Big Data – Bigger than Big

Big Data is so big it’s like contemplating infinity.

Big Data is so big it’s like drinking from a fire hose.

But you don’t have to drown in it.  Just as the amount of data grows, so have the tools and resources to help.

A few core questions are important as companies, include Equifax begin to craft their Big Data strategies. How do you transform Big Data into customer insights? How do you derive fresh, salient business intelligence that can lift your financial performance?

Used properly, Big Data can show you the full client wallet and financial situation to better reveal the broadest relationship potential. For existing customers and prospects, banks can use estimated investable assets, income, credit, likely investment style, age, or other criteria. Households can be assigned to a segment based on anonymous, aggregated financial, behavioral, and demographic characteristics. The bank can use aggregated spending behavioral data purchased from an external source to segment customers and identify optimal cross-sell opportunities.

Segmentation best practices work for both traditional data sets and Big Data from internal or external sources.

Here are five strategies to follow:

  1. Begin with the end in mind. Get agreement on the business goal and then design a segmentation approach around that goal.
  2. Build only what can be operationalized. Define the steps for turning segmentation data into insights and then into decisions. Make sure each step is feasible, affordable, and compliant with regulations.
  3. Use data that replicates the customer’s view, not just the bank’s view. For example, a bank needs to look beyond a client’s accounts at the bank and consider the client’s total wallet and needs. Share the insights gained from segmentation. Often, segment definitions can be applied without substantial changes by other core systems and customer-facing personnel.
  4. Minimize expenses and optimize investment. Understand cost-to-serve for key segments and use this as guidance for fee refund decisions, rate offers and pricing, customer experience improvements, and other decisions involving expenses and investments in Big Data assets.

In addition to defining customer segments for cross-selling, segmentation can be used to:

  • Size markets and identify growth opportunities for key target segments
  • Tailor online messaging by differentiating online visitors
  • Improve CRM and loyalty efforts by delivering communications using the right channels and relevant messages

Find out more about Navigating the Big Data Super Highway from Equifax and BAI.

How is your Big Data strategy evolving? Let us know in the comments.