Knowledge and AI: How Two Technologies Help Reduce the Cost of Customer Service
Technology 1
Artificial Intelligence (AI) has found an enduring place in the sun after seeing 2 AI winters. There are really useful AI applications in use in everyday life (we know the usual ones like facial recognition, Internet search, social media recommendations) and across industries. Customer service is one such lucky domain.
According to a McKinsey survey from December 2021, of the top 5 most common AI use cases adopted by businesses, 3 are for customer service.
Technology 2
Like AI, Knowledge Management (KM) too went through a nuclear winter. And similarly, KM is emerging as a critical capability, thanks to a recognizable need, improved technology, and proven implementation best practices. Gartner had recommended Knowledge Management as the #1 technology for customer service for 2022. Again, in 2022, Gartner has said that
Knowledge Management has the biggest impact on customer experience (CX), agent experience (AX), and operational performance out of all technologies in the contact center.
How they help
When CX leaders get impossible targets, i.e., improve service productivity and the customer experience while reducing costs, AI and Knowledge get together to help them achieve all three simultaneously.
Here are some ways Knowledge and AI help reduce the cost of customer service.
1. Avoiding or deflecting calls
Phone customer service is the most expensive form of service in the contact center. According to industry analysts, it costs 10 to 20 times as much as self-service. While digital interaction volumes are expected to increase year-on-year, call volumes haven’t declined significantly, if at all, adding significantly to service costs. The good news is that AI-guided self-service can help through call deflections.
Call deflection are of 2 types:
i) Deflection from the Interactive Voice Response (IVR) system: We have all experienced it, and Accenture affirmed it—84% of consumers find it “extremely frustrating” or “frustrating” to be put on hold for a long time. When they do get to an agent, an eGain State of IVR survey found, 73% customers say they have to repeat what they entered at the IVR to the human agent and 44% get different answers from the phone agent versus IVR and digital touchpoints.?What any reasonable human will feel at the end of this experience is what an NYT article called “tech support rage,"
…you fume. Your face turns red. You shout things into the phone that would appall your mother. (NYT article)
Thankfully, AI-infused knowledge can save the day and your sanity. Now, smartphone customers who are on hold in an IVR-fronted queue can get an SMS with links to answers or to an AI-enabled online interaction that will guide them to the answer or through the resolution process. Importantly, callers don’t lose their place in the IVR queue. It’s rich self-service with a safety net. No more IVR music!
ii) Deflection prior to the call: This is even better for the customer and the business. An AI virtual assistant (aka chatbot) front end can resolve common issues without the need to contact an agent. Conversational AI and guidance with knowledge can take digital self-service to the next level, as it takes the customer through questions of higher complexity than what simple search can. This can also help deflect requests for other forms of human-assisted service, such as chat and email. eGain’s clients (users of eGain Knowledge Hub) report being able to deflect up to 60% of such requests.
A leading manufacturer of windows and patio doors in the US successfully?deflects calls from the contact center because customers are getting the knowledge they need through self-service. From the support portal, these self-service customers are directed to the online retail store. The company's online parts store made sales worth $100K from 20,000 leads from the self-help website.
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2. Minimizing repeat and transfer of calls
When customers are forced to make repeat calls because of unresolved issues or get bounced from one agent to another where they have to repeat context for the next agent, they get frustrated even more. This is neither good for the business nor for customer and agent experience. A robust AI knowledge system ensures that customers get the right answer or resolution in the first contact (called First Call Resolution or First Contact Resolution in the industry) and that agents are able to handle a broader and deeper set of customer queries, reducing repeat calls and transfers.
This is how one telco used Knowledge and AI to transform customer and agent experience: A leading mobile operator and eGain client achieved a 37% improvement in first-contact resolution with AI-infused knowledge. The solution was used by more than 10,000 service associates across its contact center and more than 600 retail stores. The agent desktop was designed to focus on common customer problems and quick access to contextual knowledge and AI-enabled guided resolution rather than lots of customer data which might or might not be useful for resolving the problem at hand.
3. Reducing agent training
The same telco reduced the training time of its agents by 50% and improved time to competency by 50%. The AI-infused knowledge solution serves up contextual knowledge or AI-enabled process guidance at the time of interacting with the customer—proactively or on demand by the agent—which helps reduce the need for agent training and speeds up time to competency.
That can mean thousands of dollars saved. Contact centers typically spend $4,000 to $8,000 for initial training and onboarding and thousands more in ongoing training for agents. With retention rate at 21%, you can imagine the cost.
This is how a global bank used Knowledge and AI to reduce agent training and churn: A global banking client slashed training time in half while ensuring compliance across its agent pool in more than 11 countries with AI-enabled search and process guidance. A leading BPO client cut training time by 30% when its advisors used AI-enabled search to serve customers of multiple financial institutions.
4. Avoiding churn
With a churn rate of 35% to 40% (trending upwards since next-gen agents tend to stay less than older agents), US contact centers alone bleed upwards of $10 billion a year in agent attrition costs, a lose-lose-lose for the contact center, the business, and end customers.
Today’s agent pool consists of a significant number of the digital generations who would rather look up information than learn it. The solution is to empower them with knowledge and AI. Training the agents to use the system versus endless training provides a better working environment and make agents productive immediately.
The above global bank was able to expand to 11 countries while reducing agent churn to a minuscule percentage by leveraging AI knowledge.
5. Avoiding product returns
When products are returned by consumers for apparently being faulty, companies eat the costs of replacing the product or inspecting it again for defects, no questions asked. Called No Fault Found (NFF), this expensive phenomenon is often the result of contact center agents not being able to resolve customers’ problems when they call for assistance in setting up or using the product. AI Knowledge can be leveraged to remotely troubleshoot and guide the customer to a resolution, reducing unwarranted returns in the process.
Embedded AI knowledge preempts customer issues and reduces the cost of NFF returns: A leading telecom client could reduce handset exchanges and returns by 38% through effective problem resolution in its contact center. A hypergrowth SaaS provider has embedded eGain Knowledge and AI solution in its products to preempt customer service.
6. It doesn't end here
This is only the tip of the iceberg. Knowledge and AI are the magic technologies that can work together to improve two competing metrics, like reducing the average handle time for a call and improving first contact resolution rate.
eGain is an award-winning provider of Knowledge and AI solutions for customer engagement. Contact us if you want to talk about using knowledge and AI for your CX initiatives.
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