Using Big Data to Build an Integrated Voice of the Customer Program: A 6-Step Guide


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In my last column I introduced the need for “Measuring and Mastering Omni-Channel FCR (web, IVR, centers)”, noting that today customers have 15 or more channels by which they can communicate their wants and needs, their problems and suggestions. The problem is that these contact channels are often embedded in different data bases and as a result different teams administer or respond to them, creating a disjointed experience for customers and for companies.

It’s important to “measure and master” all of these and other channels as VOC (voice of the customer) opportunities in order to listen to the customer, But, by the same token, VOC inputs or “sources” are collected and analyzed all over the place, robbing the “users” from obtaining the best possible data and gaining more powerful insights. In the omni-channel case and this VOC case, what’s needed is a way to build an integrated VOC repository and enable all possible users to access it. Enter the power of Big Data.

Over the years in my consulting work and in chairing the Global Operations Council1 I have been compiling how many different channels and places where VOC can start, in other words “What are all of the sources of VOC?” Here’s a list of 40 VOC sources, some well known and some less understood:

In order to build an integrated VOC program (I-VOC) to gain more powerful insights, on both the revenues side and cost side, the following 6 steps will get things into focus:

1. Inventory your current VOC sources

Clearly 40 possible VOC sources is daunting, but in this 1st step enables you to figure out which of the sources is in place today and which ones are no longer being used; where they are collected and housed; and how they are accessed. It will take some time to gather all of these data points since some might be “owned” by Sales, Marketing, Customer Service, the Executive Office, PR, or other groups.

You might want to score each of these VOC sources with one of these five codes: 4 = used “globally”, all over the place; 3 = used in parts of the company, only; 2 = used rarely; 1 = formerly used; 0 = never used. There’s no magic distribution, but it might surprise you to find out how few of these sources your company is using.

2. Create a global taxonomy

As you inventory your VOC sources the next step is to create a global taxonomy, a coding scheme that will allow you to “unlock” value from these sources. I like seeing a succinct list of 30-50 “customer contact reason codes” that my co-author David Jaffe and I presented in our 1st book The Best Service is No Service2. For example, “my product came damaged” and “I’d like to get this [item or service] from you.”

3. Align VOC sources with objectives

In step 3, you align each of the VOC sources – across all 5 scores – against one or more of five objectives: (a) Contain operating costs; (b) Live with limited capital; (c) Increase customer experience; (d) Improve agent satisfaction; (e) Boost revenues; and (f) Enable virtual multi-center operations. You can then see how many of the VOC sources can contribute to, for example, (e) boost revenues – and how many of those VOC sources you scored 4 or 3 (in place today, globally or locally), 2 or 1 (rarely or formerly used), or 0 (never used).

If you have more 0, 1, or 2 scores than 3 or 4 scores, then this should signal the need to expand the use of VOC sources. You might also want to align these VOC sources with the 7 Customer Needs and 39 Sub-Needs that my co-author and I shared in our second book Your Customer Rules! 3 to see how you’re doing versus the “Me2B Leaders” we researched and profiled in this book.

4. Use Big Data to build I-VOC

Now comes the fun part, pulling together all of the available VOC sources into a centralized database, modeling it to contribute to the objectives. Big Data is made for this step, “mashing up” different data, “cleaning” those data, and “learning” from models to improve the accuracy of the solution. Specifically, you can use Big Data tools to pull in all of the VOC sources, associating the VOC sources with the objectives and modeling all of the factors to determine best weights. This step is related to the older term EFM (Enterprise Feedback Management) that Forrester defines as

“A system of software and processes that enables organizations to centrally collect, analyze, and report on feedback from key customer groups and tailor insights for various internal users.”4

While there are many EFM vendors that claim to be able to pull together all of these VOC sources, Big Data solves the big challenge of mashing, cleaning, and learning.

5. Assign VOC sources/objectives with users

In this step you will assign each of the VOC sources and their aligned objectives with internal users and key stakeholders across your partner ecosystem. Among the candidate users are executives and analysts in sales, marketing, supply chain and logistics, R&D and product design/development, and field service. From your EFM or Big Data I-VOC reporting you can then provide timely updates to these users including word spotting and data mining, linking the users with the VOC source material.

6. Measure results and upgrade I-VOC

The final step ties all of this together and creates a continuous improvement process. By measuring the results of I-VOC initiatives you can track progress along the five objectives, e.g. reducing operating costs (objective #1 “Contain operating costs”) and test the responsiveness and sensitivity to various actions that the organization has been taking.

As a result you can then upgrade the I-VOC, adding or modifying VOC sources or expanding the reporting and the number of users. As more powerful insights become known across the company, more and more users will seek details and inputs from these VOC sources and I-VOC will be off and running!


1 In early 2002 Alan Winters asked me if we could pull together our old “Rolodexes” shortly after I had left Amazon, to get customer service professionals together in a safe environment without direct competitors or vendors, in order to share “best practices” but also “worst experiences”, meaning what didn’t work. As a result I formed what’s now known as the Global Operations Council (GOC for short) where 41 organizations share their best practices and worst experiences around topics such as VOC, contact center operations, and business process outsourcing. At the end of April 2017 we will hold the 30th GOC meeting at Google’s YouTube offices.

2 The Best Service is No Service: How to Liberate Your Customers From Customer Service, Keep Them Happy, and Control Costs Bill Price & David Jaffe (Wiley 2008). Based partly on my years as Amazon’s 1st Worldwide VP of Customer Service, but also on “Best Service” providers around the world who have made it easier for their customers to do business with them, we proposed 7 Drivers that start with “Challenge demand for service”:

  1. “Eliminate dumb contacts”
  2. “Create engaging self-service”
  3. “Be proactive”
  4. “Make it really easy to contact your company”
  5. “Own the actions across the company”
  6. “Listen and act”
  7. “Deliver great service experiences”

3 Your Customer Rules! Delivering the Me2B Experiences That Today’s Customers Demand (Wiley 2015). Here are the 7 Customer Needs that Lead to a Winning “Me2B”Culture; each Need breaks down into a total of 39 Sub-Needs.

  1. “You know me, you remember me”
  2. “You give me choices”
  3. “You make it easy for me”
  4. “You value me”
  5. “You trust me”
  6. “You surprise me with stuff that I can’t imagine”
  7. “You help me better, you help me do more”

4 accessed 13 March 2017

Bill Price

Bill Price is the President of Driva Solutions (a customer service and customer experience consultancy), an Advisor to Antuit, co-founded the LimeBridge Global Alliance, chairs the Global Operations Council, teaches at the University of Washington and Stanford MBA programs, and is the lead author of The Best Service is No Service and Your Customer Rules! Bill served as's first Global VP of Customer Service and held senior positions at MCI, ACP, and McKinsey. Bill graduated from Dartmouth (BA) and Stanford (MBA).


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