5 Metrics to Score Your Customer Service
Ensure Customer Service Success

5 Metrics to Score Your Customer Service

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These 5 metrics are crucial to the success of your business and illustrate how well your customer service group is performing.

1. Queue Wait Time

Queue Wait Time (“QWT”) is the time a customer waits on hold to speak with a live agent. This is the most important metric driving the success of your customer service system. In the current fast-paced, technology-driven world, customers have less patience to wait for service. There is a big movement in the broader commerce market called “self-service”, where customers dictate the pace of their service. This can be seen in the use of IPads® for ordering at restaurants, beer vending machines, self-checkout at grocery stores, etc.

RevGuard analytics show the longer a customer waits to perform a task associated with their account, the less responsive they are to revenue and refund reducing techniques. A customer has a set amount of time they want to spend with your business representative, and instead of them spending that time hearing down-sell and refund mitigation techniques, they are waiting on hold. Being on hold is an inefficient use of the customer’s valuable time, as well as a lost opportunity for your business.

Customer Service Metrics Queue Wait TimeQWT standards vary by industry. However, most industries must aim for QWT of less than 90 seconds. After 90 seconds, your customer loses interest in dealing with your representatives. RevGuard’s OCO™ Product Suite targets this issue by providing customers automated outlets to handle their account at their own pace. By focusing on the underlying trend of movement to a “self-service” economy, RevGuard helps businesses design customer service solutions desired by their customer base. By utilizing automated technologies that have been optimized through A/B testing, businesses are able to free up their live agents to handle more escalated issues. This leads to lower QWT and increased profit from their customers.

2. Call Abandon Rate

Customer Service Call Abandon RateCustomer service success is also determined by the Call Abandon Rate (“Abandon Rate”). As discussed previously, the best practice for most industries is to have a QWT of less than 90 seconds. After that amount of time, customers’ attitudes towards dealing with the business become negative, and the likelihood of a customer not waiting long enough to speak with an agent increases. When a customer fails to speak with a live agent after some period of QWT, their call is said to be “abandoned.” Call abandons are absolutely terrible for a business. An abandoned call is a non-serviced customer, as well as a non-serviced business opportunity.

There is a distinct relationship between call abandons and negative social media. How often have you read online about a customer who tried to call a business and no one would answer? This type of negative social media substantially impacts a business due to the direct effect it has on potential customer opportunities, not to mention the negativity present when dealing with that specific customer. Abandoned customers use banks to chargeback subscriptions, discontinue new sale opportunities, and voice dissent about the business online.

Abandon rate guidelines are relatively the same across industries. All businesses should make sure no more than 7% of their callers are abandoning. After the 7% threshold, businesses begin to suffer financially and see an online deterioration of their reputation. If you are suffering from high abandon rates, you have two options: 1) Add more live agents or 2) Open up automated customer service handling methods.

Live agents are costly and are not always the preferred contact method demanded by customers (i.e. “self-servicing” trend). RevGuard designed its OCO™ Product Suite to help businesses A/B test customer servicing methods and automate them. This process leads to lower call volume, which leads to lower abandon rates. RevGuard has found that studying customer analytics to effectively automate customer handling options leads to greater profitability.

3. Call Handle Times

Customer Service Metrics Call Handle TimesCall Handle Time (“CHT”) is the average amount of time a live agent spends with a customer on a customer service call. As you can see, multiple customer service metrics are conditional on one another. For example, if you have a team of live agents with very high CHT, you will begin to have a greater QWT, which leads to a higher Abandon Rate. Monitoring the length of time agents correspond with customers is important to make sure QWT and Abandon Rate do not spike and that customers are having their accounts handled in an effective manner.

Call center managers tend to believe high CHT mean “extra attention” is being given to customers, but in actuality, a high CHT is representative of poorly designed customer service handling options. The higher the CHT, the longer a customer must listen to a customer service representative offer options they are not interested in. By being offered consecutive, unattractive options, customers inevitably tune out an agent, waiting for the agent to pause so that the customer can reiterate the intention they had when they initially called. The goal of the customer service department is to find ways to anticipate that initial intention and offer handling options designed to get the call resolved as effectively as possible.

How can a business anticipate the intention of a caller? RevGuard’s approach is designed around the methodology of customer segmentation, as well as testing options within each customer segment to study customer responses. Organizations should aim to locate similar customer attributes and group those customers into large segments. For example, a company may find when testing the group of customers who have multiple purchases against the group of those with a single purchase, the multiple purchases group are more susceptible to higher revenue opportunities. Customers with a high propensity to purchase multiple items may be more inclined to take a smaller discount than those who purchased once. RevGuard’s OCO™ Product Suite answers these questions on how to segment and produce optimal customer service options through A/B testing.

Any good customer handling program should resolve customers’ needs in approximately 5 minutes. Anything longer, and the customer begins to tune out what will inevitably come across as a never-ending sales pitch. Businesses need to be cognizant that extended CHT will not lead to improved customer profitability and satisfaction.

4. Expected Revenue Per Call

Expected Revenue Per CallExpected Revenue per Call (“ERPC”) is the measurement of expected revenue generated, on average, for any given customer service call. It is calculated as the product of two metrics: the weighted average of revenue items available and the conversion rate of that average. This metric reveals the ability of the customer service team to successfully present offers, as well as the responsiveness of the customer base to the offers being presented. As higher CHT can lead to higher QWT and Abandon Rates, it can also lead to lower ERPC.

Increasing ERPC is the Key Performance Indicator used to gauge the success of the customer service management team and the individual customer service agents. ERPC evaluates how well the customer service management team provides individual agents with options customers are likely to convert with. The worst thing a business can do when targeting ERPC is to offer customer service options in an unmethodical way.

RevGuard’s systematic approach relies on A/B testing to determine high-converting customer service offers. By testing multiple offers, customer service management teams can confidently conclude which options specific customer segments respond well to. This pattern of continually testing new customer segments and offers, studying the resulting data analytics, and refining offers based on the data is known as Customer Service Optimization. RevGuard simplifies this optimization process with their OCO™ Product Suite and Analytic toolset.

Unlike other metrics, ERPC is contingent on the industry and the product offering. There is no average price or conversion rate. It is recommended to track ERPC through an application like RevGuard since RevGuard details the conversion rate and the average revenue price. Focusing on the tradeoff between conversion rate and average revenue will help you learn how to receive higher ERPCs.

5. Expected Refunds Per Call

Expected Refunds Per Call
Expected Refunds per Call is similar to ERPC, where each call can have an expected refund impact associated with it. The implementation of ERPC is identical to this metric, with the only difference being the study of refunds instead of revenue. The calculation is the product of two metrics: the weighted average of refund items available and the conversion rate of that average. Just as higher CHT can lead to higher QWT and Abandon rates, they can lead to lower ERPC and higher Expected Refunds.

By building customer segments, businesses can test a variety of customer satisfaction techniques related to negative revenue items such as refunds. Instead of trying to maximize ERPC, the business attempts to minimize the expectation of a refund. Here, the term conversion rate equates to the probability of a customer getting a refund. By building Key Performance Indicators around these rates, business owners are able to see if their team is giving out too many refunds and / or too high of a refund amount.

Just like ERPC, expected refund impact is completely contingent on the industry and product offering. However, you can follow the same logic to track it and optimize it. Focusing on the tradeoff between conversion and average refunds helps you learn how to minimize expected refunds.

You should now be armed with the right questions to be asking of your customer service management team. And remember, RevGuard’s focus on developing products and services for Customer Service Optimization can help you maximize the profits out of your customer service operation.

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