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Complex requests, multiple touchpoints and resolutions that can take days (or even weeks). These are just a few of the challenges B2B technical support teams face every day. To make matters worse, many technology companies are stuck in a break-fix mentality that fails to address the underlying problems that hinder the system as a whole. Solving the challenges inherent in B2B tech requires a new approach—and the right technology to make it happen. In our whitepaper, “A Strategic Approach to Intelligent Automation in B2B Technology Support“, we detail what exactly tech companies need to do to optimize their user support operations for faster, fuller and more cost-effective resolutions. Here’s a brief glimpse at what’s inside:
Break Free from Break-Fix
Tech companies are great tactical troubleshooters. However, many struggle when it comes to broader support strategy. Often, problems are addressed on a case-by-case basis that largely exists in a vacuum—with little to no input from previous cases or supporting data. In other words, when something breaks, the goal is to fix it and move on. However, this largely reactive approach can cost companies a significant amount of time, effort and—most importantly—money. To break free from the “break-fix” mindset, companies must take a proactive approach to problem-solving, leveraging data from past experiences to inform and guide tech support agents on the best course of action when similar problems appear. Read more
“The goal is to move from reactive technical support operations to proactive ones that reduce friction and provide AI assistance to speed resolution and reduce cost per case.”
Applying AI Automation to Complex Cases
Humans can come up with great solutions to technical challenges—but they require considerable time and effort. They’re also prone to making errors and inaccuracies. (Humans are only human, after all.) By applying conversational AI and automation to support operations, tech companies can create a common system of intelligence that “learns” from each interaction and connects teams with the data they need to consistently deliver faster, more accurate resolutions.
Prioritizing Customer Cases by Complexity
Customers cases often fall into one of four tiers of complexity.
Intelligent Automation Use Cases
From intelligent self-service to intent recognition to after-call promise management—there are many use cases for AI automation in B2B technical support. In our whitepaper, we outline some of the most common use cases, including the most effective applications for streamlining customer journeys before, during and after critical interactions. Want to learn more about B2B tech support use cases and how to identify which will have the biggest impact on your company? Read our blog, “How to Optimize B2B Tech Support with AI & Automation,” and check out the accompanying webinar below:
AI and Support Team Retention
The best technical support agents are worth their weight in gold. Because B2B customer care is so complex, finding, training and retaining top talent represents a significant investment for companies. (Conversely, losing a valuable agent can cost up to tens of thousands of dollars.) In our whitepaper, we explain how AI and automation solutions, like U-Assist, can empower agents during live tech support interactions with the tools and guidance they need to consistently succeed. As a result, these solutions have shown to improve agent satisfaction and team retention rates.
Want to Learn More?
Read “A Strategic Approach to Intelligent Automation in B2B Technology Support”