Contact center and digital customer experience leaders are often tasked with doing the impossible—Improve service productivity and the customer experience while reducing costs. It sounds like a tough task, but when done with proven technology and a solutions partner with domain expertise, they can do just that with artificial intelligence and win acclaim for achieving the impossible!
How Modern AI helps reduce costs
Call avoidance or Call deflection
It is no secret that 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 (by up to three times through 2020, according to McKinsey), call volumes are stable or declining only a bit, depending on whose stats you believe, adding significantly to service costs. The good news is that AI-guided self-service can help in a big way.
Call deflection falls into two groups:
- Deflection from the interactive voice response (IVR) system: We have all experienced it, and Accenture affirmed it—84 percent of consumers find it “extremely frustrating” or “frustrating” to be put on hold for a long time. But consumers need to fret no more, thanks to AI-infused knowledge. Customers on hold in an IVR-fronted queue can now get an SMS link 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 queue. It’s rich self-service with a safety net! Who wouldn’t want it but for rabid fans of IVR music?
- Deflection prior to the call: This is even better for the customer and the business. AI reasoning with or without a natural language or virtual assistant front end can take digital self-service to the next level, handling 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 report being able to deflect up to 60 percent of such requests.
Repeat call and transfer avoidance
Repeat calls and transfers are proven detractors to the customer and agent experience. When customers are forced to make repeat calls because of unresolved issues, or get bounced from one agent to another where they must not only endure call re-initiation or transfer and additional wait times, but have to repeat context for the next agent, they get frustrated even more. Perhaps this is what has led to the phenomenon of tech support rage, described eloquently by The New York Times. This is not good for the business or agents. Again, a robust AI knowledge system can help agents handle a broader and deeper set of customer queries, reducing repeat calls and transfers.
A leading mobile operator and eGain client achieved a 37 percent 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 500 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.
Contact centers typically spend $4,000 to $8,000 for initial training and onboarding and thousands more in ongoing training for agents. However, the retention rate is only 21 percent, and digitally-savvy next-gen agents would rather look up answers than absorb and retain training material. Contextual knowledge or AI-enabled process guidance served at the time of interacting with the customer—proactively or on demand by the agent—can help reduce the need for agent training and speed up time to competency.
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 percent when its advisors used AI-enabled search to serve customers of multiple financial institutions.
With a churn rate of 35 to 40 percent (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 novice reps who have to drink knowledge from the proverbial fire hose while keeping up with frequent changes in information, policy, and procedures. The solution to this problem is not the draconian Tayloristic methods used on agents by many contact centers. Rather, it is empowering them with knowledge and AI.
The aforementioned global bank was able to expand to 11 countries while reducing agent churn to a minuscule percentage by leveraging AI knowledge.
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, 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. Here’s the good news: AI knowledge can be leveraged to remotely troubleshoot and guide the customer to a resolution, reducing unwarranted returns in the process.
A leading telecom client could reduce handset exchanges and returns by 38 percent through effective problem resolution in its contact center.
Field service avoidance
Dispatching service technicians to field locations to fix problems is expensive. Called truck rolls, these visits cost $150 on average and are often initiated after the contact center failed to solve customer problems. Again, smart knowledge can help.
A white goods manufacturing client saved $50 million per year by reducing unnecessary truck rolls through effective problem resolution with AI knowledge.