Chatbots are not a new concept. They’re not even from this century. Alan Turing’s 1950 paper on ‘Computing Machinery and Intelligence’ laid the foundations of computer conversation via the Turing Test. Almost 30 years ago in 1979 (the same year Sir Tim Berners-Lee invented the World Wide Web), Moviefone began their interactive telephone service. The first real and widely used ‘chatterbot’ named Smarterchild was powered on in 2000.
These fundamental and literal milestones along the ‘Chabot revolution’ make us question why it has taken so long. The answer is quite straightforward and grounded in reality. Chatbots, despite their on-paper potential to represent computer intelligence, have really just been an alternative way to search for information or complete simple, routine operations.
Voice and text commands add value by using their infinite patience to channel your path across a known set of choices with less deviation and more speed. These principles have been transposing quite favourably into customer service. Gartner predicts that by 2020, 85% of all customer interactions will be handled by chatbots.
Let’s face it, most companies will admit their top three customer questions represent the lion’s share of request volume. One of China’s largest food delivery companies, Ele-me, receives two hundred thousand support requests between 11–2pm on weekdays. 90% are ‘My food hasn’t arrived yet’ and ‘My food fell out of the container’. They are all becoming robot-answered with version of “We’re sorry. Nothing can be done right now. Here’s a discount code for your next order’.
It is no surprise, then, that the upward creep of chatbots has been primarily absorbed by this form of direct questions-and-answers. What we have reached in recent years could be bluntly described as a glorified FAQ around a tight decision tree. Now thanks to a background rise in network speeds, edge computing and service integration — and also we humans being almost ready to talk to computers… the real revolution is upon us.
Enter the conversational UI (User Interface). This is a more general term for natural-language based interaction with computers. Chatbots are a key part of the interface. The bigger picture includes text, voice, visual patterns (like cards and buttons), cross-platform activities and a new way of getting things done.
The power here is to make interaction natural. As humans in our first years we go through implicit cognitive development to communicate with the people around us. Everything else is explicitly learned; using a mouse, typing on a keyboard, browsing an OS or inputting multi-currency-taxed-partial-refunds into the booking system. Some actions are more natural than others.
More than we care to admit need specific training.
But what if this wasn’t the case? What if we could make our every-day actions feel like natural every day interactions. No training, no errors, no irrelevance and no mashing buttons to reach an outcome with the least immediate pain.
This is a significant dimension beyond looking up movie times or complaining about late food delivery. When it comes to getting things done we are playing on a new dimension of business solutions.
8 things to keep in mind when building a conversational business UI.
We’ve been spending time here in the Innovation Lab understanding what conversational UI means to SMBs as they conduct business day-to-day. What we’ve found has been very revealing. With the right mindset comes the potential to redefine chat-based interactions. Here are some of our key points to keep in mind when building solutions designed to help businesses operate:
 | 1. Business vocabulary is already outside the natural sphere of conversation. industry-specific jargon are interspersed amongst seemingly general sentences, making them particular difficult to extract. Common abstract nouns like ‘opportunity’ or ‘refund’ often become concrete or proper nouns to the user. They are referring to a specific type of business object and perhaps a specific instance of an object. Expect to define a dictionary of business actions and build well-defined intents across them to accurately detect sentences like ‘I have an opportunity. |
 | 2. Once the user’s intent is understood, magic can happen. Typical business interfaces involve lists, forms, mandatory fields, default values and dependencies. With a conversational interface all this must be maintained entirely behind the scenes. Assume that missing information can be requested as part of the rolling interaction. In this way, the user is not overwhelmed with clutter and is instead getting precisely their intended job done. |
 | 3. Businesses are complex. Trying to handle all possibilities in a single thread can be both heavy to implement and potentially dogmatic to use. In the Lab we are building a family of ERP bots which are experts of their own domain and act as concierges to their service; creating opportunities, handling customer records or summarizing information. By openly talking to each other within the UI, they provide handover in what feels like a more natural way than typical interfaces. As humans we are actually quite comfortable with talking with different people about different topics. |
 | 4. In business, interactions are rarely discreet. A huge milestone in Chatbot development is nested conversation threads. A prompt to the user such as “tell me the customer’s name” may very likely be answered with a question “who are my customers?”. As tasks become complex and potentially lengthy, define a strategy for dealing with interruptions. Do this either by visibly parking the existing thread, or handing over to a new agent, or indicating that a sojourn has happened. Messages in the log like “cancel” “get me out” “forget it” are common indicators that uses are getting lost and want to start over. |
 | 5. Success is a very specific outcome and failure is not an option. This is business. The user has to get their job done and inputting a sales order has no margin of error. They don’t have consumer-style flexibility to try a different provider or come back later. Business interfaces are particularly downward sticky. Once an action fails, trust is broken and spreadsheets are opened. Ensure that the interface provides commitment, confirmation and feedback when performing actions like creating and modifying records. |
 | 6. Extensibility and underlying complexity cannot be ignored. As a general rule, the conversational UI should be able to handle the same degree of customization as the standard UI, whether that means user-specific metadata or client specific dependencies such as mandatory fields or tax calculations. It is okay to narrow the scope and push/refer to existing methods if they are too complex to handle right now. It is not okay to ignore them and essentially throttle back your business software to a rudimentary version for the sake of adding a chatbot. |
 | 7. Start with Zero UI. The most common denominator for integration is pure text. Whilst platforms may build on top of this with UI elements and widgets, there is no guarantee they can be directly transposed between platforms. Thinking text-only also ensures the basics of conversation are covered. Whilst the final solution may never be 100% text/voice (we believe it is more likely that smart speakers will converge with displays before too long), starting this way ensures the fundamentals of conversation are covered. |
 | 8. Natural language is synonymous with intelligent interactions. If the interface is human-like, then the brain should be human-like too. This is one of the biggest areas where conventional chatbots fail to satisfy because we have such high expectations going-in. In business, this means a pre-requisite of business intelligence whether that be smart-handling stock replenishment, identifying churn-risk support tickets or simply automatically applying discounts. It may mean re-thinking the underlying business-logic in your solution. |
If it works, conversational business UI will become a seamless part of their day-to-day life without even acknowledging the Turing Test. Users will become closer to your products than ever before, benefiting from being better understood on their own terms. This is a new realm of chatbots and if done right, will trigger many other questions and solutions which might just re-define the way business happens.
About the SAP SMB Innovation Lab
As part of SAP’s SMB Group based in Shanghai, China, we mold the hottest technology trends into inspiring innovations. We act as an internal startup poised on the shoulders of a world market leader to get our hands dirty in defining and creating new ways of getting business done.
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