Companies like Amazon are dumping the smart, AI-powered and NPL-reliant bots and going all-in on a new generation of rules-based chatbots that are easy to implement, easy to use, and 99-percent effective. Learn how to leverage the simpler rules-based chatbots that can solve customer service issues, fast, when you join this VB Live event!
“Customer service has turned into something that consumers actually hate,” says Abinash Tripathy, co-founder and chief strategy officer at Helpshift.
Companies spend $1.5 trillion running contact operations around the world, in an extremely labor-intensive, human-intensive industry, turning out a service that frustrates customers more than sends them away with a great brand experience.
The problem is that companies still haven’t evolved as much as consumers have, Tripathy explains. While consumers have moved on from the phone to very modern digital experiences, brands are still too often completely disconnected from them. Customer service is still essentially a legacy experience, where consumers are forced to call, then wait, listening to elevator music, and then be interrogated by a human being.
Where companies have tried to apply AI, usually in the form of speech recognition technologies he says, it’s been disastrous. The first generation of bot technology, deployed over the last four or five years, were all built on a classic AI approach and on NLP, with disappointingly low accuracy levels. But nobody could bring any service to production with these NLP bots.
“All these big brands that invested millions and spent a lot of time with IBM basically walked away with very negative experiences,” Tripathy says. “None of those bot deployments were successful. Not a single Watson deployment has been proven to be successful.”
There’s the NLP bot approach — and then there’s bots that work, he says. Companies like Microsoft and Amazon are seizing the opportunity to digitize their entire contact center operation by moving to messaging-based technologies that feature “dumb bots,” that streamline the entire process and slash costs.
Amazon has the most natural language processing engineers in the world right now — in Boston they’ve assembled between 3,000 and 4,000 AI engineers who work on their core NLP platform, Lex, which is used to power Amazon’s Alexa service. But Amazon was smart not to bring any of that into their customer service bot, Tripathy says.
Instead, the Amazon bot uses a guard-railed kind of approach, building narrow dialogues on the bot platform that do simple tasks, automated without a lot of intelligence. For example, you can go to the Amazon bot and say, I ordered something, and I want to cancel it. Or it’s arrived and I want to return it.
“It’s not, ‘Let me try to understand what you’re trying to say.’ It’s more like, ‘Here are things I can do for you, customer. Choose one option.'” Tripathy explains. “Amazon’s approach works to maximize what’s possible today, not lead consumers into a path of confusion and disillusionment about bots. All you have to do is use the Amazon bot once and you’ll think, I’ll never talk to a human again. It just works.”
The biggest reason you want to apply a bot is because bots are the always-on, ready-to-answer mechanism, he adds. Not only that, it’s very hard to scale a human-oriented contact center to a point where you can cater to all customers with a real-time approach, where every customer is serviced almost instantly.
Even the biggest brands in the world struggle to do that, because of the cost. Every time you scale by adding more human capacity to your contact center, you’re adding a commensurate amount of cost. Bots can solve the most common, rote, and routine customer service — which makes up 80 percent of a contact center’s inbound requests — fast, which drives high levels of customer satisfaction and indirectly helps maximize LTV.
“The purpose of customer service typically is to maximize customer satisfaction and everything else is secondary,” Tripathy says. “With these bots, brands are benefiting with high levels of customer satisfaction and driving top level metrics.”
To learn more about how bot technology can help provide a better and cheaper customer service model, why dumb bots are the future, and how to seize the opportunities they offer, don’t miss this VB Live event.
Don’t miss out!
- 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
- Leslie Joseph, Principal Analyst, Forrester Research
- Abinash Tripathy, Co-Founder and Chief Strategy Officer, Helpshift
- Mitch Lee, Manager, Credit Karma and Co-Founder, Penny
- Rachael Brownell, Moderator, VentureBeat
Sponsored by Helpshift