The digital world has redrawn the map when it comes to what constitutes customer intelligence. While digital footprints and user consumption behavior have come under intense analytical scrutiny over the years, some organizations are playing catch-up like never before on this front. Outdated methods of customer data storage and “analysis” are killing businesses, and the worst part is you don’t have access to the data (or insights) that will tell you how to change course.
For better customer experience, data-driven decision-making is not an optional strategy but an imperative to drive meaningful customer engagements. If you are a financial services firm, it impacts how your institution predicts a customer’s risk appetite and churn patterns and understands their financial goals and imperatives. Focusing on the right data can lead to impeccable decision-making that benefits the organization as well as the customers.
When it comes to knowledge management and resulting customer engagement, financial institutions in many segments remained challenged for primarily two reasons.
1. Scattered and siloed customer data
This is true for most client-facing businesses in that there’s no single source of truth when it comes to customer data. The information you need is disconnected from the customer profile and most often saved in siloes. Making informed decisions based on such incomplete datasets becomes unnecessarily complicated or, more often than not, leads to the wrong decisions. This is because multiple layers of data silos need to be penetrated to get the full picture. These include:
- Departmental silos: Marketing, sales, customer service, and other departments interact differently with customers. They all store this data in isolation, leaving every other department with no comprehensive view of the customer.
- Product silos: Customer data for their savings account, loans, Stock holdings account, etc., are stored separately, so it’s impossible to readily understand the customer’s true financial position.
- Ownership silos: The data you need is spread across third-party vendors, partners, or subsidiaries. Accessing and integrating this data with what you possess is a prolonged, slow and expensive process.
- Channel silos: Customer touchpoints like mobile, website, in-branch, through customer reps, etc., all collect and store data individually, making it tough to understand their preferences.
The data that you do manage to get after breaking through these siloes are inconsistent, or in some instances, inaccurate. Making informed decisions without untrustworthy information, in turn, leads to ineffective outcomes that don’t drive the best customer experience.
2. Central repositories of unintelligence
Since the data you need is stored in multiple (unconnected) locations and formats (both structured and unstructured), combining and analyzing such data first requires integration and can also lead to inconsistencies and inaccuracies in analyses. To combat this twin challenge, it makes sense to think of a central repository as well as put in place some reconciliation intelligence in the same.
Data in cold storage is still passive and siloed. It’s just that they’re all siloed together now. There’s no real-time processing or analysis. The data may be unstructured, therefore not actionable and cannot be used for quick decision-making unless you spell out the exact details you need.
In most cases, the central repository of data does not drive any business decisions, contribute to better customer engagement, or add any real value to the organization other than fulfilling compliance and regulatory requirements.
With the advent of AI-enabled tools, there are now a range of Machine Learning based solutions that drive significant real-time intelligence on customer buying and engagement behavior when it comes to customer intelligence. However, despite the above revolution in AI-based tools and their impact on customer intelligence, as customers we continue to experience business interactions which tells us the business’ internal systems are not intuitively connected when it comes to leveraging customer data to drive intelligence and decision-making.
What can financial institutions do to turn this around?
Customer intelligence can only make sense if it is attached to the customer. For a data-driven customer experience, data must be easily accessible, accurate, updated in real-time, and, most importantly, flow as part of the customer’s profile.
A central repository cannot do that for you, whereas a powerful CRM or knowledge management platform can. Leveraging customer data across business units can help improve your current services and develop new ones.
Though most institutions understand the importance of doing so, the lack of the right technology prevents them from acting. So, let’s look at how a good CRM platform that is built around a knowledge management framework can help manage customer intelligence.
1. Single source of contextual truth
Even 100% factual statements can be misleading when taken out of context. This applies to customer data too. A good CRM empowers organizations to get a bird’s eye view of all customer data (including interactions, likes and dislikes, priorities etc.). This means sales teams, customer support, and marketing can truly understand the persona they’re targeting and look for behaviour patterns and preferences to make personalized recommendations. In the world of financial services when the customer has evolving needs, the role of contextual truth gains even greater relevance.
2. Elimination of manual data entry
CRM platforms can help financial institutions automate repetitive manual data entry by providing a unified interface to view all customer data. This gives employees more time to focus on building meaningful, strategic customer engagement instead of routine labour. Eliminating manual data entry also means fewer data inaccuracies and delays and real-time, transparent customer insights. In the world of financial services, particularly in the world of capital markets, customer feedback and insights are captured in conversation and voice-to-text technology helps to capture data in ways that were not possible till a decade ago.
3. Better customer service & insights
Recent studies from J D Power show that almost 80% of retail banking customers would continue using their bank if they received personalized support. Yet, it’s rare to see deeply personalized investment advice or services from financial institutions in that manner.
Collecting and crunching data should aid the personalization process. With a good CRM, support teams are not left scrambling for details when a customer reaches out to them. It enables financial institutions to easily collate the right data and provide customer support that is quick and accurate. Slicing customer data and insights intelligently allows for better pricing for specific segments as well as leads to a higher level of retention and overall customer satisfaction.
4. Improved customer retention
Most businesses will find that since 80% of their revenues come from 20% of their customers, retention is a core metric, especially for financial institutions. Providing personalized experiences with the right insights can help prolong the customer lifecycle, detect churn patterns, identify and target the right areas for cost-cutting measures, and so much more.
By accessing the right data at the right time, a finely tuned CRM enables institutions to address customer concerns proactively and improves customer retention rates significantly.
5. Accessible, not vulnerable
CRM makes it easy for employees to access relevant customer data. Setting roles and permissions within the CRM makes it easy to control who gets access to what data and creates a streamlined workflow to provide further information on a case-to-case basis. This also addresses confidentiality requirements as well as wider organizational controls.
Additionally, the organization must ensure that data stored in the CRM is secure and GDPR-compliant, unlike other modes of central data repositories.
When it comes to financial services delivery and engagement, context is vital to add real enduring value to the customer. Managing customer data the right way provides visible and undeniably better results. You might hire the best minds in the industry, but leaving them scrounging for customer insights wastes time, effort, and opportunities to do better. In our journey of building a world-class CRM experience, our recent offering incarnation in the form of InsightsCRM builds on years of experience and learning to deliver material value in the area of organizational knowledge management and customer engagement. When your customer data starts “talking” to you without much effort, it sets in motion a set of events that makes the customer engagement and retention challenge effortless and ensures an entirely new culture across the organization.