For banks, hyper-personalization is becoming as much an opportunity as an obligation in a market that is exploding with neo-banks and the risks associated with fraud. To achieve this, you need to know your customer well. Very well indeed. Datastax and JEMS give us two keys to success.
What is hyperpersonalization?
As consumers, we want offers that meet our immediate needs. It’s even a permanent need, as our daily digital life is so invaded by advertising cookies and other personalization algorithms: e-commerce purchases, video streaming and recommendations, music curation, etc. Hyperpersonalization in marketing means sending the right message to the right person at the right time.
In a study released in 2020, “Trends in financial services” Salesforce tells us that 55% of people only start to consider an offer if it is personalized. 66% of customers also expect financial institutions to understand their needs and expectations. Thomas Been CMO of Datastax explains:
“There is a real expectation on the consumer side. They don’t want intermediaries anymore and want an immediate impact. This is especially true with services like payments or cryptocurrencies. These offerings must take into account the value to the customer as well as their financial health. The financial services company must understand the customer and act as a partner.”
Customer knowledge: an obligation to achieve hyperpersonalization
There is a paradox to overcome. Financial services companies need to establish a relationship of trust with the customer at a time when the customer has less and less confidence in the financial system. Hyperpersonalization is the key to unlocking this situation. Knowing the customer’s context allows us to position them in an on-demand offer and to respond in real time to their needs.
Because the leaders in customer knowledge use all the data to understand them: not only the contractual data stored in a Datawarehouse but also the data coming from the applications that arrive in real time. Starbucks, for example, is continuously pushing highly targeted offers, which has boosted its sales considerably.
But to know your customer well, the reference system is no longer enough. The approach must be global. We are seeing more and more operational data being added to the customer’s repository, with a desire to mix the two worlds. The problem is that the tempo of a customer repository is slow: it takes time to verify the information and the figures. But customers don’t want that time anymore.
If CIOs continue to rely solely on their repository, not all data will be valued and this may lead to inaccurate customer knowledge which will lead to errors in the offers made and an increasing churn rate.
How to implement this hyperavailability of the customer relationship?
Pascal Dury, VP data management at JEMS explains. “There are two keys to success: having an MDM methodology in place and having a Data Centric and non Data Driven approach. Both are absolutely necessary”.
- Key to success #1: Apply the MDM processing method. This involves collecting, cleaning and identifying all data and creating the cleanest possible golden record at a given moment. Then we complete this 360 vision of the customer by enriching it with all known elements: contract, loan, interaction. One of the joint projects between DataStax and JEMS for the bank of a car manufacturer was to move from an IS based on contracts to a vision of the person. The driver becomes Mr. Martin or Mrs. Park and no longer a contract number.
- Key to success n°2: the Data Centric approach. This is the way we model the data of the banking institution. When we work on a use case (a new offer for example) we will take the data from different systems and reconcile them to create a use case. If another use case is requested, we redo the whole reconciliation protocol.
Being Data Centric will make us do this reconciliation only once. This translates into delivering use cases 3 to 5 times faster.
The Data Centric model optimizes reconciliation efforts
Hyperpersonalization is an imperative for financial services. Their customers want fast response times and real-time interactions. IT departments need a system with a solid, scalable foundation to handle on-demand use cases as well as the ability to scale up with additional real-time data.
For more information
About DataStax :Company Founded in 2010 in California to support Apache Cassandra. Datastax has contributed to the Cassandra, Pulsar, Kubernetes open source communities. Datastax has over 500 company customers worldwide including American Express, CapitalOne, Euronext, Fidelity, RBC, US Bank, Visa.
About JEMS : JEMS is a data industrialist whose job is to create and enhance the patrimony of its clients’ data. With more than 450 data and digital projects, JEMS is present in 13 cities in France and abroad.
Matthieu LENTZ – Directeur Marketing JEMS