It’s no surprise that consumer-facing businesses with strong customer experience programs generate staggering amounts of data across a variety of touch-points.

Consider a retail bank, for example. Customers visit a branch, bank online, call customer service, and communicate with bankers by email on a daily basis. We believe that this avalanche of data can—and should—be mined to empower businesses to better understand their customers.

Collecting the Right Data, the Right Way

In this post, we review best practices that we’ve implemented in putting customer data to work. Though we use retail banking as an example, these steps apply to any enterprise with a large customer base.

A Structured Approach

A thoughtful, structured approach to acquiring and analyzing data is critical to the success of any Voice of the Customer (VoC) program.

  • Prioritize – We begin by identifying processes that have both strategic importance to the business and affect the customer experience.  For example, data collected during customer interactions with online properties, customer interactions during ATM transactions, or understanding experiences through channels that exist only for high-value customers. Once understood, we define their relative importance and prioritize.
  • Discover – During this step, we interview business and data owners to document and confirm their understanding of the data and its value to the business.
  • Stage – To prepare for downstream analysis, we obtain data from operational databases and stage it in an analysis workspace that we help our client to create.
  • Build and acquire metadata – We then help to develop contextual information about the customer’s interaction with the business. Having context about the customer experience—is this a high value customer, where is the customer engaging with the business, how many accounts does she have, how long has she been a customer—is essential for analysts as they draw insights about customers.
  • Determine usability – During this stage, we characterize the data, define its source, identify the number of records available, and document the existing text fields that contain customer verbatims.
  • Go / no go – Based on the initial assessment, we decide if the data source will likely provide insightful analysis about the customer experience. We make this decision for each data source, re-engaging with business and data owners where appropriate.
  • Data loading and analysis – After each of these steps has been completed, the data is ready for analysis.

What We’ve Learned

In our work with high-touch, consumer enterprises, we’ve learned that a thoughtful data acquisition process is a key component of an effective VoC program. It is important to focus on sources that provide actionable insights that can improve the customer experience.

In upcoming posts, our technical team will discuss the inner workings of the analysis process of VoC initiatives.

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