THE DAWNING OF THE AGE OF THE CHATBOT

As Mavenir have already mentioned in our previous blogs, reach is key for brands, but once the connection between the brand and the consumer has been made, a fast and responsive bidirectional communication needs to be established. This applies also to mobile messaging.

Businesses have always seen the potential of embracing technological advancements. With the arrival of the telephone, they started to provide a phone number to let customers reach them. Later, enterprises realized that they could centralize customer service using the telephone and reduce the cost of having physical branches in smaller markets, and the call center was born. But that was still costly, so technology figured out a way to pre-screen incoming calls automatically with pre-recorded messages and touch-tone options, and thus the auto-attendant was created.

In a similar fashion, message-based customer engagements have had a similar evolution. Businesses started with chat options in their websites where customers could converse with real people in a contact center (the evolved version of the call center that included data applications). But contact centers are also expensive, and many of the queries their agents were receiving were similar and repetitive in nature—for example, password reset requests. This led to enterprises looking at technology to provide automation solutions. Thus, the chatbot was born.

A chatbot, in essence, is a piece of software that interacts with users to provide predefined responses to their inquiries and sometimes collects specific personal or service-related information. Chatbots can vary in complexity, ranging from very simple bots based on keyword detection that run over predefined scripts and decision trees (like a text version of an auto-attendant or a Choose Your Own Adventure book), to very sophisticated entities incorporating artificial intelligence and natural language processing capabilities that can emulate the responses of a human and automatically escalate a chat session to a human agent when needed.

Chatbots have huge potential for enterprises in the following areas:

• Customer service improvements — eliminating the need for those annoying “all our agents are busy at the moment, please stay on the line” messages, accelerating responses, and easily locating answers to frequently asked questions at a minimal cost. And not to forget chatbots provide service 24 hours a day, 7 days a week without the need for breaks!
• Online shopping friction reduction — for example, to provide a guided shopping experience, facilitate product information, clarify available options, displaying product availability at physical stores, as well as collect user data, credit card information, delivery options, process payments, and, finally, confirm the order. The consumer does not need to go through different departments and repeat the same query to multiple people.
• Communications personalization — chatbots can specifically answer the users’ questions instead of providing a long list of information like websites do.
• Response rate enhancements — if you wait 5 minutes to respond after a lead first reaches out, there is a 10x decrease in your odds of getting in touch with that lead.[i] Chatbots respond to 100% of the user messages immediately and can convert more users into buyers.
• Automation of repetitive tasks — users do not like browsing long FAQ documents online when they are looking for a quick answer such as business hours, return policy, delivery options, bill payments, making a reservation, subscribing to a mailing list, etc. A chatbot can reduce the number of calls to the contact center for these repetitive questions. For example, for a simple password reset, a chatbot can provide a fast response with a link to the password reset website with a cost of cents of a dollar, whereas a call to a human agent for the same purpose can cost tens of dollars.

Enterprises have seen the potential of chatbots and, as a result, multiple chatbot platforms have flourished in the market (Microsoft Bot Framework, IBM Watson, Amazon Lex, Google Dialogflow, Converse AI, Octane AI, Botsify, etc.) that provide connectivity to different messaging communities (Facebook Messenger, Slack, Amazon Alexa, etc.) and integrate with different web services (WordPress, Salesforce, Shopify, etc.).

A recent survey[ii] shows that 15% of users have used chatbots to communicate with businesses in the past 12 months and that users prefer chatbots over apps when communicating with companies. However, for those of us who have tried to use online chat on our mobile web browser, the mobile user experience still leaves much to be desired (multitasking between browser tabs is not convenient, there is a risk of accidentally killing the tab and losing the chat session, there are no notifications if the browser is running in the background, and many more inconveniences).

Fortunately, chatbots interact using messaging procedures and, from the telecommunications point of view, messaging with a chatbot is no different from messaging with a person. However, for the consumer, messaging with the chatbot on a mobile messaging application is much more convenient than doing it from a web browser’s tab (proper multitasking, message notifications, persistent conversations, etc.). To facilitate these interactions, the Messaging-as-a-Platform (MaaP) layer of RCS Business Messaging (RBM) provides REST-based API’s to connect chatbots to the mobile network and allow consumers to easily discover the brands. But this means that enterprises need to adapt—and in some cases re-create—their existing chatbots to use these RCS APIs.

Download the Connecting the Bots white paper for more information on RCS Business Messaging and how RCS can become another standard messaging channel available in the leading chatbot platforms to facilitate the relationship between brands and consumers.

^{[i] Lead Response Management Best Practices; June, 2015}

^{[ii] The 2018 State of Chatbots Report: Drift, SurveyMonkey Audience, Salesforce and myclever}