Four bot-user interactions to consider before launching an infant Chatbot - Part 1
Well, we weren’t expecting that!
During her recent London Fashion Week catwalk show, Victoria Beckham got more than she bargained for. Amidst rumours of a divorce from her husband, David Beckham, VB launched an automated Facebook messenger app - ‘Victoria’ bot - for her fashion line. What she didn’t bank on was her fans using the bot to interrogate her marriage, personal life and even her political views. Not only that, but the automated bot only seemed to confirm suspicions that the Beckhams were on rocky roads and that ‘Victoria’ was happy with Theresa May’s efforts to navigate Brexit.
We believe that Ms Beckham (and her team) could have anticipated and better managed this bot use by considering key bot-user interactions that directly affect the experience and quality of automated infant chatbot responses.
According to Facebook IQ, more than 2 billion business-related messages are sent through Facebook Messenger chats. Should Victoria have primed her infant chatbot before setting it free in the wild, it would have had better PR and brand experience.
Prime your infant bot for fitness
With the increased conversion rates and decreased time to conversion enjoyed by chatbot deployment, Gartner has predicted that chatbots will power 85% of all customer service and that 25% of customer service and support operations will integrate multi-channel, multi-touch point chatbot technology in the next two years. In fact, 48% of consumers would rather connect with a brand using chat than other forms of contact (Hubspot, 2017).
Automated chatbots learn and optimise themselves as they get used but this takes a little time. It also means that a proportion of users will be exposed to the bot in its infancy during launch. The challenge is decreasing any negative impact of an infancy learning bot on the user experience.
Before automated infant chatbots are unleashed, they are populated with answers. For any imaginable question that a user wants to ask the bot, the bot is set to reply with an on-brand response. Through repeated guerilla usability testing we have found that an 100% Q&A (Question and Answer) accuracy hit rate isn’t everything.
In a two-part series, we’ve identified four bot-user interactions which work together to manage user expectation which, when bots respond correctly against, create micro moments of brand delight for the user and brand value for the business. This, the first in the series focuses on the relationship that the user wants to have with the bot. The second in the series looks at the affect of user intention on bot responses.
1. Cater for the Intimacy Spectrum
Variations of user need, behaviour and linguistics reflect a response expectation that corresponds to a level of intimacy that the user wants to have with a bot.
On the extreme left-hand side, where the desire for intimacy is zero, we have a modus operandi that demonstrates a very functional expectation of the bot:
a. Stance: “Give me what I want”
b. Time: “Limited”
c. Formality: “I won’t likely say hello, goodbye or thanks”
d. Syntax: “I will use keywords, short and succinct, on average two words”
In stark contrast, on the extreme right-hand side, where the desire for intimacy is 10, we have traits that convey a very emotional expectation of the bot:
a. Stance: “Let’s chat!”
b. Time: “I have time to spare”
c. Formality: “I will likely ask you questions that do not pertain to my task”
d. Syntax: “I tend to use full sentences”
The Intimacy Spectrum is further compounded by the tendency of users to treat the bot as human or having a human at the other end, despite being told that they are automated bots. UI devices such as the Chatbot window title, the initial greeting and response content and tone are all used to help manage user expectation, but their impact diminishes as the conversations progresses.
In its infancy, the bot needs to cater for both extremes of intimacy and everything in between. The art of decreasing the impact of an infancy bot lies in balancing the functional and emotional intimacy expectation of the response within the accuracy and size of response.
2. Embrace the Gamers
Curiosity questions, as opposed to transactional questions, are those questions that users ask, that are not necessarily directly relevant to the bot’s intended purpose. Though they can be in some way related to the product or service offering or the sector, curiosity questions tend to be more generic and reflect local conversational practices.
Curiosity questions tend to come from the users on the high end of the intimacy spectrum because regardless of content, i.e. what the question is and whether they are built into the transactional part of the question, curiosity questions are inherently designed to establish a closer relationship between the parties.
As shown in this exchange, the user goes into gamer mode and is not necessarily trying to quickly get to a particular answer.
The gamer plays and is subconsciously trying to push the bot, to test it and even to break it. The user in gamer mode doesn’t necessarily expect answers to its curiosity questions but when the bot responds back in a playful, relevant and relatable way, these Easter eggs are moments of delight for the user that can positively enforce brand perception. The bot’s purpose is not only to alleviate pain points but to augment moments of delight.
Curiosity questions demand a brand intensive composition compared with transactional questions which are more formulaic.
Emoji and emoticon cognition should also be built into the question detection and answer response. Not only is this universal commonplace communication but we can see nuances - sentiment - that are ripe for bot question and answer analysis and learning. This will supplement the distillation of entities - keywords - from utterances to increase the quality of the language model.
Where user language and motive vary so much, bots must be equipped to deal with this, and perform appropriate actions.
In the next post, read how bots can be used in different ways – as a Mariner or to build micro journeys...