We live in the era of the empowered consumer. Within financial services (FS), this means that customers – whether consumers or businesses – have more choice than ever before. In addition to the traditional suppliers of FS, there are many agile and customer-focused start-ups providing quicker, smoother and more effective approaches to FS, as well as other organizations such as supermarkets that have entered the FS market.
In the face of this increased competition, it means that FS providers must understand their customers better than ever. They must learn what customers’ pain points are, identify when they might be unhappy and be able to take concrete and positive steps to address them.
The ability to understand what a customer is interested in, is feeling, and their likely intent is therefore highly valued in 2017. That’s why so many organizations have made such a substantial investment in Customer Relationship Management (CRM) platforms, to manage customer data. But with most CRM systems unable to process unstructured data, how can FS firms capitalize on the insight held within the unstructured data they hold?
CRM: Yes but not only
FS firms hold large amounts of data on their customers – call notes, meeting minutes, social updates, user-generated content, emails, customer service records and much more. This big data means there is lots of information on a customer’s intent, preferences, and any potential issues, and to extract this insight, companies have invested heavily in CRM systems.
CRM has been a growth sector within technology for many years. In Gartner’s most recent ‘Market Share Analysis: Customer Relationship Management Software, Worldwide, 2015’ it was revealed that the CRM market software totaled $26.3 billion in 2015, an increase of 12.3% from $23.4 billion in 2014.
But despite this, CRM owners are constantly looking for ways in which to get more from their CRM system. The growth in customer data has outstripped the rise of CRM systems and has led to a ‘data blackhole’ in many enterprises, whereby the most relevant and insightful data is not being picked up and analyzed by the CRM system.
Most CRM systems work only with structured data, yet around 86% of enterprise data is unstructured. The issue is clear – enterprises are attempting to understand their customers based on a tiny fraction of the relevant information. Salesforce itself has estimated that only 1% of a company’s data is used by its CRM system, meaning that vast amounts of customer insight are left untapped.
Leveraging Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) and Machine Learning (ML) are critical technologies when it comes to empowering CRM systems, accessing and unlocking the unstructured data that is so important to successful client relationships in FS.
The sheer volume of big data in FS organizations can be bewildering, and it comes in files and formats that most CRM systems are unable to manage effectively. Unfortunately, this data is often the most valuable, containing rich insight into that particular customer and their specific needs and requirements. This unstructured data would include: any social content – Twitter, Facebook, LinkedIn, Instagram – by, and relating to that customer; email conversations between the customer and FS provider; service call scripts that detail any recent or historical issues.
This is the data that really enables an organization to understand its customers. By deploying AI and ML, organizations can collect data from multiple sources and in multiple formats, extracting fresh and insightful meaning from it and helping to deliver a complete view of that customer.
New Revenue Potential with Unstructured Data Insight
If an FS firm is able to enrich and unify any data type (structured or unstructured; internal or external) and index it for future CRM and client engagement use, so the value of that data grows. The insight derived from it can be used in a number of ways:
To drive value and grow business opportunities– knowing and understanding your customers means that new opportunities can be identified on a regular basis. Users can search for new insights on competitors, partners, markets, individuals and much more, all of which deepens their knowledge and understanding of each customer and provides upsell or cross-sell opportunities.
To anticipate customer needs – customer understanding can also be used to identify trending issues and anomalies around an individual client or group of customers and address these before they become an issue.
To adopt a client-centric view – having a 360-degree view of a customer, across all channels is a powerful asset for anyone in FS. Doing so means that VIP accounts are never overlooked and allows the targeting of clients at the right time with the right communication.
To free-up client management time – because all of the unstructured data is now included in the CRM platform, users are able to save substantial time when searching for information on clients.
Not deploying unstructured data within a CRM is potentially a major problem for FS firms. It means that huge swathes of potential customer insight are missing, which can have an impact on client service.
The implications of this are potentially dramatic. Given the increased choice and resources available to FS customers, what is their motivation to stay with an organization that does not understand their individual and specific needs?
Only through the availability of all relevant information does CRM become truly compelling and provide an organization with the customer insight required to thrive in such a customer-centric FS environment. But achieving this is a major challenge and requires AI and ML to really enhance an organization’s current CRM system.