Every business wants to provide personalized service to all their customers. But, it can be an incredible challenge. If you are a super high end luxury brand it’s less of a problem. The high cost of your product or service limits how many people you have to please at any one time. But, what about everyone else?
Hiring countless customer service agents isn’t always an option and rarely economical. But a new solution is emerging in the form of chatbots, computer systems that mimic the speech and behavior of a real person.
As anyone who has struggled to get Apple’s Siri, Microsoft’s Cortana, or Amazon’s Alexa to understand them knows, the tech isn’t completely there yet. But, every year digital agents get a little closer to the real thing. The time is fast approaching when you won’t be entirely sure if the person helping you shop online is made of flesh and blood or ones and zeros.
Faster, Smarter, More Lifelike
Formerly, chatbots could do little more than recognize words and then offer back a canned response. For example if it noticed you said or typed the word “support,” it might respond by asking if you needed to be directed to a tech support agent.
Human beings have a natural inclination to interpret even somewhat ambiguous dialog as genuinely conversational, but it doesn’t take long for them to realize when their partner is having trouble keeping up. Most people only need one or two lines of communication before they realize they are talking to a machine.
But, today’s talking bots are moving past those rudimentary abilities towards something far more robust: natural language processing (NLP), which is roughly defined as the capability of a computerized agent to not just recognize a word, but to actually understand its meaning.
It just might be a killer app for customer relationship management. Not only will they provide a wealth of analytics for honing in on the needs and satisfaction level of customers, but it will enable incredibly personalized encounters for billions. Ad exec Pete Sena told Digiday:
“Brands know now that the No. 1 thing that they can compete on is experience — and chatbots, done properly, can really add value there.”
Another concurred: “It’s smart for the brand to go where the users are and create a presence on these platforms, while providing relevant and personalized one-to-one conversations with consumers.”
Will Messaging be as Big as Social Media?
Messaging apps in particular are quickly becoming a testing ground for state of the art commercial chatbots. Apps like Kik, WeChat, Viber, WhatsApp, and Facebook Messenger are growing exponentially. Facebook owned WhatsApp was the first messenger app to break a billion users in early 2016, and Facebook’s in-house messenger isn’t far behind, hitting the billion user mark last summer.
Messaging is even threatening to put social media sites in their rearview. The top four messaging apps, WhatsApp, Facebook Messenger, WeChat, and Viber, have 2.125 billion monthly active users globally. Remarkably, that’s roughly the same as the number of monthly users on Facebook, Twitter, LinkedIn, and Instagram combined! And, the messengers are mobile only, while social media is multiplatform.
Kik founder Ted Livingston is understandably bullish about the sector, and expects chatbots to push things even further:
“Chat apps will come to be thought of as the new browsers; bots will be the new websites. This is the beginning of a new Internet.”
It’s a bold claim, but he’s got some evidence to back it up. Scores of advertisers and brands are working with Kik on creating chatbots. Fragrance retailer Sephora created a chatbot that quizzes potential customers on their likes and dislikes and offers custom tailored product suggestions.
“How Can I Help?”
According to Bindu Shah, Sephora’s vice president of digital marketing, chatbots’ personalized output and opt-in nature will provide a better experience for their customers: “We can let clients ‘choose their own adventure’ with our content, rather than posting content that goes into a ‘newsfeed river.’ We believe more brands will want to interact this way too.”
Other messenger apps are also offering individualized promotions thanks to chatbots. On WhatsApp shoemaker Clarks developed three virtual characters to promote its new product, the “Desert Boot.” The digital agents can chat with customers and serve up product info as well as videos and music playlists. Dutch Airline KLM recently create a chatbot for Facebook’s Messenger that can send you your boarding pass.
Mobile fashion marketplace Spring has also developed its first chatbot to aid shoppers. Founder Alan Tisch reported that the move was necessary because the app ecosystem is becoming crowded. “Customers aren’t spending their time on a sprawl of apps anymore,” said Tisch. “But, there’s a high concentration of engagement on Facebook Messenger. So we created an experience to fit into the natural behavior that’s already happening on the platform.”
The chatbot makes suggestions based on simple questions like “What are you looking for today?” and “What’s your price range?” It also does followup work for the company like sending receipts and shipping confirmations, and it can answer basic questions about the status of an order. It’s all intended to offer immediate responses, personalized service, and interactions that are highly representative of the brand’s culture and narrative to millions simultaneously and at any time.
The Conversation Continues
There have been a few notable bumps on the road to a chatbot-driven marketplace, like Microsoft’s foul-mouthed Tay who picked up some bad habits from users feeding its learning algorithm with swear words and crude sentiments. Affair arranging site Ashley Madison’s phony fembots got it in hot water for luring unwitting conversants into purchasing memberships.
But overall, the future for chatbots is bright. Brands are looking into a number of uses from content distribution by delivering audio, video, photos, and articles on demand based on user queries, to customer service and lead generation, and of course a streamlined system for purchase conversion.