It is quite hard to surf the internet without encountering a chatbot these days. In fact, according to surveys, 80% of companies want to employ them into their businesses by 2020.
But although many bots on the market do a great job meeting consumer needs, there are others that don't deliver.
As a business, you need to be able to measure the effectiveness of your chatbot as a part of your customer service. The process of defining the best KPI’s for your company depends on the goals and functions you want the bot to perform. Here are 7 metrics of success you can use to monitor and improve your chatbot’s performance:
One great way to measure how well your chatbot is performing is by asking the people who use it. Fortunately, you can use the same chatbot to get this information., For instance, you can set it to ask key questions such as, “How likely are you to recommend our chatbot, on a scale of 1 to 10?” This will provide you with a great way to understand the customer experience performance of your bot, and the areas it is lacking to allow you to improve them for optimal performance.
In this case, the activation rate refers to the likelihood of a user responding to a chatbot’s initial message with an answer or question that is relevant to your business goals. For instance, a chatbot that is designed to provide weather updates will receive an activation rate if users enter their location.
This allows the chatbot to provide them with accurate information. If you realize that people are not responding when your bot reaches out to them, you can think of ways to tweak it to provide more satisfactory results.
The best indicator of a chatbot’s value is the financial benefit it brings a company. There are many different ways you can check the impact of a chatbot has on revenue, and the best one will be based on the bot’s purpose. For instance, you can measure a bot’s profitability by checking how much it saves the business compared to hiring customer service reps to man your site 24/7.
You can also measure its efficiency by checking its impact on your customer service.
Check to see if your self-service rates have improved and whether your customers are more satisfied. This will lead to an increase in repeat sales and higher online conversions, which eventually will impact your company’s bottom line.
Self- service Rate
You know that a chatbot is working efficiently if potential clients get precisely what they want without needing any human input. If for instance, your bot’s goal is to help users change their passwords, you can measure success by checking the percentage of users that have successfully achieved that without requiring any human assistance.
The self-service rate is closely correlated with the cost-saving facet of revenue growth. So check how much your company is able to save after the bot does its job efficiently.
Although bots have a strong natural language processing, they do not always understand what a user is trying to communicate. These confusion errors are an important indicator for measuring your chatbot’s performance. Chatbots receive three types of errors, each of them needing their own kind of response.
- The first error occurs if a bot does not understand a comment. In such a case, a basic response such as “Sorry, I can't understand that. Please rephrase your question?” will do.
- The second trigger occurs when a user asks the bot questions that are outside its remit. If you realize these types of triggers regularly, consider programming the chatbot to relay a message that outlines its exact purpose.
- The final trigger occurs when the bot wants to move a potential client to a customer service rep after an unfruitful interaction.
Machine Learning Rate and AI
How strong is the artificial intelligence of your bot? You can check the percentage of client questions it understands to measure this. You also need to check if your chatbot can learn independently. If it does, measure progress by comparing the improvement rate in self-service over time without needing human intervention.
This refers to the number of users that return to the chatbot for more engagement over a certain time frame. The time span may vary based on the bot’s specific purpose. For instance, a diet chatbot will require daily engagement and will benefit from the analysis of its one-day retention.
Today’s consumers demand the need for chatbots due to their need for easy and effective service. Unfortunately, not all chatbots are able to deliver on this promise. But with these KPI’s you can ensure that your chatbot stays one step ahead of its competition.