Measuring chatbot success requires a variety of contact center metrics, including customer satisfaction, completion rates, reuse rates and speech analytics feedback -- all of which ultimately aim to improve the customer experience.
As chatbot use in contact centers flourishes, evaluating key metrics is necessary to ensure that this self-service technology supports customer needs in a simple, yet effective manner.
Here are four key performance indicators for contact centers to measure chatbot success.
1. Customer satisfaction
One of the important chatbot success metrics to measure is customer satisfaction after an interaction with a bot. This is done in a similar manner to gauging interaction with an agent -- except there needs to be additional focus on customer effort.
Much of the human element is gone with chatbots, so there needs to be a deeper focus on the amount of customer effort during the interaction, including:
- whether the chatbot was able to understand the customer;
- whether the chatbot was able to respond to the specific question being asked;
- whether there was first-contact resolution; and if so
- whether the chatbot transferred the customer to an agent when the question could not be understood.
2. Completion rates
The self-service completion rate is another of the important chatbot success metrics to calculate. Measuring completion rates in bots is similar to that of an interactive voice response system. One of the major goals of chatbot automation is the reduction of expenses via a higher level of self-service.
If a customer is transferred to an agent, it is necessary to identify at what point the caller ends an interaction with a bot and begins interaction with an agent. This analysis helps identify opportunities to improve chatbot comprehension, scripting and potential additional functionality to improve self-service levels.
3. Reuse rates
It is equally important to identify customers who have used chatbots previously to see if they reuse the bot vs. quickly default to an agent. This provides insight above and beyond the feedback from customer satisfaction surveys by identifying whether customers were satisfied with their previous chatbot interactions.
4. Speech analytics feedback
Analyzing the specific elements and tone of the call -- including customer frustration levels and whether a customer must repeat themselves -- can provide insight into how bot interactions work and identify opportunities for improvement.
Dig Deeper on AI for sales
Related Q&A from Scott Sachs
Call center agents need to make sure they have the skills for which hiring managers are looking. Here are the top call center agent job skills you'll... Continue Reading
The largest companies can choose the largest CRM platforms, but what's left for small- and medium-sized businesses? How should they choose the right ... Continue Reading
While many factors can make or break a sales-service platform merge, three challenges stand out when combining service, sales strategies. Continue Reading
Have a question for an expert?
Please add a title for your question
Get answers from a TechTarget expert on whatever's puzzling you.