Posted On: September 21, 2020 | 10 mins read
Back when the industrial age was first beginning to boom, businesses found themselves changing with it. Supply and demand were no longer the only Key Performance Indicators (KPIs) of market activity. With the boom came competition, and rival brands vying for customers meant a third KPI had entered the market: Customer Experience (CX). Business success used to be all about one mantra: Location! Today, customers will deal with businesses across the world – should they want to. And that largely depends on the customer service strategies and knowledge base capabilities of the brand in question.
As companies grew, they began to identify vital contact points across customer service business was won or lost not just basis the product, but basis interactions with sales agents in call centers, convenience and leisure factors like wait times, and an overall post-sales service feeling of contentment. In short, it became clear that measuring customer experience, and optimizing it, would come down to the identification and monitoring of KPIs across these factors, allowing companies to respond to data and maintain positive interactions.
Customer service strategies begin with identifying the problem, current or future, at any center of contact. How long did a customer have to wait? Was his problem solvable? How long did it take an agent to answer the phone, understand the problem, and solve it? Did any calls go unanswered?
Measuring metrics like these will give you a solid understanding of not just the types of problems your company faces when it comes to customer service, but also how you may respond to better that experience – and guarantee repeat customers.
But while great strategies begin with identifying certain KPI relating to call centers, self-service, and CX – they must then also explore optimizations and further CX KPIs to measure the effectiveness of deployed solutions.
The KPIs below are basic but essential examples of what a good customer service strategy will cater to:
Rule number 1 in service strategy in today’s world – don’t make them wait. Patience has long worn thin, and the modern customer hates being kept on hold – and will quickly drop the line in favor of a chattier competitor. Measuring this KPI will give you an idea of if your contact center is sufficiently staffed – and poor Average Response time is going to tank your CX scores.
Good knowledge management platforms provide you with a database summarising the above stats, as well as aggregate communication across channels – to help you optimize response times, and build a customer base loyal to your brand. Technology like automatic call distributors further streamline the process – and keeps data flowing in and out of your channels with ease.
How long do your agents take to resolve calls? This KPI measures the average time your agent invests into closing calls from start to finish, and give us valuable insights into the efficiency of the problem-solving process. Our takeaways go further, however, as long Average Handle Times (AHT) could be indicative of multiple problems – poor training or problem-solving skills, calls going to the wrong departments, or basic product information being unclear – leading to your call center being inundated by waves of calls from confused customers.
Again, a good knowledge management system will help you identify your exact problem through clear data, and thus allow you to fix it at its source, instead of shooting in the dark. For example, Learning management systems can help train employees globally to a certain standard, impart information on customer FAQs, and generally better prepare agents to solve problems – leading to happier customers, shorter handle times – and thus more customers ultimately served.
Call center KPIs further include vital metrics like abandonment rates and first contact resolution, and work similarly to above. Managing data from these KPIs will give companies a general idea of where the problem spots exist – and KM arms them with the data required to combat these problems, and leave your customers on top of the world.
Today’s world moves faster than ever though. Companies with optimized contact centers found that there was still space for improving average CX. While knowledge management software had helped optimize the art of the phone call – technology had long caught up, and sped past the dial tone. Instant communication is now the norm, and while call centers are considered a must-have a classical feature of the business world; customer service today has had to find ways to speed up the process even more. This is where self-service enters the picture.
Companies realized that new forms of communication meant problems could potentially be solved without needing to have an agent answer a phone. Advances in AI and virtual technology allowed bots and automated services like Interactive Voice Response (IVR) to take over the game – all with one goal in mind. Allow the customer to solve problems themselves, while still departing with a feeling of having fruitfully interacted with the company.
Allowing AI to interact with customers isn’t the same as abandoning them to a series of robotic calls and frustrating dead ends – it isn’t enough to simply automate your processes. Companies need to smartly identify the problems a customer may have, his probable solutions, and alternate channels should the initial solution fail. If any of these steps fail, you’re going to have angry customers and lost business. As ever, a good knowledge management system is generally key – allowing you to institute and measure KPIs across self-service that will help maintain a high level of customer service, and therefore satisfaction.
While the KPIs above help identify problems, a good customer service strategy wouldn’t end there.
Further metrics like the ones below help measure the success of your service strategy, optimizing results:
A self-service channel is considered a success if the customer can solve his problem without ever talking to a human agent. Well-designed FAQs are a prime example of a good self-service resource – and if customers are still calling support specialists with the same questions, chances are the FAQs are lacking, or don’t target the largest or most common customer issues. Knowledge management platforms enable companies to identify where Self-Service is failing, why that may be happening, and the best possible route to a solution.
Metrics like the Net Promoter Score (NPS), as well as more direct channels like feedback or reports, give companies an idea of overall customer satisfaction across channels – while isolating underperforming channels and areas of improvement. A company could have 10 different channels for self-service, from a website FAQ to AI customer service chatbots – but if they aren’t doing their job, and customers aren’t finding answers, then low customer satisfaction would deem this Self-Service inadequate.
Can a customer with a common problem be routed to the FAQs? Can a customer calling the wrong department to be automatically routed to the right one? Customer service strategies that offer solutions to problems like these will boost your call deflection rates, allowing customers to serve themselves better. Efficient knowledge management will ensure customers always have a path to their solution besides reducing fulfillment speed as they spend less time searching for the answers they want.
As mentioned above, metrics like the NPS help measure the efficiency of the channels you set up; and allow you to measure your Return on Investment (ROI) through these channels.
Measuring metrics like customer happiness is hard, and new channels of communication and customer service are likely to stutter at first – but KM will allow you to spot improvement over time through a constant flow of quantifiable data, such as measuring satisfaction in the form of repeat customers, and will keep your customer service strategy at the very top of its game.