How is AI changing customer engagement for financial services?
Everybody knows that customer engagement and customer experience play crucial roles in determining business outcomes. Despite becoming overused buzzwords, it’s been proven that improving customer engagement metrics—which leads to increased customer retention—has a multiplier impact on the bottomline. In fact, Bain & Company suggests that a mere 5% increase in customer retention could boost profits by as much as 95%.
The implication for companies is that,to acquire a competitive advantage, they must transition from product-centricity to customer-centricity. This is true regardless of industry, but it is even more applicable to financial services, where building long-term customer relationships is crucial. As more players continue to enter the financial space, competing over products is simply unsustainable. This is why forward-thinking financial services companies are leveraging the emergence of AI to gain this competitive customer-focused edge.
At AiDA Technologies, we understand how artificial intelligence can be used to enhance customer-centricity. Steve Jobs said it best:
You’ve got to start with the customer experience and work back toward the technology, not the other way around.
What is the difference between customer engagement and customer experience related?
To understand the impact AI is having on customer engagement in the banking and financial services sector, it’s important to first understand the relationship between customer engagement and customer experience.
The reality is they are vague terms, with varying definitions across different sources. At AiDA Technologies we define them as:
Customer experience – the customers’ overall perception of a business whenever they interact with it—whether it’s support or sales or marketing. It reflects their emotional experience during each interaction.
Customer engagement – more focused on the actions of your customers. Typical questions that arise are – how deeply are they engaging with the brand? Are they investing in more products? Are they spreading positive word of mouth? Improved customer engagement can therefore lead to tangible results, but it cannot happen without good customer experience management. Delivering superior customer experience is without a doubt the best way to boost engagement—and the bottom line.
Case in point: The power of customer engagement in the financial industry
According to research by Gallup titled The Financial and Emotional Benefits of Fully Engaged Bank Customers, more engaged customers—who are loyal and emotionally attached to the bank—resulted in the following tangible benefits:
- Increased revenue: An average of US$402 in additional annual revenue per customer (US$869 for the mass affluent segment)
- Higher wallet share: 10% greater wallet share in deposits and 14% for investments
- Stronger product penetration: An average of 1.14 additional product categories used
- Greater purchase intent and consideration: A much higher intent to invest in new products, open new accounts, and increase balances (an average of 30+% vs. under 5%)
- Fostering a lifelong relationship: 71% of fully engaged customers believe they will use their primary bank for the rest of their lives
How is artificial intelligence impacting customer engagement and experience?
The first digital revolution in customer engagement arrived in the 1990s with the internet. It saw companies scrambling to establish online footprints so prospective buyers could engage with them. The second revolution was the advent of AI, which is looking to be just as influential as the internet was.
The shift brought about by the internet was scale—companies could now reach more people than ever before. But such reach was mostly generic; everybody went to the same website and got the same message. AI upped the ante by allowing companies to add a crucial ingredient to the mix—personalisation. Thanks to AI, businesses can now enable real-time, scalable, and intelligent personalisation. It has resulted in nothing less than a fundamental shift in the customer engagement process.
Why is personalisation important for customer engagement?
While the internet permitted companies to reach customers at scale, personalisation still largely remained in the domain of face-to-face customer interactions—necessitating higher costs. In the financial services sector, this is evidenced by the different levels of personalised services provided to distinct client segments. High-net-worth individuals are assigned private bankers, while the mass market had to be content with branch staff and generic online banking offerings.
AI is now making generic marketing personalised, but without sacrificing scale. While the words ‘scale’ and ‘marketing’ have spammy implications due to old marketing methods, this is no longer the case. Spam-like tactics are and should remain a relic—the mantra moving forward is personalisation at scale.
Here is one example of how this is playing out:
Hyper relevant product trageting
The ‘old’ model of personalisation was based on analysis of demographic data, including age, income, and marital status. While this is still in use today, customers find it lacking—its hit rate is simply not very good. Research by Accenture found that only 22% of global customers think that the companies they do business with deeply understand their needs, preferences, and past interactions. To give customers what they want, companies must focus on the next generation of personalisation: hyper relevance.
Today, each customer generates a wealth of data, from credit card and ATM transactions to salary information. But often, these data points are disconnected and remain in silos, limiting their potential. With predictive analytics and machine learning, financial service providers can make sense of this increasing amount of data, remove them from their silos, and provide a singular holistic 360° view of a customer to provide hyper relevant product offers.
Now, instead of merely being able to provide products targeted to a specific demographic, they can now offer products personalised down to the level of the individual customer—a demographic of one.
For example, AiDA’s Smart Engagement Solution taps unstructured data sources including social media to create insightful user profiles. This allows banks and insurance companies to identify hyper relevant cross-sell and up-sell opportunities. It even proactively warns when there are signs of disengagement, providing the opportunity to take rectification measures.
What is the future of customer engagement?
The future of customer engagement is AI-powered personalisation.
From the users’ perspective, they will benefit from improved customer service and access to products and services that can truly meet their needs. And on the business side, banks and insurance companies will be able to understand their users like never before and give them what they want, when they want. In short, the future of customer engagement in the financial services sector is a holistic end-to-end customer management process powered by AI.
The results are manifold—higher levels of customer engagement lead to maximum customer lifetime value, greater customer retention, and a stronger bottom line. And most importantly, it’s a true win-win scenario for both the companies and the customers.