Just adding a chatbot on your website or mobile app will not reduce customer service calls.
Sometimes as an analyst I must tell a customer service team that it is not surprising that their well-designed chatbot is not reducing customer service calls. In fact, it’s doubtful that they will ever see the return on the investment they promised their managers.
Here’s the wacky part: In fact, that bot may be more valuable to the brand than the cost savings that increased customer service automation might have provided. But the remaining problem is that, in their business case, they committed to the wrong success metric.
What do you mean, “the wrong success metric”? Aren’t bots supposed to reduce my costs?
While there is some overlap, people who want to chat are often not the same people who call customer service. Think about a prospect on your website. If they can’t find an answer to their question, they might be willing to try a chatbot, but they are not likely to dig around to find your 800-number. That prospect may simply go to your competitor’s website, and you just lost a sale or a deal that you didn’t even know was in play.
But if that chatbot deftly engages a prospect who ends up buying, that chatbot shows immense value to the brand. That chatbot will not absorb customer service calls, however.
There is value in shifting your channel mix.
For those who have already deployed chat and are looking to maximize adoption, introduce strategies that encourage your callers to become chatters. This can be as simple as your IVR proactively offering a link to chat to anyone waiting on hold for a voice agent. If you do this, make sure that your digital support is as high-quality as what you offer by phone. If you send them to digital and your analytics tell you that they call you back within minutes, you’ll know that you have just executed an epic customer-experience fail. Nailing chat is tricky, but successfully converting loyal callers to digital, you’ve broadened the pool of interactions that can be contained by your new (well-designed) chatbot.
What if I’m still creating the business case for our chatbot?
If you are reading this before you promised your leadership that your chatbot will reduce customer service calls, huzzah!
To build the right business case, you need to do some analysis on your web or mobile application users via tools such as journey mapping, voice of the customer, confidence-building measures, and customer analytics:
- Where (and why) do they get hung up? What are their “pain points”?
- What can’t they find on your website or in your mobile app?
- Where is the information that the customer needs to move forward?
- What questions aren’t you answering throughout the customer journey in your digital touchpoints?
With these insights, you can identify what your potential chatbot will do — e.g., generate more sales, assist with payment, or whatever it may be. It’s possible that your customer support site has problems and that people are calling customer service after failing there, but you need to validate that assumption, not build a business case on it.
Analyze whether a voicebot may be a better option.
If your domain is customer service and you want to reduce contact center costs, explore an advanced voicebot that automates more calls. A modern voicebot will also reduce agent call durations by ensuring that all calls will be escalated to the best available agent with all the pertinent customer information required to solve the customer’s problem quickly.
Many brands look to deploy chatbots first, thinking that they are simpler to deploy and a better experience for customers, but if your goal is to reduce customer service calls, put your bot on the phone. Every call that the bot handles is a call that did not need an agent.
If you do go down the voicebot path, think about omnichannel for the long run, meaning you should find a vendor that can provide digital as well as voice services. This way, when you deploy your chatbot, you will provide consistent customer experiences and leverage your workflow and integration work across all interactions, saving development time.
This post was written by Principal Analyst Max Ball and it originally appeared here.
