I was talking to a VP of Service the other day and he had his call center manager on the line. When I asked the manager to name his biggest challenge, his answer was, “My agents don’t know when to quit…” What he meant was that they didn’t know when to stop trying to diagnose the problem by themselves and escalate to a higher tiered agent or an FSE. The VP said another challenge is that when an escalation does occur, his experts get pulled into too many issues that are “below their pay grade”, thus wasting their time.
Below is a table showing how issues are being resolved today in a typical service/support organization (this is based on actual conversations with OEM’s). Each block represents the number of service issues per year. As you can see, customers typically don’t do much troubleshooting and rely almost completely on the support organization. The call center, in particular, is tasked with resolving the lion’s share of the issues. FSE’s also get pulled into issues that end up getting resolved relatively quickly.
What if you could shift support events earlier in the support chain, enabling more customer self-service? By enabling call center agents to resolve more complex issues (“A”) and enable the customer to solve the simpler issues (“B”), you can shorten resolution time and improve customer satisfaction. Other issues are moved earlier in the support chain accordingly.
Saying it is one thing. Doing it is another. Here’s one way:
Give your customers AI-driven tools that help them gather necessary diagnostic information. When they encounter an issue, the tool asks for information about the symptoms and then gives them guidance on the most efficient way to diagnose the problem and suggests a resolution.
If your customers still can’t fix it, they can hand the problem off to the call center with a history of what they’ve done so the support agent can hit the ground running.
Those same tools can be used by tier 1 agents in the call center to ask the right questions and make the best suggestions. Knowing what to ask, and then having a system that uses those answers to make suggestions, can make even the newest support agent sound like an experienced pro.
By studying what kind of problems customers and agents are solving, and the ones where they get stuck, you build valuable knowledge about how your customers work, and how your product could be made to work better.
The holy grail is to help your customers solve more of their own issues without needing to contact support. Or enabling your support agents to resolve problems without getting engineering involved. This frees up your service experts to deal with the rare issues that are really hard.