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3 Ways Data Can Drastically Improve Your Customer Service AND Decrease Costs

By on April 26, 2016

While most believe we’ll avoid another recession, companies remain challenged to “do more with less.” At the same time, customers are increasingly expecting more. More self-service, more immediate response times, more bang for the buck.

The good news is that data sits squarely in the middle of what once may have been irreconcilable differences. With the right tools you can correlate all kinds of customer service related data to reveal:

  • Where are we inefficient?
  • Where can we save money?
  • What opportunities for growth are we missing?

What to Ask Your Data

There are a few scenarios to consider when deciding how data can directly improve customer satisfaction, and decrease costs:

  • Are you looking at the most complete picture possible? Customers are more self-serving than they used to be, and the experience is as multi-channel as ever. Connecting those dots will be invaluable for the business and customer alike. For example, according to the latest benchmark (link requires registration) from The Service Industries Association, the average cost for a field service call is a little over $1,000. Compared to resolving an issue over the phone, field service calls are a “lose-lose”: the customer waits longer for a less-convenient solution, and the company spends more money. A lot more money. This use case talks about how successful telecommunication companies are correlating and analyzing customer interactions across call center(s) and field service teams. And going above and beyond here means incorporating traffic from their website, plus what the customer did in their mobile app before calling for help.
  • Are you mining your internal data to find inefficiencies, or areas to lean in? Don’t discount the human factor. Call center agents have lots of technology at their fingertips to help solve customer problems. But that doesn’t mean they’ll all achieve the same results. Analyze how they use those tools and see if it correlates with reduced field service calls required. Do the best agents tend to have longer calls? Do they do more searches in the knowledge base, or use different keywords that return better results?
  • Can you discover a problem before it exists? This video describes how leading home automation provider Vivint analyzes sensor and IoT data to better understand and service their customers. One of the things that they can see is when their data is telling them that a certain sensor or battery may be getting close to failing based on historical data. If they’ve got a field technician in the local area on another call, they can have that technician make a proactive service call to service equipment or batteries ahead of an outage. It improves the service that they can deliver for customers, and eliminates single-stop, reactive field service calls.

4 Steps to Being a Customer Service Hero

  • Use All Your Data. Getting the complete picture requires data on web interactions, call center interactions, service calls and your customers. This data comes from multiple places, and is in varying sizes and formats? Can you work with structured, semi-structured and unstructured data? Can you pull data from both external and internal data sources you need? And can you quickly and easily join disparate datasets for the most complete picture possible?
  • Do It Yourself. You know the problem best, so who better to find the answers than you. You’ll need a self-service data discovery tool with user experience familiar to you. What’s better than an Excel spreadsheet like interface? And that tool needs to let the data tell you the answers.
  • Use the Results. Insights are only as good as the actions you take. You need to put those answers into trusted, repeatable processes? Can you schedule these analytics to be run on a cadence that works for your organization? Can your insights feed downstream systems your customer service teams use to so they can use the information everyday?
  • Embark on a Journey. Finding the answers for today’s issues is one thing. But, things change. Customers change. Products change. Service policies change. This problem and the required analysis is part of a continuous journey you will take for constant improvement of your customer service experience. When new data is added or new questions need to be answered, your data discovery platform must allow you easily expand your analysis to meet those new needs. It also needs to be collaborative and have governance facilities so you can work with your colleagues on continuous improvement.

Regardless what industry you’re in, there’s likely a competitor of yours just waiting to pick up any of your dissatisfied customers who, rightfully, might be looking for a better customer experience. Looking at your data, and acting on what it’s telling you, is not only possible, it’s going to become mission critical to stay competitive. And, if in those same exercises you can find ways to streamline your spend or shave off inefficiencies, you’re only going to further separate yourself from the competitive pack.

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John Morrell

John Morrell

John Morrell is Sr. Director of Product Marketing at Datameer.