What Problems Are CX Leaders Hoping To Fix With AI?

By Machielle Thomas

So many problems can break your customer experience (CX)—a nasty tweet, a defective product, or a conversation with a disgruntled employee. 

But nothing impacts CX like customer service. Your agents are on the frontlines of your customer interactions, which is where AI is solving many CX problems today.

Companies have been experimenting widely with AI in CX in the hopes of supporting their agents so they can operate less resources, while still improving the quality of support. 

AI support is 24/7, can handle tickets autonomously, and companies that use it deflect double the requests. In fact, you’re 3.5x more likely to lower your costs if you use AI, while customer satisfaction increases by 5% on average.

AI is making these changes by disrupting some of customer service’s stickiest issues—delivering consistent information, resolving tickets quickly, routing tickets to the right place, ensuring agents are supported, and finding cracks in the system to close.

5 Problems CX Leaders Are Solving with AI 

The good news is a lot of CX leaders are already out there solving these problems with AI. They’ve forged the path for other leaders and are already seeing results.

Our latest CX Benchmark Report for 2024, based on a survey of 512 mid-market, U.S.-based companies, reveals key areas where AI is making a significant impact. 

They include knowledge article creation, ticket resolution, ticket prioritization and routing, agent assist and reporting.

1. Knowledge base article creation

Automated customer support can help customers self-service, but the AI powering them relies on the information you give it. If you have a ‘set it and forget’ approach to your knowledge base, or its information is outdated, AI won’t be able to help customers self-serve or support agents solve problems. 

Customers will be frustrated, support will be ineffective, and all communication channels between teams and customers will be a frustrating experience that could result in lost leads, customers, and revenue.

Forethought is an AI solution that automates the upkeep of your knowledge base, so that customers and AI agents have access to accurate and up-to-date information. 

Achievers, an employee voice and recognition solution, experienced a spike in support inquiries around a busy holiday season. Their queue was filled with basic, repetitive inquiries, like how to retrieve a lost password. 

They used Solve’s Gap Detection to identify data gaps and improve their knowledge base, using an automated widget to resolve repetitive tickets. 

Achievers now resolves 93% of tickets at first contact, significantly reducing the time agents take to resolve issues across the board. 

2. Ticket Resolution

Another hot problem is resolving tickets quickly. In fact, this is the most common use for AI in CX, as cited by 62% of the CX leaders we polled in our benchmark report.

AI can speed up resolution times by resolving tickets itself, and by supporting live agents. 

Beeline, a B2B software managing the global extended workforce, handles support inquiries from several people, including client users, suppliers, and candidates.

They focus on creating a good customer experience, but also speed to revenue, and therefore can’t sacrifice efficient and effective support workflows. 

Solve allows Beeline to provide customers answers to their support questions instantly. Ticket volume dropped by about 100 tickets per month, and call volume by 400.

With Solve, Beeling has decreased time to first response by 24.3%, time to resolution by 52.2%

3. Ticket Prioritization and Routing

Tickets that get routed manually can take forever to get sorted to the correct person for assistance.

Plus, misrouting to the wrong agent or department can lead to delays and incorrect handling of customer issues. Customers don’t want to open the same issue with a new agent over and over—that’s a one way ticket to making them angry.

It doesn’t have to be this way. CX AI tools like Forethought are great at routing and sorting tickets accurately and quickly, deflecting tickets from agents, and speeding up resolution times.

Thumbtack, a platform connecting homeowners with professionals, implemented Triage to test against their in-house built customer support routing system. 

Their Customer Support team members need to know how to best ‘triage’ the tickets, or decide which they should spend time on and which could be automated.

They found Forethought’s AI was more accurate, and faster, with 85% accuracy on routed tickets.

4. Agent Assist

Support agents often get stuck sifting through a ton of open tabs: product information tabs, pricing and payment tabs, troubleshooting tutorials tabs, and more. 

It’s worse when many of these tabs hold outdated or inconsistent information.

AI-powered tools provide real-time assistance to agents, offering the right articles and relevant information on-demand to best resolve customer issues. 

It can also suggest ways to improve efficiency and effectiveness in the support process whether by flagging gaps in information, or surfacing relevant info across various channels.

Etekcity, an e-commerce service for tech products, uses Assist to surface relevant knowledge articles, past cases, macros, and personal notes within their agents’ help desk. 

The personalized notes function within Assist lets Etekcity’s agents create, share, and quickly apply commonly used note templates. 

Basically, all agents get the same information across cases in real time. This centralization leads to a 69.7% reduction in time to first response and a 60% reduction in average time to resolution.

5. Reporting, analytics and insights

There is often too much data for teams to sift through manually to generate truly helpful insights without a professional analyst. 

AI can help here too by generating detailed reports and insights on massive amounts of data. This allows you to analyze performance metrics, identify trends, and make data-driven decisions to enhance customer experiences. 

This example from Forethought provides you with access insights for Solve, including an overview of metrics like CSAT and intent-level insights.

Users can also download data related to chat conversations and visualize it.

Key Goals and Expectations of AI in CX 

It’s not enough to implement AI and feel like customer service improves (obviously)—you want to measure your efforts. 

In our benchmark report, we talked with CX leaders to get a sense of the KPIs they were using internally and how they expected AI to move the needle. Our study reveals the strategies they’re using to achieve these goals.

Overall, leaders aim to lower costs and boost team efficiency to serve more customers. In fact, 81% of CX leaders want to improve CX. VP-level respondents ranked automating deflection most highly at 63%. 

AI Should Reduce Costs 

We have good news for the 68% of directors who said they wanted to reduce customer support costs—implementing AI in customer service can reduce costs by up to 30%

Turns out talk is not cheap after all. People are expensive, and leaders expect AI to reduce this cost dramatically. Currently, the average contact center conversation with a human costs $8, whereas the average customer service interaction via chatbot costs 10 cents

AI Should Proactively Improve Processes

Leaders also want AI to help them proactively identify areas where they can improve customer service. 

57% of customers thought customer service had worsened in the last year, and leaders want to know how to reverse the trends if it applies to them.

Uncommon Goods, an e-commerce retailer, onboards hundreds of new agents for the holiday season who don’t have much experience answering customer questions. 

They use Assist to surface relevant knowledge articles, macros, past tickets and notes directly within their agent’s helpdesk. New, seasonal agents have access and can better give their customers the right information, providing them a satisfying service experience.

Make Bad Chatbots Better

People hate chatbots today because they’re wonky and inconsistent. It’s also complex for CX teams to manually build chatbot workflows by trying to guess what their customers want. 

AToday’s AI-powered chatbots continuously learn based on your knowledge base and prior customer interactions, which thankfully eliminates the need for manually built decision trees.

iFIT, a global health and fitness subscription technology company, opted to implement Solve, removing the need for outdated decision trees. 

Customers ask the chatbot about product details, cost, and technical information. As a result, 33% of iFIT’s chats are deflected via the Solve widget. 

Improve Every Precious Interaction with Your Customers

AI is transforming customer support by solving some of the most frustrating issues in customer service.

Everything affects customer experience—from product to marketing to service—making it tough to consistently deliver a good experience. But AI helps make customer service, your first line of defense, faster and more accurate. 

Ready to improve your automated support? Request a demo from the Forethought team to see how you can solve some of your trickiest CX problems today.

Dive in.

Interested in generative AI for customer support? Check out this guide to learn about the 3 key pillars you need to get started.

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