Access to increasing amounts of data is changing the way businesses serve customers. Brands of many kinds – from Amazon to Netflix, Shopify to Google – are using the insights gleaned from vast data stores to create personalized experiences that stimulate loyalty and trust. Because of this, more and more customers expect brands to anticipate their needs by proactively suggesting relevant products. In short, personalized customer experiences are becoming a necessity for businesses. What’s more, the companies that create them are gaining a competitive edge.
Financial services somewhat lag behind other sectors in terms of developing personalized customer experiences. Although there are valid reasons for this, as the digital economy expands, companies that ignore their customer’s demands to be seen and treated as individuals will struggle to retain market share and attract new business. Hyper-personalization is becoming an imperative for those who wish to continue trading in a digital economy. Below we take a look at why personalization is so important for the financial services sector, the obstacles financial services need to overcome and the benefits that await the companies that do.
Stepping into a digital age
Tailor-made experiences are a pervasive aspect of our digital age. Research conducted by Salesforce in 2020 found that 66% of customers expect companies to understand their needs and expectations. 52% expect offers to always be personalized and a whopping 80% believe the experience a company provides is just as important as the products and services.
Personalized offerings increase customer loyalty and provide companies with a competitive edge. In order to create these experiences, businesses need to leverage real-time data and generate insights by viewing the information through the lens of behavioral and data sciences. When done well, companies become able to deliver products and innovate services that are relevant to customers and context-specific.
Smart devices and real-time data processing capabilities are two of the elements needed to create personalized experiences for customers. Changing governmental and regulatory expectations are further pushing the anticipation of hyper-personalization for the financial services sector. The result is greater brand differentiation, increased customer engagement (and therefore retention and lifetime value), and greater financial inclusion for traditionally hard to service segments of society.
The hurdles of hyper-personalized customer experiences
Personalized customer experiences are reliant on large stores of data. On the face of this, financial institutions appear to be sitting on a goldmine – data is hardly scarce. However, due to regulatory compliance and legacy technologies, much of the information in the hands of this sector is simply unable to be leveraged properly for the insights needed.
Data privacy, customer protection and security regulations are three of the areas that make mining the data needed for the creation of personalized experiences a seemingly treacherous endeavor. However, with technologies already available – hybrid clouds and artificial intelligence (AI) to name just two – these seemingly serious barriers to deriving insight from the data already available can be easily overcome. It is not a question of more data, or even lower security measures, instead it is a matter of data analytics and behavioral science capabilities. Businesses that are able to implement these tools effectively will be able to answer customer’s demands for streamlined financial journeys, live alerts and customer-centric business models that anticipate their needs.
Financial decisions are often difficult and require short to medium term sacrifices for longer-term gains. Our tendency to forego larger future rewards for smaller immediate gratification impairs the successful sale of financial products. On top of this, customers are often unaware of the financial products needed to achieve their goals. Companies in the financial sector that mine data stores for personalizing experiences can circumvent these behavioral inclinations. By creating customer journeys that evidence the gains realized through their products and addressing latent needs in ways that activate the brain’s reward system, businesses can generate good feelings about their products and services.
Partly due to the global financial crisis of 2008, trust in the financial services sector is relatively low. Gaining customer confidence can be a major hurdle for businesses wishing to expand or innovate new products. By taking a thoughtful approach to data collection – only requesting relevant information and being transparent about how that information will be used – financial institutions can build trust with customers. When it comes to collecting more personal information – life stage events or health data for example – it can help to detail customer benefits for sharing this information.
Breaking new ground with personalization
Behavioral science can deliver insights from already available data that enables the design and development of routine-shaping products and services. Products can nudge customers toward more constructive financial behaviors and forge deeper connections with the companies that provide them. Multiple firms have already employed similar techniques to become leaders in their fields – Netflix, Target and Amazon are just a few of the brands realizing gains from big data insights.
Netflix create hyper-personalized customer journeys for their 203.66 million subscribers with real-time behavioral data collection. The personalized messages, recommendations and artwork derived from the insights has helped them increase market share and boost brand loyalty year on year. Similarly, driving apps for car insurance companies serve both insurer and insured through a better understanding of driver behavior, reduced premiums and increased trust.
Financial institutions who leverage the customer data they hold stand to build customer loyalty, increase the life-time value of customers and innovate increasingly relevant products for customers while lowering their costs of acquisition and risk. Greater insight into customer behavior enables businesses to improve relevancy and inclusion while lowering their risk through better correlation of a range of data points.
One such application for the analysis of vast data sets with AI found borrowers taking loans on Wednesdays repaid them faster while seemingly inconsequential data points like the speed with which someone enters their birth date or the life of their smartphone battery when applying for finance, indicated the likelihood of defaulting on repayments.
Personalized customer journeys for the financial services sector is no longer a ‘nice to have’ but rather an imperative for future growth and security of the business. While barriers are real, they are not insurmountable. Customers are already demanding better use of the data collected by financial institutions, soon investors and stakeholders will be too.