How Can Machine Learning Improve My CX Design?

According to The Northridge Group, 73% of customers will consider switching companies after a single negative experience. In addition, digital channels as a customer service option (compared to phone and email) have grown in popularity by nearly 60%.  

That’s why Gartner estimates that as of this year (2022), 70% of customer interactions will involve technologies such as machine learning. 

Organizations who have adopted these technologies – including state governments, retail leaders, and shipping services – have seen benefits including the following:

• 140,000 daily inquiries handled by VAs, with 99.9% of client claims addressed in a timely manner
• Reduced calls to in-store employees by 50%, freeing up over 100 employees to focus on high-value tasks
• 32% of queries now handled by VAs, with 70% of queries now handled immediately

The Future of Self-Service: AI-Modeled Interactions

Let’s imagine a future state for a moment. What if contact center artificial intelligence and machine learning could:

• Analyze real conversations with your actual customers, and accurately identify the most common topics?
• Identify the best areas for self-service and automation?
• Intelligently design the best ways to solve pain and enhance self-service?

Turns out, it can.

What is AI-Modeled Interaction Design?

It’s AI-guided customer service operations informed by large-scale AI insights on what your actual customers are telling you they need and want.

The process starts with your own customers, and real conversations you’ve had with them.  We’re able to securely process anywhere from a minimum of 10,000 recordings, all the way up to a maximum of 100,000 (more details below). Those interactions are collectively a gold mine of data points and insights, but extracting from such a large dataset would be a massive challenge for any human team.

That’s why UJET makes it painless, and saves you countless staff hours required to analyze and automate at scale. We leverage conversational AI and machine learning to build your contact center’s optimization roadmap. You’ll get a prioritized list of Virtual Agents (VAs) to deploy, along with a high-level cost/benefit analysis for each.

How Does AI Identify My Customer Pain Points?

Customer pain point data is derived from up to 100,000 actual customer interactions with your company. We use Google’s Contact Center Artificial Intelligence (CCAI) to run a conversational analysis on the interaction to quickly and accurately derive insights at scale – on commonly discussed topics, issues, frequent customer requests, and more.  

• Analyze tens of thousands of your customer service interactions to identify your customers’ most frequently asked questions
• Find and annotate the most common and important topics
• Identify the best types of interactions for self-service and automation 
• Flag the most common friction and pain points, and design ways to resolve them via VAs

The data is only used to inform interaction and workflow optimization, and is removed when this analysis is completed.

In addition, the data will likely have dozens if not hundreds of additional actionable insights, such as:

• Recurring points of friction or frustration, such as issues with payment methods, passwords, website errors, etc.
• Rising trends in complaints or returns for one particular product or feature.  
• Repeated requests for new product lines, or enhancements to existing products/services.  

Here’s an example of how AI-modeled interaction design might work for a retail business:

Imagine you ran an online clothing retailer, and you wanted to optimize and streamline how you handle frequent customer requests.

After performing the analysis on your recordings, UJET found that two very common customer queries were:

1. Initiating returns
2. Understanding garment sizing 

Next, we would work with you to design VAs to handle these use cases.  For the first query, we could design a virtual agent to help with the exchange process and creating shipping info. For the second, the customer could receive fitting guidelines, size conversions, tips for measuring, and so on.  

No matter your industry, you’ll receive a prioritized list of VAs for you to deploy, along with a high-level cost/benefit analysis for each. Remember, depending on your circumstances and commitments, you could qualify for a rebate of up to 100% of the discovery costs.