Data and advanced analytics lie at the core of every financial institution wanting to build stronger engagement capabilities. Unfortunately, many organizations continue to struggle to apply data that will improve the customer journey, or to move from reactive to proactive communication.
To build a successful consumer engagement strategy, banks and credit unions have to better understand — and in real time — the consumer opportunities and threats that data reveals. The challenge: Most organizations have cumbersome data and analytic back offices and outdated data policies. And they lack sufficient talent to make the application of insights timely and reliable.
Creating Personalization at Scale and in Real Time
Customer engagement leaders know that the key to a strong customer experience is to behave like a financial relationship management “concierge,” proactively providing insight to the consumer based on real-time financial opportunities or threats. Is there more money in a checking account than normal? A skilled concierge proactively asks the customer if they can move some funds to a higher-yielding savings plan for them. On the other hand, are funds in the checking account running low from an historical perspective? Or is a loan payment coming due? The engagement leader moves funds accordingly … in real time.
The entire process must run seamlessly, with minimal consumer intervention required. Over time, the consumer should believe in the decisions being made on their behalf, in much the same way that they would feel being handled by a financial advisor who treats them as the largest relationship in their portfolio.
The power of data, advanced analytics and artificial intelligence will be at the foundation of consumer engagement, creating autonomous, real-time decisions without human intervention. Because the decisions are made mostly through instant machine-learning capabilities on an individual basis, the deployment of personalized customer engagement will be completely scalable across an organization at a nominal variable cost.
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Bringing Engagement that Improves over Time
The beauty of digital engagement driven by data, advanced analytics and AI is that a dialogue can be created across a broad range of topics. Instead of trying to sell a limited range of products in a program-based environment, all products and services can be included in the conversation, based on identified need.
Each interaction is based on the individual profile, preferences and behavior of the consumer. With the integration of chatbots, voice and live agents, consumers can provide feedback on each communication and interaction, allowing models to improve and become even more personalized over time. The learnings during the process not only makes the engagement more personal, it makes it more powerful because recommendations will be more accurate.
While what’s learned will potentially increase the amount of dialogue over time, personalization and contextualization improves, as do results and revenues. More importantly, the learnings will be shared across the organization, making every contact point (human or machine) more intelligent and consistent. This democratizing of customer insights across the organization will also make business projections more accurate.
Integrating Social Media Signals for Consumers’ Benefit
Traditionally, customer acquisition, onboarding, cross-selling and loyalty were all supported through the use of internal data and insights. The response to a marketing solicitation, the change in balances, the opening of a new account, or some other trigger created the opportunity for potential engagement. For the most part, these activities were centralized within the financial institution’s database or on channel-based transaction histories.
In the future — and that’s today — there is no reason to limit signals of intent to banking transactions. Instead, every engagement that could have a financial potential can be included. Consumers may express a financial goal, need, concern, change in lifestage, or future opportunity or threat on social media, in discussions with your call center, as part of digital content interactions or even mass media absorption.
Combining insights from all of these touchpoints will create an even more robust profile of your customers that can improve engagement success. Remember, consumers no longer walk into a branch or pick up a phone to voice a concern or to make a purchase. Instead, they often interact on other channels hoping that their financial institution will “figure it out.”
Reallocating Resources to Make Consumers the Focal Point
The future of customer engagement leverages data, advanced analytics, modern marketing technology and expanded communication channels to spot changes in consumer behavior almost instantaneously. In a manner similar to the power of technology in today’s modern automobile, the goal is to find the best possible route to an intended future destination with minimal risk. If a potential hazard appears unexpectedly, or an opportunity to reach a destination becomes available, the automobile responds accordingly.
With advanced technology, machines can find engagement opportunities with little intrusion by humans. This frees up marketing and data personnel to focus on design, strategic direction, organizational integration and agile test-and-learn scenarios that will improve results. The success of these engagement tests will also help the innovation process, selection of technology and open banking partners, human resource allocation and changes is delivery.
To facilitate the future of engagement will require strong leadership support. Not only will investments need to be made in technology and training of existing personnel, but a culture shift will be required that sets the foundation of an entirely new focus on the consumer. The consumer will become the center of all initiatives, with product goals and resource allocation being determined by consumer needs and behaviors.
While it will be difficult to let go of past methods of communication and selling, the results will be stronger with metrics that can support every step of the process.