Did you know that your cellphone contains already a software that recognizes voice and allows conversation between the operating system and a human? Conversational Commerce is a trend that some consumers have already adopted. In business-to-business and business-to-customer contexts, Conversational Commerce offers completely new opportunities for developing customer service and customer experience.
At the moment, human-machine communication is very consumer-driven
Conversational Commerce is basically about the verbal communication between a human and a machine. At present, consumers are already using e.g. Amazon’s Alexa Voice Service, which responds to the questions addressed to it via Echo speaker. You can ask Alexa to play music and ask it information e.g. about news, sport results or weather forecasts.
At Consumer Electronics Show CES, held in Las Vegas in January 2018, you could see hundreds of smart networked speakers intended for home use. In the third quarter of 2017, Amazon’s deliveries of smart speakers increased by 498 % compared with the previous year. In 2017, five million units were sold. At the moment, the field is very consumer-driven, and Conversational Commerce and gesture recognition are emerging also e.g. in the automotive industry.
What Conversional Commerce is about at system-level?
Broadly speaking, Conversional Commerce is about how we can get the system to adapt to human behavior and way of doing things. Often, it’s based in machine learning, which starts to recognize voice, motions and shapes. Through machine learning, user interfaces develop to support the natural human behavior; in the future we won’t tap our cellphones and tablets as much as we are doing now. Moreover, the entities formed by devices and the systems managing them are becoming more and more smart, and at the same time their use becomes simpler and more and more intuitive.
One noteworthy point is also that the system must be able to distinguishing between sound and speech. Through voice recognition the machine is able to know, what is happening e.g. at home, whether the sound is related to opening the fridge door, water damage or burglars. The principle is: “What an eye doesn’t see the ear can hear.” The above-mentioned applications don’t require a dialog, but the machine must be able to constitute rational cause-effect relationships.
Understanding about interaction and creating a rational conversation as a challenge
Modelling of conversation is also an important element. When a human is speaking with a conversation application – virtually with the system underlying it – he has a certain preconception about how the conversation will proceed. This requires, that UI designers can build a dialog which a human can perceive as meaningful and matching his expectations. In some communication situations, the verbal communication can be very limited: if we ask the outer door to open, we don’t expect the system to answer us with many words.
It is essential to understand and tell the user which role the system has in the dialog. Equally important is to teach the system what the user needs from it. If this mutual understanding and knowledge don’t exist, the conversation will not succeed.
Also background noises can teach the system
Always, it’s not only about exchange of information between the user and the system. The system can also interpret from the noises heard in the background of a conversation whether it is reasonable to continue the dialog as it is or e.g. via a chatbot. Not so ideal location for a conversation can be e.g. a bus or railway wagon full of people; a conversation between outsiders annoys fellow travelers or can jeopardize the information security the company.
At the moment, we are in the early stages in the planning of a dialog between a human and a machine, and the gist of the successful solution is planning the conversation. It’s also important to understand that this is a complementary channel, not an alternate one. However, there is every chance that in the near future, the conversation between a human and a system opens up outstanding new possibilities both in consumer environments and in the business world.
Conversational Commerce runs on Design and AI
As earlier stated the conversational commerce successful requires empathic user-centric situational design to able detect behaviors, intents, tones and purposes behind the conversation. What is natural to human beings is not so easy to computer systems. Successful conversational commerce solutions require also rich full technology stack to turn speech to text, to design conversation, to analyse tone and audio and to combine complex enterprise information. This is why Symbio uses IBM Conversational Services and is partnering with IBM. IBM Conversational Services allow Symbio to concentrate to end-user and to conversation.