Chapter 6. Summary
This book is dedicated to anyone interested in bots. The bots are said to be the “new apps” and the tools are only starting to improve, just like with the early apps for mobile devices. Some tools focus on ease of use, while other tools focus on complex systems or integrations with existing infrastructure.
The idea behind bots dates back to Alan Turing’s early research on computing machinery and intelligence in the 1950s. Turing laid out the idea behind what is now known as the Turing test, whereby a human and a computer would interact entirely by written messages. Turing believed that if the human recipient couldn’t tell the human and the computer apart, then the computer should be labeled as intelligent.
The first wave of bots were based on rules programmed into the software and were used to automate simple, repetitive tasks. However, bots have advanced to the point where they are streamlining support cases, explaining frequently asked questions, scheduling appointments, and completing orders. Originally, these tasks required multiple inputs from a human to answer rule-based logic questions. But with advancements in AI and leveraging deep learning, bots are now able to perform more complex tasks and write their own commands on the fly using massive data sets to answer even more complex queries.
One of the gray areas in the future of bot platforms is the concept of permissions and access control. In mobile platforms, users are asked to grant access to specific settings before an app gets access to their data. However, up until now, this has not been fully addressed in the case of bots. We are typically sharing very personal data when talking over messenger apps to each other. Messaging is a private and intimate thing and messenger app providers are expected to keep their user’s data private. Bots now enter the domain of personal and private communications. We can see a huge transfer in terms of data control: From the user to the messenger app provider. Usually bots don’t know much about their users initially. Typically, it is something like the name, screen name, and maybe additional data.
Facebook, for example, discusses their privacy policy, just like with Messenger, their chat app. You can order your Uber drive through Messenger, buy stuff or plane tickets, and pay directly in Messenger. All transactions are logged by the platform’s servers, which monitors and logs the communication between the user and the bot.
Things to Remember & Things to Avoid
These tips are given by the Messenger Platform itself to help guide developers to produce better bots and follow best practices:
Consider the ideal creative format for meeting your business objective. A click on a photo ad in News Feed will open Messenger, but a click to play a video ad will open the video.
Set expectations for how people will experience your bot by choosing an appropriate call-to-action for your ad.
Use consistent language. Your ad’s copy should feel similar to the language used in your bot.
Design thumb-stopping imagery to capture attention on mobile. The creative you use for your ad should reflect insights about your target audience.
Build a media strategy optimized to reach your audience using direct response best practices.
Leverage structured messages (JSON) to follow up in a more conversational way. Otherwise, people who click or tap on your ad will receive a copy of your ad as their first message.
Don’t over-promise in your ads. Instead, communicate your bot’s value proposition. Share what makes it unique to inspire interest.
Don’t mix bit.ly with a CTA Button. Instead, use one call-to-action to encourage click through to your bot.
Don’t violate any of the related policies.
Include your ads policy and Messenger policy.
Most business models for chatbots are still emerging, but as we look to Facebook and WeChat, we find applications that let you transact within the messaging application. Even though it is still early for ecommerce in chat applications, we are seeing interesting use cases, such as selling books and apparel. In these use cases the brand is making a personal appeal to their consumers in chat. Bots are a great application to help surface actionable insights or refine our options and take action.
Because time is money, people will pay to automate many tedious aspects of their lives, and thus the potential for customer-facing businesses to provide new services and means of services is very promising. Saving the consumer time is just one of the compelling use cases of bots.
The future is not just one of building standalone bots or bots on platforms. The big question is: What will the inflection point be with bots? When the Apple App Store launched, it catapulted apps to the mainstream—now we can’t imagine a smartphone without apps. It remains to be seen what the dominant distribution mechanism will be for bots. This is quite literally a billion dollar question.
Thank you
Thank you for buying and reading our book. Without readers like you, this collective work wouldn’t exist.