What is the secret to customer loyalty? The answer straight from ~50,000 “horses’ mouths” (consumers, that is), per a massive survey conducted by Corporate Executive Board, was: Make it easy to get service. In other words, reduce their effort.
In order to find the recipe for the ever-elusive ease, Forrester Consulting asked 5,000 consumers (on our behalf) about their biggest pain points in getting customer service. Again from the horses’ mouths, the answers (by far) were lack of contact center agent knowledge and inconsistency of answers across touchpoints, followed by the inability of websites to deliver answers. With a common “knowledge” theme running across the pain points, the panacea is clearly an intelligent and unified omnichannel knowledge management (KM) system.
Done with the right technology, process, people, and best practices, Knowledge Management reduces customer effort, which, in consumers’ own words, creates loyalty!
Beyond this strategic differentiator, KM also enables breakthrough enhancements to operational metrics which not only transforms the contact center but also transcends it in many ways.
Here are sample metrics and corresponding real-world examples from our Global 2000 clientele. One caveat: Remember “different strokes for different businesses.” The metric that makes sense for one brand might not make sense for another. Force-fitting Walmart-style metrics to a Nordstrom brand intent is not a good idea!
- First-Contact Resolution (FCR)
- Average Handle Time (AHT)
- Average Speed to Answer (ASA)
- Annual Training Hours (ATH)
- Call / Email / Chat deflection
- Product Returns and Exchanges
- Dispatch Avoidance Rate
One of the key customer-focused contact center metrics, First-Contact Resolution can significantly reduce consumer effort. While FAQs, search, and topic-tree browsing can help with simple queries, more sophisticated technologies like Artificial Intelligence (AI) are essential to resolving issues of medium to high complexity at first contact.
- Knowledge in action A premier telco client was able to improve FCR by 37% across thousands of contact center advisors when they made it mandatory for all agents to use guided help, a capability enabled by Case-Based Reasoning (CBR), an AI technology. In fact, any agent there is now able to handle any call, the “holy grail” in contact center customer service!
While it is a good metric for the customer as well, AHT is more of an internal metric for customer service operations. It is important to bear in mind that AHT without FCR can only increase customer effort and defection. Happily, KM, when done right, can transform both of these seemingly conflicting metrics.
- Knowledge in action As an example, a premier banking client reduced AHT by 67% while improving FCR by 36%, leveraging AI to guide customers to answers! In fact, advisors in its contact center used the same technology to guide customers through processes such as account opening and other banking transactions while complying with industry regulations!
ASA might better be called ASORA, the Average Speed to One Right Answer! Without the “right,” ASA might mean speed to the wrong answer, increased customer effort, and you know how that goes. With the proliferation of customer touchpoints, it is important to have a centralized omnichannel knowledge management system that is in consistent use to make sure that the customer gets the single right answer regardless of channels or even people within a single channel.
- Knowledge in action The telco client mentioned earlier leverages the same AI technology and omnichannel knowledge base across its contact centers and hundreds of retail stores to deliver single right answers fast, regardless of touchpoint!
Agent roles continue to become more complex. They are in perpetual training mode even as attrition remains in an unpleasant 35-40% range. It’s no wonder that consumers point to knowledge-related issues as the main sticking point in getting good customer service. How do you reduce training needs without compromising service quality? Again, KM delivers the answer.
- Knowledge in action With CBR/AI technology, a leading global bank was able to reach the #1 spot in customer service NPS and reduce ATH by 50%, even as it expanded to 11 countries with mostly novice agents in its workforce! With the same technology, a telco reduced induction training time by 43% and time-to-competency by half. Note that reducing the need for training also reduces shrinkage, which is the amount of time lost due to agents’ breaks at work, sick time, training, holidays, etc., another commonly used contact center metric.
Customers increasingly prefer self-service, and contact centers benefit from it as they look to cost-effectively meet increasing demand for service. However, robust KM is critical to delivering digital self-service. One of the popular metrics for measuring digital self-service effectiveness is the number of calls/emails/chat requests successfully deflected.
- Knowledge in action Contextual and intelligent self-service enabled a retailer to deflect up to 60% of email requests, while a media and legal services giant deflected 70% of requests for agent-assisted email and chat customer service!
In today’s hypercompetitive marketplace, many branded manufacturing firms, retailers, telcos, and others, accept product returns or exchanges, and eat the costs in processing them. Called by various names depending on the industry—No Fault Found (NFF), No Trouble Found (NTF)—many of these returns and exchanges are unwarranted where the products were not faulty but the customer thought so (and the contact center could not resolve the problem.) NFF costs many organizations tens millions of dollars each year, but here’s the good news: KM can address this issue head on.
- Knowledge in action A large telco has reduced unwarranted handset exchanges by 38% using AI-powered problem resolution for the consumer at its contact center, while improving FCR by 19% and call quality by 23%!
Unresolved problems that could have been avoided with smart problem resolution through the contact center result in unnecessary truck rolls or engineer callouts. Depending on the industry, each such visit can cost from a couple of hundred to a few thousand dollars, biting into the business’ operating margin.
- Knowledge in action With omnichannel AI deployed in the contact center and on the website, a leading white goods manufacturer was able to save tens of millions dollars every year by reducing such wasted truck rolls. A water utilities firm was able to save ~$5M per year by reducing unnecessary engineer callouts, and even improved FCR by 30%!
These metrics are only the tip of the iceberg. There are other areas transformed by KM, including agent churn reduction, regulatory compliance, reduction of website abandonment, customer journey progression, and softer metrics like agent morale and customer satisfaction.
I don’t mean to channel Francis Bacon here, but it’s true that some technologies improve customer service on the margins, some enable incremental improvement, and only a handful actually transform it. Knowledge management (KM), AI included, is a technology that clearly falls into the last category!
So, read, bookmark, download this article where we show you sample metrics and corresponding real-world examples from our Global 2000 clientele about the value of knowledge management in customer service.