05th Oct, 2020

Use AI for Customer Service to Improve Key Service Metrics

This article highlights how leaders are using AI for customer service to more effectively communicate with customers and impact key service metrics while bolstering exceptional digital customer experiences. 

Customer service teams have seen a spike in digital self-service adoption as a result of the coronavirus pandemic. More than 20% of US retail bank customers tried their bank’s digital platforms for the first time during lockdown, according to the Boston Consulting Group. European consumers likewise advanced their digital adoption rates by two to three years in just a few months, according to McKinsey.

Customers aren’t necessarily substituting digital channels for agent-centric ones, however. Instead, customers are making more calls and adding digital options on top of person-to-person interactions, which are in higher demand during crisis times, according to analysis by Accenture.

Artificial Intelligence (AI) channels for customer service have never been so critical.”

-Dawn Anderson et al., Accenture

Higher volumes across the board means more pressure on customer service departments to maintain both high service levels and strong digital gains, not to mention pressure to preserve cost structures that are anchored around the efficiency of digital channels. Using AI for customer service can help service leaders improve critical digital communications related to customer service that make it easy and intuitive for customers to solve issues themselves so service agents can focus on complex issues that require human involvement. Persado found that companies that use AI to improve customer service communications and experiences can increase self-service adoption and effective IVR flows by up to 40%.

Persado found that companies that use AI to improve customer service communications and experiences can increase self-service adoption and effective IVR flows by up to 40%.

To understand how using machine learning and AI for customer service can empower service leaders to sustain digital gains and get ahead of the service wave, we highlight four customer service strategies and the role that language AI can play with each.

How AI for customer service drives high satisfaction rates

Companies in all industries benefit when their customers receive better, faster, more relevant service. Retailers see more completed purchases; telcos see less churn from customers frustrated by long waits and poor service levels; and banks and insurers improve retention and manage service costs.

Persado’s AI platform improves customer service communications by analyzing clients’ content to identify the key words, phrases and concepts, and then conducts machine learning experiments to discover the combination of language elements that most effectively steers customers to solve their problems.

In one example, a U.S. health insurer saved $1.5 million in customer service costs from a single outbound email campaign by working with Persado to fine-tune the language. Clear, effective language encouraged customers to set up automatic prescription refills and eliminated the need to call in when they ran out of medication. Better language led to better service for the customer and lower service costs for the insurer.

Applying AI technologies to customer service can improve outcomes to all of the four customer service call management strategies highlighted below.

Strategy One: Prevent calls from happening in the first place

In the servicing world, the best service call is the one that never happens — the customer either sets up automated systems or already knows where to find needed information and can act on it. The U.S. health insurer described above leveraged Persado’s language AI to steer that customer service issue permanently away from human agents and toward automated digital channels, saving more than a million dollars in service costs.

Strategy Two: Deflect calls to digital self-service channels

When customers call the service department with a one-time issue that can be addressed through self-service channels, the ideal outcome is for the IVR script to guide customers to a resolution without engaging human agents. A tier two solution might alternatively direct customers to a section of the website or the app that answers their questions.

A European telecommunications provider worked with Persado to improve the IVR script heard by customers who called in to pay an overdue bill. The Persado-generated script increased the percentage of customers who accepted the suggestion to pay with self-service and ultimately drove 24% more customers to complete their payments entirely using self-service channels.

Strategy Three: Address the issue efficiently through human-digital collaboration

Straightforward issues that still require limited human intervention fall into this tier. With the help of well-designed IVR prompts or chatbots that accurately identify a customer’s issue and then route them to the right department or agent, customer service teams can achieve high resolution rates inexpensively and prevent repeat calls related to the same problem due to costly misrouted calls.

The European telco provided this option for the overdue payers who weren’t willing to finish the process entirely through self-service channels. An additional 13% of customers made their payments with the help of a human agent.

Strategy Four: Focus human resources where they’re most needed

There will always be calls that require a human being to resolve them, one-to-one. These calls might be too individual to address through automated means; they might be too complex; or the customer may simply want to speak to a person. Effective language helps customers provide information and follow prompts that place them with the right agent the first time, increasing first call resolution rates, preventing repeat calls, and in the process, lowering costs and customer effort which has been shown to positively impact loyalty and retention.

Achieving the benefits of AI for customer service

Proactive organizations can start now to analyze their customer service data and identify customer service calls that could be prevented altogether or handled through self-service channels. One Fortune 50 US bank took such a step after analysis of its service data revealed that “chronic callers” who’d contacted the call center twice in the previous months didn’t have automatic alerts set up. A proactive email campaign to encourage callers to sign up for alerts produced 146% higher engagement than the bank’s control message.

Across industries and customer service strategies, AI for customer service can improve key service metrics such as call volume and first call resolution while reducing costs and boosting the customer digital experience.


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