because not all bots need to be great at conversation.
Lots of great chat- and voicebots have been developed and presented to the public in the last couple of months. Think about Google home, Amazon Alexa, Invoke and Apple HomePod. The tech industry was baffled when Google presented Google Duplex at Google I/O. Microsoft announced late May that it had acquired the AI Startup ‘Semantic Machines’ in an effort to make its bots and intelligent assistants sound and respond more like humans. And the list goes on. It’s clear that big tech corporations are investing in making the bot experience feel more like natural conversations.
Although we’re big fans of the virtual assistants mentioned above; we should ask ourselves ‘does my bot need to be thàt smart in order for it to be successful?’.
Not every bot requires its own persona: you don’t want a social chatbot personality in a business setting, but you also don’t want a sturdy business persona in a social bot experience. It’s important to consider the use case.
Your bot can be great at conversations. If you’re designing a virtual assistant, it should be! It can have a vast vocabulary and can even make great jokes, tell you about the weather or help you discover music you like. But unless it addresses the problems that your users need to solve, these capabilities may contribute very little to making your bot successful. According to our findings, we shouldn’t assume any correlation between a bot’s intelligence and how much Natural Language it can handle, and the user adoption of the bot.
If you want your bot to be successful, you need to assure you are creating a bot experiences that actually solves a business problem, in a way the users will prefer the bot experience over alternative experiences like apps, websites, phone calls, or other means of addressing their needs. Ensuring a great user experience should be your number one priority during the design phase of a bot. Forget about trying to create the next Siri, Google Home or Cortana for a minute.
Here are some of the key questions you could ask yourself during the design phase of a bot:
- Does the bot easily solve the user’s problem with the minimum number of steps?
- Does the bot solve the user’s problem better/easier/faster than any of the available alternative experiences (app, website, phone call, …)?
- Does the bot run on the devices and platforms where my users are?
- Do the users naturally know what to do when using it?
Note that none of these questions are directly linked to how ‘smart’ the bot is. In most cases, it is unlikely that making your bot smarter will guarantee happy users or adoption of your platform. In reality, many bots have little advanced machine learning or natural language capabilities. And that’s perfectly fine, because a lot of use cases don’t require those capabilities. A bot may include those capabilities if they’re necessary to solve the problems that it’s designed to address, but often a ‘dumb’ (yet effective) bot with a limited scope and an effective flow has a far more successful user adoption rate.
This blog was originally posted here.