As many organizations begin to increase their spending on CX and AI, customer service leaders must invest in improvements for customer service.
The trouble is that CX leaders may not align their technology strategies with customers’ expectations, according to Metrigy’s “Customer Experience Optimization 2024-25 — Consumer Views” research study of 502 U.S. consumers. These customer service gaps were a major topic at this year’s Enterprise Connect conference in Orlando, Fla.
Has customer service gotten worse?
Despite all the technological advances over the past several years, customer service ratings are not as high as they could be. When asked to rate the customer service they receive, only 14.7% of survey respondents said it’s excellent, compared to 40.6% who said it’s good and 36.3% who said it’s fair.
Meanwhile, business leaders see things differently: 35.3% thought their customers would say their service was excellent, and 60.7% thought they would say it was good. That’s a big disconnect in how customers experience service and how business leaders perceive that experience.
Businesses don’t have a lot of chances to make mistakes. After three bad experiences, on average, customers leave for good. In fact, over 40% of consumers said they would leave a brand after just one bad experience.
Just over one-third of consumers said they saw an improvement in customer service in the past year, while over two-thirds of businesses said their service improved. This continued disconnect demonstrates the potential risk organizations face when their perception doesn’t match reality.
Businesses don’t have a lot of chances to make mistakes.
How AI affects customer service
Although most consumers in the Metrigy study said technology positively affected their interactions with businesses, AI did not top that list of technologies. Most consumers view organizations that use AI less favorably than those that don’t. And yet, 70.2% of organizations said they use AI for CX initiatives and are growing those rollouts.
Only 11.6% of consumers prefer AI agents or bots, while most respondents said they actively avoid them or only use them in select circumstances. Respondents said they avoid bots because they get stuck in a loop, don’t understand the question, don’t have the answers or take too much time. However, respondents said properly designed AI agents can save them time — which was the top value for customers — and answer their questions.
Most consumers still prefer voice calls, which they said have the fastest resolution time. When consumers call a company, they expect to talk to a live agent. However, 41% of organizations are accelerating their use of voice AI agents.
While AI has its own challenges, it increases the number of channels through which businesses can reach customers.
5 customer service gaps
Businesses and consumers don’t align on customer service delivery for various reasons, including the following:
Businesses apply AI agents — i.e., chatbots or voice bots — to problems they are not trained to address.
Consumers get stuck in a loop and can’t escape an AI agent to speak to a live agent, so their problems aren’t resolved.
Underlying data that supports AI models is not curated or integrated, causing problems with data integrity and accuracy.
AI is frequently portrayed as evil in TV shows, movies and other media, and businesses don’t showcase success stories to counter the negative portrayal.
Contact center staff are not trained properly, have high turnover rates or need more people or support — all resulting in less-than-stellar CX.
How to close customer service gaps
Ironically, AI and analytics services can help companies close customer service gaps. Additionally, operational processes and strategic decision-making drive efforts to improve CX.
For example, typical customer ages can dictate the types of interaction channels a business uses. Customers who are 45 and older prefer voice, email and in-person interactions. Customers younger than 45 prefer digital channels, including video.
Some key technologies and best practices to have in place are the following:
Develop or expand a voice of the customer program. VoC programs evaluate customers’ feedback on their interactions with the business. Customer service teams can supplement that feedback with inferred sentiment — which uses AI, like sentiment analysis and national language processing — and outcome metrics to assign a customer satisfaction value to every interaction.
Use AI strategically. AI agents can be useful, if applied to the right problems and trained properly. In fact, CX leaders expect over one-third of their total pool of agents will be AI agents by the end of 2025.
Use AI for supervisory functions. For example, AI can regularly train agents based on quality management evaluations. This saves supervisors almost 12 hours per week, according to Metrigy, and they can use that time to instead reach out to at-risk customers and reduce churn.
Invest in proactive outreach programs. Proactive customer service with AI at the core can analyze whether the business uses the right channels with the right frequency to reach customers. If outreach gets annoying, customers opt out.
If customer service teams collect consumer feedback on technology and experiences — using both AI and manual methods, like surveys — they can close the gap and create experiences customers want and expect.
Robin Gareiss is CEO and principal analyst at Metrigy, which conducts research and advises enterprises and technology providers. She leads coverage into AI, customer experience and contact center operations.
