Smart customer service chatbots are cool. But there’s a reason companies like Amazon are ditching them in favor of a new generation of rules-based chatbots. Learn more about these easy-to-implement rules-based chatbots that are 99-percent effective, and why you should get on board, in this VB Live event!
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When chatbots were the rage in the tech community, every company was building one, every business wanted one, and it was a wave of smart bots getting designed and implemented across companies and across industries, says Leslie Joseph, principal analyst at Forrester Research.
“But we were watching the impact of these chatbots on things that really matter — the customer experience, the metrics around customer engagement, like call deflection or self-service automation rates,” Joseph says. “And the thing is, some of the metrics that were fundamental chatbots, and to customer care in general, went unmeasured.”
Mostly it was hit or miss, Joseph says – though “hit” usually meant “acceptable,” and the success rates weren’t really moving. And when you’ve spent that much money and time on a new and fancy technology, it’s a little alarming.
Misses can get ugly. She points to earlier in 2018, where Telstra, the largest telecom company in Australia released a chatbot called Cody on their website and their mobile app. It began going into recursive loops where it wouldn’t know the answers for a lot of the common questions that Telstra’s customers were asking it — and not know how to transfer to a human, apparently. Frustration among customers translated directly into a huge backlash on social media for Telstra.
“What we’ve figured over the years — this may sound surprising to some, and obvious to others — but as customers, what we usually want is not conversations,” Joseph says. “Nobody wakes up in the morning thinking, yeah, I’m gonna talk to a chat bot today!”
We don’t want to talk to the enterprises we do business with — we want convenience. We want to get things done.
“If you ask pretty much any good customer service professional, they’ll tell you that happiness or satisfaction, in the context of customer care, is usually interpreted as the fastest and the most frictionless path to the answer to your questions,” she says. “And so when you think about, in this context, how effective chatbots have been at creating satisfaction, what you notice is that they’ve not really been as effective as we had hoped and wished.”
While this whole idea of AI is evolving, it’s really nowhere near where it can seamlessly, or even partially seamlessly, mimic a human, which has pretty much been the state of promise for so many of these emergent chatbot solutions.. Vendors boast in some cases that their chatbot is “as good as your best customer service agent,” but that’s never true. And years have gone by since the first chatbot surge, and the killer app for conversational engagement, the chatbot to rule them all, has not really emerged.
Now that the hype cycle has died down, and the dust has settled, it’s time to start executing chatbot technology and chat-based customer service in ways that are actually helpful to customers.
“Large brands like Amazon, that have huge investments in NLP or AI technology — they’re the owners of platforms like Alexa, but they’re not applying Alexa into the customer service scenario on purpose,” points out Abinash Tripathy, co-founder and chief strategy officer at Helpshift.
When customers come in for customer service, they want convenience, personalization, rapid responses. Amazon focused on solving that problem with a narrow-path decision tree and simple rule-based bots.
“If you don’t get caught up in the hype and don’t go all the way over the deep end, like we did a couple of years ago, and you focus on solving customers’ problems, there’s a lot of success that can be had,” Tripathy says. “You can drive a lot of business value through chatbots.”
To hear real-world success stories from companies both big and small, how companies across the world have been successfully implementing “dumb bots” for years, and how to effectively, efficiently, and inexpensively deliver the kind of customer self-service that keeps your customers coming back for more, catch up on this VB Live event!
- The difference between NLP and rules-based bots and why it matters
- Why companies like Amazon are turning away from natural language processing-driven bots to rules-based bots
- How to deliver mobile and web-based customer service that works, using the right bots.
- How rules-based bots make the customer journey more effective
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