Contact Center Big Data: 3 Things You Need to Know

by John Doane in Customer Service Outsourcing, John Doane, Order Management

What’s the big deal about Big Data?

It’s a topic on every industry conference and it’s a theme that seems to be streaming endlessly through our collective Twitter feeds – and yet there are so many different opinions about what Big Data actually is and how it should be leveraged.  We put together this primer on Big Data basics specifically for contact center people to bring some clarity to the subject as it relates to our work in customer service.

You need to know three things:

1. Contact Center Big Data is just data – only more of it

There are dozens of definitions of Big Data floating around the web, and a lot of them make Big Data sound like a tsunami coming your way. Just look at the Wikipedia definition of Big Data:

  • “Any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.”

If that doesn’t exactly make you want to roll up your sleeves and dig in, here’s Gartner’s definition of Big Data which makes more sense to business people:

  • “High-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”

The three Vs (volume, velocity and variety) make sense, but it still sounds pretty daunting. The definition that I find most useful is from an article in Forbes:

  • “Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.”

That definition makes it more clear what we are working with and what we can do with big data.

Contact centers and contact center outsourcers already work with traditional sources of data, which include product transaction information, financial records, customer satisfaction surveys, call logs and voice recordings. And most contact centers are either embracing – or acknowledging the need to embrace – digital sources, such as web behavior and social network interactions – Tweets, Facebook posts, and the myriad of other places customers can and do post information. However, this new wealth of unstructured data is often text-heavy and requires new forms of data mining to gain actionable, valuable insights.


2. Big Data can improve agent performance

In the contact center industry, we’ve always been big believers in the saying, “What gets measured gets attended to, and what gets attended to gets done.” That’s why we measure everything and use that information to improve quality and efficiency of service. So, to be fair, we are already in the business of big data (measuring everything) and analytics (using that information to improve). The exciting part is that evolving technology offers the following opportunities:

  • More things to measure (such as social network interactions)
  • More ways to measure it (such as advanced speech analytics and deeper dives into user’s web behavior)
  • More ways to integrate it (bringing us closer to a true 360-degree view of the customer)
  • More ways to make sense of it (with increasingly powerful analytics engines)

I could go on and on about the ways we can use big data to quickly and continually monitor, measure and improve agent performance, so let me just pick one example: speech analytics.

Contact centers are beginning to tap into the vast resource of recorded calls by analyzing them after the fact to identify not just key words and phrases but also emotion and sentiment in the caller’s tone of voice. This can provide agent-specific information that can be used in coaching, as well as more generic information that can be used to improve overall training in general. The success or difficulty that specific agents demonstrate with various types of calls can also be translated into call routing that better matches skills sets to customer context or needs.


3. Big Data can improve customer experience

The reason we focus on call center metrics is not just for the sake of improving agent performance. Yes, we want to make our agents and our processes more efficient to reduce things like Average Handle Time (AHT), increase First Contact Resolution (FCR) and reduce cost per contact (CPC). But none of that matters if the contact center is not producing a superior customer experience (CX).

That is where Contact Center Big Data offers the greatest opportunities: improving both customer engagement and the overall customer experience. And yet, according to research conducted by the International Customer Management Institute (ICMI), while 67% of contact centers are currently managing agent performance through the use of data, just 48% are using it to proactively impact customer satisfaction (CSAT).

One of the many ways Big Data can be used to improve CSAT and CX is by integrating systems for a 360-degree view of the customer, allowing for cross-channel engagement and real-time personalization.

Imagine that when a customer calls, the call is routed based on all past interactions with the customer. If the customer has recently had a call with high levels of frustration identified in the call recording, the call bypasses the IVR and goes directly to a live agent – one who has demonstrated above average success preventing churn with disgruntled callers. This agent is presented a dashboard that shows the caller has been tweeting about a problem with a recent purchase (something 60% of contact centers are not proactively providing, according to ICMI). Even before the caller says a word, the agent understands the caller and the context and has a far better chance of making the customer experience both positive and profitable.


Where do I start?

Even though Big Data is an exciting opportunity, it can still feel overwhelming. There are so many possibilities. If you are currently using Big Data and would like to talk about your next steps – or if you are just now looking into it and need a strategy for getting started – we would love to talk to you.


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