal details – it knows you from your spending patterns, online behavior, earnings and financial history, and is able to provide you with personalized, context-relevant offers that feel less like spammy, scatter-gun promotions, and more like useful, experience-enhancing offers and benefits that the bank knows you’ll appreciate.
The effective processing and use of big data, artificial intelligence, and behavioral analytics, can empower banks to anticipate customer behavior and – based on an intimate understanding of their financial history, likes and dislikes and overall credit worthiness – manage and enhance relationships, increase their own usefulness to customers, build brand loyalty and generate more business by identifying and proposing relevant up-selling and cross-selling opportunities.
In the face of pure-play payment services, start-up banks and the encroachment by tech companies (Apple, Google, Amazon) into the banking space, today’s bank needs to recognize the importance of knowing and being close to its customers. It needs to know how to anticipate and satisfy the needs and desires of its increasingly expectant customers, and it needs to know how to do all of this in real time. A failure to commit to transformation through technology is as good as a commitment to failure.
If you’re committed to winning the hearts and minds of your customers and are interested in delivering micro-personalized customer experiences, get in touch with ITMAGINATION.
Learn it. Know it. Done.
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