Putting data at the heart of a customer-centric approach
By James Johnston, Regional VP at Cloudera
Competition in the financial sector is fierce when it comes to delivering on customer service. As challenger banks continue to make an appearance on the scene, they are consistently outpacing and outshining the legacy players with the choices they make available to consumers. In fact, according to KMPG, fresh faces such as Starling Bank, are leading the way in the UK when it comes to excelling at customer experience. When it is taken into consideration that customer-centric banks can benefit from 55% higher returns, it is clear financial institutions need to get this part of their offering right. To master the art of customer service, and maintain a competitive edge over their rivals, there is only one place banks should turn to. Their data.
Driving decisions with data
For financial organisations, data and analytics is the key to knowing exactly which products and/or services should be updated or introduced, in order to best meet the needs of the customer. Through analysis of data sources such as investments, account activity and loan requests, banks can gain a comprehensive understanding of their clients and deliver the tailored experience that is expected. However, these traditional data sets are only the tip of the iceberg. Due to the ever growing amount of data customers are producing, there is now a plethora of data sources that those within the financial services can tap into. For example, unstructured data feeds such as chatbots, location data, social media streams and clickstream data, all offer invaluable insights into clients. In bringing together the data from sources both old and new, these companies will be much better equipped to understand their customers and innovate their experience.
To truly maximise on this data streaming, from across the business, it is vital that finance organisations have the right tools in place. The correct solutions will provide organisations with a single point of visibility over their data, irrespective of where the data has come from or where it resides in the enterprise. This will enable financial institutions to carry out real-time interrogation of their data and extract the value-added insights needed to improve the services to customers. An example that can be drawn on to illustrate this is in fraud detection. With the ability to consume, analyse and derive patterns typical of fraudulent activity, as it is happening, businesses can more easily alert clients and resolve any issues before they escalate.
The bountiful benefits of a connected lifecycle
It is clear that, to excel at delivering on customer experience, having visibility over all data is key. As a result, the emphasis must be placed on building a connected data lifecycle that allows for a comprehensive view of the entire data journey: from edge to cloud. It is this fully connected data, and visibility over it, that will ultimately underpin the success of banks wishing to remain at the forefront of the industry.
However, making improvements to customer experience is not the only benefit that comes from having a connected data lifecycle. Other critical business goals, such as the following, can be met more easily when financial institutions take a data-led approach:
- Driving customer loyalty and long-term retention
- Analytics-driven customer engagement tools, such as feedback analysis, digital assistant and customers surveys are all methods through which financial companies can collect information. Obtaining real-time insights that can then be used to inform positive changes for clients, in near to real time. Despite the ever-changing needs of customers, this continuous assessment of data can enable businesses to stay in tune with what they want and deliver accordingly.
- Expanding existing business
- When armed with a holistic view of their clients, including each interaction they have with the organisation, financial institutions can seek chances to proactively offer a new service or product. In the case of cross-selling, it is vital that the sales team has access to the customer’s entire profile, including their history and previous searches, in order to offer the most appropriate product. However, if the various data sets relating to clients reside in silos, determined by how the data came into the business, this process can be delayed. As a result, the customer’s interest may waiver and they could leave in favour of seeking alternative options. This is why it is paramount that financial organisations have access to the data from across the enterprise. Armed with this, teams are better placed to cross-sell their products and successfully build upon their current client base.
- Acquiring new customers
- Using techniques such as segmentation, businesses are able to analyse and profile all their existing customers. In turn, companies can draw on these insights to create tailored messaging and fine-tune their outreach to prospective customers, knowing what is likely to entice them based on similar customer data. The guesswork is then taken out of targeting and instead grounds outreach in factual insights from existing customers.
Leading by example
Two examples of organisations that have used data to attract and retain customers and stay ahead of the curve are DBS and Rabobank.
DBS, one of the leading banks in Asia, realised that it needed to become more data-driven if it was to successfully provide a high-level of service to its customers. However, the businesses’ existing technology stack, used to support advanced analytics, did not have the flexibility to support this work, nor was it cost-effective to scale. To overcome this, DBS built an enterprise data hub and central data team with Cloudera, which now enables employees to regularly experiment and be at the forefront of innovation. This has also allowed them to gain a better understanding of its customer’s experiences. In addition, DBS utilised the knowledge and data to apply human-centred design to its services. It now has the ability to store and analyse billions of events within its modern data platform, meaning DBS can proactively share insights its customers need, before they ask, thus delivering a better service and effectively engaging customers.
Rabobank needed to help its customers, including small businesses, to improve debt settlement in order to become self-sufficient. To do this, the company required access to a mixture of timely, accurate and high quality data, which it could share back to customers, on demand. As such, Rabobank adopted a solution that could ingest large quantities of streaming data and was able to cope with huge amounts of pressures related to high levels of data processing. With these technologies in place, Rabobank was able to quickly process real-time and historic data simultaneously, further improving its employees capabilities to run queries faster for customers. From up-to-the-minute transaction records to customers’ loan repayment patterns, the financial institution can now provide its customers with immediate access to the data insights needed to better understand the current state of their financial situation. In turn, Rabobank is able to provide next level customer service and insight.
Keeping ahead of the competition with data
The fight amongst financial institutions to outshine and out-maneuver one another is ongoing, and will likely be even more fierce in the aftermath of 2020. Failing to deliver on customer experience, even once, might mean a bank risks losing valuable customers to competitors. However, through harnessing data and then being guided by the insights it delivers businesses can provide solutions that sets them apart from competitors. It will be those organisations that invest in connecting their data lifecycles, in order to create actionable intelligence that improves the customer experience, that will thrive in the long term.
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