A guide to call center analytics
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Customers view the company as a whole, whether communication is with service, marketing, sales, billing or any...
other part of the organization. Accordingly, best-practice service metrics and contact center analytics enable holistic views of the company and the customer.
With the rapid expansion of multichannel service, the importance of end-to-end customer experience visibility cannot be overstated. End-to-end customer experience transcends product lines, geographies, functional areas, channels and time. According to recent research from Ovum, 74% of consumers use at least three contact center channels for customer service-related issues, and 44% of consumers prefer non-voice channels.
First call resolution (FCR) is often measured in the call center and sometimes separately for self-service. However, overall FCR—regardless of service channel—may be the ultimate measure of customer experience success. Customers prefer not needing service in the first place, but when they do reach out for help, they want to feel confident they’ve received an effective answer right away and move on to other endeavors.
According to eBusiness Customer Service And Support Benchmarks by Forrester Research Inc., only 23% of self-service Web pages ask customers whether the answer provided by a customer service channel solved their problem. By not measuring customer feedback, companies are ignoring an important aspect of customer experience management (CEM) technology.
Emotion analysis through text and speech analytics can paint a more complete picture when combined with the overall FCR metric, indicating the level of confidence customers feel about whether the answer they received has resolved the issue at hand.
Text mining applications can help companies analyze data within written records of customer interactions. For audio recordings, speech analytics applications can automate analysis of call samples using a wide range of filters.
The following metrics assess the customer experience in order of customer-centricity within each of these service channels: chat, communities, email, social media and text messaging.
- Percentage of chat participants acknowledging that a provided solution is successful
- Customer wait time during chat
- Customer requests for re-phrasing of questions and solutions
Ensuring a positive customer experience requires a blend of effectiveness and efficiency, catering to the customer’s circumstances. These metrics assess the agent’s ability to quickly assess customer context and access the needed information to the customer’s satisfaction. Text-mining applications can tabulate these metrics from recorded chat logs.
- Content rating
- Endorsements (such as “Tell a Friend” or “Like” links)
- Percentage of questions for which the question originator acknowledged the answer
- Percentage of visitors who post additional questions (unrelated to their first questions)
- Time from question post to answer post
- Repeat visits
Customers access communities to enhance their experience through others’ knowledge. High-quality, timely content and answers to customers’ questions determine whether customers will have a positive experience and whether they will trust the community as a useful resource in the future. Most community platforms enable content ratings and endorsements; it may be necessary to request additional functionality from the community platform vendor to track answer acknowledgment, answer timeliness and repeat usage of question features.
- Success acknowledgement from the question originator
- Incident turnaround time, by severity level and by customer-specified timing
- Longest delay in queue
Customers send emails to companies for a number of reasons. Some are too busy to call, while others have the extra time to wait for an answer. Still others want to receive lengthier instructions in writing. Although their response-time expectations are relatively lower, they may have a specific window of opportunity to receive a company’s reply to fulfill their needs. Automation of these metrics may require a request for additional functionality from the email platform vendor.
- Percentage of solutions acknowledged by recipient as successful
- Endorsement of solutions (such as number of shares, embeds, “Like” ratings, @replies, direct messages, comments, wall posts, third-party blog mentions)
- Time from originator’s post to solution post
- Increased usage of self-service referenced by a solution post
- Sentiment changes after solution post
Customers use social media to express themselves, learn from others, and help others avoid or gain experiences they’ve had. Prompt company response can engage the customer positively and have a far-reaching impact on other customers and prospects.
- Percentage of text message requests by repeat users
- Percentage of customers acting on text message account alerts
- Percentage of text message participants acknowledging solution as successful
Customers like text messages for timely updates and accessing information remotely. The flexibility and spontaneity that is unique to text messaging can have a great effect on the customer experience. SMS texting applications enable text mining to tabulate these customer experience metrics.
To effectively use customer experience metrics, organizations should research what prompts customers to use each channel and their specific expectations for that channel. Segment the customer experience metrics by what causes customers to use each channel rather than demographics.
The customer’s perspective is the key to excelling in CEM technology. Holistic views of customers, and measurement of multichannel performance as the customer sees it, will reveal substantial opportunities to differentiate organizations for superior customer experience.
ABOUT THE AUTHOR
Lynn Hunsaker leads ClearAction customer experience management (CEM) consulting, and has led CEM programs in Fortune 250 companies since 1989. She is on the Advisory Boards of CustomerThink, The Customer Care Network, Marketing Operations Partners and Customer Experience One.