New KPI Metrics in the Era of Self Service
Once upon a time, measuring customer service success was straightforward. Hire some agents, train them, and use standard contact center KPIs to measure how well they perform.
Modern contact centers are made up of a complex combination of humans and virtual assistants – using both natural and artificial intelligence – operating over multiple channels and using a wide range of tools to solve customers’ issues.
With many of these channels and tools enabling self-service, old-school KPIs are no longer sufficient. When a virtual agent fields a customer’s enquiry, collects all relevant details and passes it to a human agent for final approval, how should average handling time (AHT) be measured?
When a customer searches through FAQs, follows a video tutorial, asks a question on a user forum and still does not have a satisfactory answer to their question, resulting in a call to customer service, is that resolution considered a first contact resolution (FCR)?
When more enquiries are handled by AI-assisted agents – for example with best-next-step recommendations – are traditionally measured agent performance metrics still accurate?
As self-service becomes more widely adopted in the customer service arena, gone are the days of two-minute performance-boosting calls asking to update an address.
Calls asking for basic operating instructions are also a thing of the past. And long gone are those password reset requests. These simple enquiries can now be handled via self-service channels, leaving agents to field the more complex calls that are currently beyond the capabilities of machines.
Complex calls take longer, of course. They sometimes require research or approval from a supervisor. No matter how capable the agent, or how efficient the process, these complex cases will obviously have a negative effect on AHT, and sometimes even on FCR, if a follow-up conversation is required.
Customer care center metrics in the era of self-service clearly require a different approach. New, more relevant self service KPI metrics that measure the success of self-service tools along with agent performance are now required.
New Self Service KPI Metrics
Call Deflection Rate
Call deflection occurs when a customer’s enquiry is routed to an alternative service channel. The goal of call deflection is both to ensure that customers receive the answers they are seeking in the most efficient manner, and to reduce the number of calls routed to human agents. Instead, enquiries may be deflected to FAQs, live chat, community forums, and knowledge center databases. While this metric refers to “calls,” it also encompasses any contact requiring agent attention, including chat sessions and emails.
Measuring the call reflection rate is complicated. One method, according to DB Kay & Associates, is to estimate both the percentage of users who are successful with self-service and the percentage of users who would have contacted a live agent. The product of those two percentages represents the deflection rate.
Measuring call deflection with absolute precision is almost impossible as the metric essentially measures what didn’t happen. It is more useful to monitor the metric over time, as deflection should increase as the self-service channels improve and customers become more comfortable with the technology.
Total Cost Per Contact
To measure the total cost per contact, enterprises must go beyond the cost of each call, and measure the cost of each channel – including email, live chat and virtual agents – as well the combined cost per contact. Enterprises must consider staffing costs, call center management systems expenses and the cost of self-service tools. Experts estimate that the current average total cost per contact across all industries is approximately $15.
In today’s omnichannel contact center, it is exceedingly difficult to measure each of these channels separately, as customers generally experience more than one channel during a support episode. A customer may use FAQs and live chat, search the knowledge bank while on hold for an agent or send an email after watching a video tutorial. The cost of the initial contact would be the cost of the two channels combined, and the total cost per contact would be the total cost of all available channels.
This metric provides enterprises with the actual cost of support when multiple channels are used to provide a customer resolution. It also indicates whether adding self-service options has decreased the overall cost of support.
Fulfillment speed represents the length of time it takes to conclude a self-service transaction from initial request to completion. The speed of fulfillment should be faster than the time it would take the customer to contact a human agent. If, after implementing a self-service channel, fulfillment times have increased or even stayed the same, the implementation cannot be considered successful.
For example, providing payment details via a chatbot will always be faster than having a customer call in to provide payment details to a live agent. Does the same hold true if a customer wants instructions on using an electronic device? If a customer wants to upgrade his level of service? For this self service KPI to be green, it should.
No matter how excited the business may be about implementing self-service channels, if customers are not satisfied by their usability or efficiency, then the self-service channel cannot be considered a success. Customer satisfaction must be tracked for each self-service channel – including surveys, direct feedback and Net Promoter Score (NPS) – to learn which channels are most successful as well as which ones need improvement. A temporary drop in satisfaction scores is to be expected when rolling out new channels or restricting access to familiar ones, but if done correctly, customers will appreciate the ability to use self-service to get the answers they need when they need them.
Self-Service Success Rate
The success of self-service can be determined by tracking how many customer enquiries are handled by self-service channels without being escalated to a human agent. The success rate can be linked to a number of metrics, such as the percentage of times a “how to order” FAQ leads to an order rather than a customer-initiated chat session, the percentage of times a video tutorial explaining how to activate a device eliminates a customer call to the contact center, or the percentage of times a knowledge bank search leads to a useful article. This is typically measured by asking the user to rate the article or mark it as “useful” or “this solved my problem.”
Boost KPIs with Visual Self-Service
When visual interaction – whether via image or video – is combined with self-service, the opportunity for a better CX increases exponentially.
Call Deflection Rate: asking a customer to visually identify their device is a much more efficient method than asking for customers to provide makes and model numbers. A coffee machine manufacturer may present images of six different models on their Contact Us page. Once the customer chooses their model, they may be presented with images of the machine’s different parts in order to troubleshoot the correct one. A video tutorial or additional images can be presented on-screen so the customer can best benefit from self-service.
Total Cost Per Contact: implementing self-service channels has been proven to reduce costs. According to Accenture, a typical utility provider could see $1-3 million in annual savings by adding self-service. They allow for a greater deflection rate, more effective self-service and faster resolutions without necessitating escalation to human agents.
Fulfillment Speed: humans are visual creatures. With 50% of our brain capacity used for visual processing, visual communication leads to instant, clear understanding. Adding a visual element to a self-service channel will likely speed up the time it takes to complete a self-service transaction. For example, if a chatbot can provide instructions via images to a customer seeking help with their TV remote control, it will be much easier for them to understand than if the chatbot had to explain them using text: “the third button on the right…”
Self-Service Success Rate: self-service tools often fail when customers request tasks that require vision such as “show me how to fix, how to install, how to operate.” Adding a visual element to each self-service channel makes it easier for the customer to find the resolution they are seeking, thereby eliminating the need for them to transfer to a higher level of service.
Customer Satisfaction: adding a visual element to self-service channels optimizes those channels and leads to greater customer satisfaction. Customer satisfaction increases due to faster resolutions, higher success rates and a feeling of personalization that promotes loyalty.
With over 50% of customers preferring to solve product issues themselves rather than relying on customer service, the age of self-service has arrived. And just as customer care approaches have changed to reflect current realities, the KPIs used to measure contact center success must change as well. New, more relevant self service KPI metrics that measure the success of self-service tools along with agent performance are more appropriate in today’s modern contact centers. Metrics such as call deflection rate, total cost per contact, fulfillment speed, customer satisfaction and self-service success rates are all good indicators of the success of self-service channels. Adding a visual element to each self-service channel further enhances its effectiveness and goes a long way towards improving the KPI performance of self-service.