The rise of chatbots has been a source of great interest in the business world in recent years. With a Salesforce survey showing that 15% of adults in the US have interacted with a chatbot in the last year and that 37% would use one in an emergency, it is something that is becoming an increasingly important part of daily life.
Yet, some business owners are still unclear on how they can measure the performance of their bot in order to maximize its potential. This is where a better understanding of chatbot metrics and analytics is necessary.
Many people believe that chatbot metrics and analytics are the same as web analytics. Yet, this is a different subject that requires you to take a fresh new approach to it.
As with any kind of metrics, this is about tracking and assessing processes by accurately measuring them. When done correctly, this allows the business to more fully understand the performance of their chatbot.
Chatbot analytics will typically provide information such as the total number of users, together with the number of active and engaged users. We can then see the likes of the different types of messages used in conversations and the overall success rate of the bot. All of this information is crucial in understanding how the chatbot is doing against its objectives.
Of course, users may decide to create their own metrics to meet their own analysis needs. However, the basic idea remains the same, with the data letting us see exactly how it is performing in the most important areas. This allows us to see where bottlenecks are created and where better communication is needed.
Can You Create Your Own?
The next issue to look at is how to create your own chatbot analytics tools. Finding out figures for how a bot is doing can be tough, so getting a customized tool would very helpful. Therefore, you might wonder: can this only be done by experts or can anyone do it?
There are some third-party tools that you can integrate fairly easily. This means you don’t need to be a technical expert to get started, although you may need to set aside some time to do this well.
However, some users find that the user interfaces on these bespoke tools can be a little cumbersome and not very user-friendly. It should also be pointed out that you might struggle to find a tool that suits you perfectly, which can mean spending a lot more time on trying different approaches than you would like to.
What Other Options Are There?
So, what should you do if you want to improve your understanding of your chatbot’s performance but prefer not to spend a huge amount of time on it?
An interesting alternative comes from Sisense Boto. This is an embedded analytics tool that is accessible to anyone and extremely easy to use. It can be adapted to meet your exact needs and then embedded into your system for a fully branded look. There is also the option of integrating it with third-party applications.
This tool is effective because Sisense uses its own data science and machine learning tool, InsightMiner, which simplifies the user interaction. They have also included natural language capabilities, which is powered by their partner, Narrative Science, and means that human-level conversation can take place.
“#Health check-in’s are surprisingly fu” (CC BY 2.0) by Mark Koester
What Does the Future Hold?
The future of chatbots is undoubtedly exciting. Areas such as customer service, health apps, the blockchain, and the AI developed by Elon Musk are all linked to the growth potential in this field. Perhaps the details released by Google DeepMind – about AlphaGo Zero and its ability to learn from scratch – provide the most intriguing recent development in the field.
Will we use chatbots for just about everything in the future? A survey by Oracle in 2016 seemed to suggest so, estimating that by 2020 some 80% of businesses would be using them. While this figure might seem slightly optimistic just now, there is no doubt that it makes sense for forward-thinking companies to look into how chatbots can benefit them when used with the right metrics and analysis tools.