Finding (and Using) Insights from Customer Service Big Data

Knowing your customers is important for providing the best possible service, but how companies use customer data is more essential than ever for creating an experience with lastly positive impressions. Analytics drive a company’s ability to match a customer, for example, a 29-year-old male located in the Midwest, with the customer service agent best suited to address the issue at hand.

Software Advice, a web-based reviews and evaluation site for help desk systems, recently released a new report on what preferences millennials have for phone support. Using Big Data to Improve Call Routing in Customer Service points out that millennials are predicted to become one of the most valuable demographics over the next 5-10 years and are characteristically brand loyal if given goods and service they like.

So it stands to reason that accounting for the preferences of millennial customers will drive successful interactions and therefore profit for the business. This kind of thinking is what pushes smarter companies to re-invent everything from how they write their phone scripts to implementing contact center technology such as skills-based and analytics-assisted routing and intraday automation.

Back to the findings of the report: As one might imagine, millennials were more inclined to prefer a faster pace during a call (36%) and dealing with a customer service agent who was more casual (26%). Conversely, roughly 25% of baby boomers and Gen Xers preferred a faster pace. While it’s not surprisingly that the 65 and over crowd prefers a formal tone over a casual tone, the 55-64 age group was more inclined to prefer a casual tone, even more so than millennials. As the report puts it, “older callers prefer patient agents; younger callers prefer quick resolutions.”

Now, companies have lots of customer service big data, and the catch-22 is how to best utilize it for the greatest impact, such as how to provide service that’s aligned with customer demographics. Craig Borowski, the market researcher at Software Advice responsible for the report, says, “Some observers are skeptical about the claims made on its behalf. Can much business value really be derived from analyzing large sources of often disparate, unrelated data? The answer to that depends on who you ask.”

What this all stands to illustrate is a) customer service big data is valuable and not always put to use, and b) the best way to serve customers (like those millennials) is by using that customer data to make sure the right agent is available for the interaction.

It’s what we refer to as turning insights into actions, integrating the ACD and various call and customer analytics systems so that real-time adjustments can be made to the frontline staff. For contact center leaders, it’s a supply-and-demand issue: a fixed number of properly prepared and queued agents (supply) and a somewhat unpredictable volume of customer issues (demand). Intraday Automation makes use of all that big data to bring supply and demand into balance so you can serve your customers — whether baby boomer, Gen Xer, or millennial — in the most efficient and effective way.

About the author

John Englund

John is a copywriter at Intradiem. He has a background in print and broadcast journalism and digital marketing with emphasis on technology.

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