This is a guest post from Julie Miller, vice president of product marketing for Clarabridge.
Customer centricity and optimization are top of mind for many executives. Surveys used to be the primary method by which companies collected and acted on customer feedback to improve the business. As survey response rates have drastically declined in recent years, business leaders are left with statistically less reliable data from which to measure and drive business action. As a result, more organizations have begun using contact center data as a source of insight.
By analyzing real interactions between customers and agents (human and bots) in the contact center, companies can receive valuable insights about the customer experience that, when acted upon, can increase loyalty, reduce effort and churn, showcase product, sales and marketing opportunities, and ultimately drive revenue and reduce call center operation costs. What can companies learn from contact center interactions, and how can you gather that data to make more informed decisions using contact center analytics?
Contact center interactions are a trove of useful information, but they must be mined correctly. Legacy initiatives to understand the customer experience have heavily relied on surveys to gauge how customers feel about your services. Oftentimes, however, the customer is filling out the survey long after a series of negative interactions have occurred. By then, it’s too late for customer support to resolve issues and retain that customer!
Every interaction a customer has with your customer service teams leaves a trail of data. As customers move from automated self-service channels to human interaction in contact centers, the sentiments they express in their speech or text change. What begins as a neutral and productive tone becomes more emotional and negative as poor experiences add up and the customer expends more effort to solve their issue.
If you could analyze those shifts in emotion and effort across the customer journey, you could uncover the root cause of channel hopping, repeat contacts, low satisfaction and identify areas of improvement aimed at customer retention. Interaction analytics in the contact center enables you to dig deeper to uncover the key insights you need to provide the best customer experience you can.
Customer interactions are complex and filled with many kinds of data. While it first might seem overwhelming, there are a few ways you can start collecting information in preparation for a deep analysis.
Your contact center is likely handling far more interaction channels than just phone calls. Emails, chats, private messaging and social media posts all contain valuable information — and can be a much more cost-effective method of communication. If you’re already recording phone calls and surfacing operational metrics using speech analytics, continue doing so, but you should also expand your analytics to include all digital channels of engagement. A richer data pool leads to more finely tuned insights you can deploy in your contact center. To this end, you will need an enterprise-grade text analytics platform capable of handling large data volumes at scale. It’s not enough to simply categorize topics of conversation, either. To get the maximum value from cross-channel customer experience analytics, you will need exceptional Natural Language Understanding capabilities to derive additional insight about emotion, effort, intent, and sentiment. It’s this information that helps drive action.
Contact center analytics is often process focused, measuring average handle times (AHT), acoustic quality, or call resolution (binary yes or no). While slow resolution or poor audio or repeat calls might explain the reason behind low customer satisfaction scores, more concrete insight can be derived by listening to the words the customers themselves say about the experience. Combining comprehensive listening with a shift to customer indicators such as effort, emotion, sentiment and intent tells a more complete story about the customer journey and allows you to better anticipate when customer feelings about your company will shift.
My company surveyed contact center agents and found 26% of them reported their center collected feedback in the form of surveys after customer calls — and 12% reported no feedback at all was collected! With limited customer feedback from surveys, you won’t be able to make insight-backed decisions to improve your contact center’s interactions. Contact center analytics can help you expand your data sample size to understand how all your customers really feel about your products and services. The processing power in analytic solutions will also enable you to gather useful data on all your customer interactions to help drive continuous improvement.
Once you’ve analyzed the interactions in your contact center and understand the issues, you can then operationalize the insights through prioritized action. For example, customer effort directly impacts customer loyalty and can be used as a leading indicator. If they’re loyal to your product, they’ll go through multiple steps like self-service and contact center outreach to solve issues before considering a different company’s solution. Insights from your contact center can illuminate points of process or product friction, from which you can prioritize action to improve the experience and retain customer loyalty.
While improving customer experience is a clear benefit of interaction analytics, you can also learn more about what product or service features most often frustrate customers. Your product development team would surely be grateful for direct customer feedback to improve product or service offerings! Better products and services lead to higher customer satisfaction and retention rates, boosting revenue growth and reducing the volume of issues your contact center faces.
Contact centers are a gold mine of information waiting for you to explore. By listening to what customers express during each and every interaction with your company and understanding drivers of contact, emotional shifts, and the root cause of friction that impacts effort, you can prioritize continuous improvement actions for a positive impact on customer experience and, ultimately, your bottom line.
This is a guest post from Julie Miller, vice president of product marketing for Clarabridge.
About Julie
Julie Miller is the vice president of product marketing for Clarabridge, the leading provider of Customer Experience Management (CEM) solutions for the world’s top brands. In her role, Julie leads a team of tech-savvy creatives to clearly articulate the business challenges that Clarabridge solves, explaining how the technology works and showcasing real and measurable value. Prior to Clarabridge, Julie held product marketing roles at companies such as Approva, acquired by Infor, Rosetta Stone and Ntrepid Corporation. With more than 20 years of experience, Julie is passionate about educating buyers to make informed purchase decisions.
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