The Rise and Rise of Financial Marketing Databases

The era of “big data” is upon us, especially in the financial services industry where a wide range of products is delivered in a variety of channels and marketed through multiple media.

In the digital age, your database is the core of your marketing programme. It should be driving your strategy, which requires advanced data capture and integration. The amount of data you can gather is what will determine your level of success.

It starts with the proper context of the customer. Who are they? What do they want? How and when do they want it?

The effectiveness of your database hinges on connectivity – the ability to appropriately capture and use data across multiple channels – which will require effective identity management and a strong data management tool.

  1. Customer data

The most powerful and predictive data for financial marketers comes from data provided by customer interaction and behaviour. While most institutions have built adequate and even comprehensive marketing databases that incorporate demographics, balances and product use; some data points may have been overlooked:

  • Length of relationship– Where are they in the lifecycle of their relationship with the bank?
  • Life stage– In which phase of their lives are they?
  • Expanded demographic data– What other preferences and propensities can be correlated to financial service product needs?
  • Lifetime value– What kind of long-term potential for revenue do they represent?
  • Net worth– What is the value of their total wallet, not just what they have at your institution?
  • Location– What is their physical proximity to a branch?
  • Abandoned application data – Important for follow-up marketing.

Strategix’ data management tool, myDMT, can be used to support master data management by removing duplicates, standardising data (mass maintaining) and incorporating rules to eliminate incorrect data from entering the system in order to create an authoritative source of master data. Master data are the products, accounts and parties for which the business transactions are completed.

  1. Channel interaction

The vast amount of detailed transaction data distributed across multiple channels and product categories (e.g. silos) makes it difficult for companies to tap into their transactional data. The optimal approach is some kind of “operational data store” that captures transactional data and summarises it for practical applications. Some examples of these types of data are as follows:

  • Transactional channel usage– Branch, online, mobile, ATM and call centre transactions.
  • Single vs. multiple channel users– Understand “traditional” and “digital-only” groups.
  • Contact and problem resolution preferences– It’s important to understand how customers want to interact with you – they may prefer different touchpoints for problems versus marketing or general contact.
  • Customer dialogue disposition– What were the results when you made contact via phone or email?
  • Social media identifier– Consumers who “like” your Facebook page are likely to be highly engaged and have a favourable attitude towards your company.
  • Frequency of interaction– How often does the consumer interact with your company?
  1. Media viewing and response

It is important to capture response data and use it for remarketing. If a consumer has previously responded to marketing offers, he or she is more likely to respond to subsequent campaigns. Here are five examples of media channels that provide great opportunities for response capture:

  • Online search as well as display advertising– Using cookies and behaviour data.
  • Direct mail– Using “responder” identification.
  • Email– Click-throughs and conversions.
  • Outbound telemarketing– Via captured disposition.

Because all these various data streams involve a mix of addressable and non-addressable information, you’ll need an “identity management system” to tie it all together.