You’ve just set up a chatbot on your website to make it easier for your website visitors to communicate with you and get their queries answered.
That’s wonderful news!
But your work doesn’t end here. A chatbot isn’t something you can set up and forget.
You need to constantly keep an eye on its performance and keep improving it to make sure you're actually meeting your goals and not just sitting there with a deadweight feature that’s not adding anything to your business.
But more importantly, not leading to any conversations.
A chatbot isn’t something you install just because everyone else in the industry is doing it as well. So you need to ask yourself, is your chatbot impacting how online shoppers feel about interacting with your Shopify store?
Do these interactions translate into sales?
To answer these questions and determine whether your chatbot is effective or not, you need to take a look at your chatbot’s analytics for some very specific KPIs that are relevant to your chosen objective.
Let’s find out which ones.
This is a measure of the total number of interactions that are held between your website visitors and your chatbot.
It is an active track of sessions that begin when a person asks the bot a question on their own or when they receive a notification from the bot and decide to take the conversation forward, till some meaningful dialogue takes place between the bot and human.
This metric can help you judge whether your chatbot is being used frequently or not and whether there’s an increase in the number of people using it. A higher activity volume indicates that people are actually using the chatbot and holding conversations with it because they find it useful.
If a user ends a chat session in the middle of the conversation, before your chatbot's set goal is accomplished, it means the user has bounced off. Bounce rate is a reflection of whether your chatbot is actually useful to your visitors or not.
A high bounce rate means that your visitors are prematurely ending the conversation which could be due to a multitude of reasons such as the chatbot making irrelevant responses or providing inadequate information.
If your bounce rate is high, then the cause needs to be investigated on priority, lest you keep losing customers because your chatbot is incompetent.
This is a measure of the percentage of users who have had repeated conversations with your chatbot over a given period, i.e., the number of users who have returned to interact with the chatbot again after the first interaction.
If your chatbot is engaging people in positive conversations that they find helpful, then they would most likely come back to seek help from the chatbot again in the future.
A low retention rate means that your chatbot isn’t meeting your customers’ expectations and needs. So retention rate is a good indicator of whether your customers are satisfied with your chatbot or not.
This metric is a measure of the total number of questions your chatbot has answered accurately over a given period, which is crucial for understanding whether your chatbot is actually helping your visitors with their queries or not.
Since the technology behind chatbots’ language processing abilities is still not at par with human speech and its nuances, most chatbots aren’t capable of understanding an individual user’s intentions and expectations, and hence fail to deliver tailored responses.
A low matched response rate indicates that your chatbot is unable to answer the questions your visitors are asking it or responding with an answer that isn’t relevant to the question they asked.
This is a measure of the length of the conversations between your chatbot and users. A longer session duration means your chatbot is engaging your website visitors in longer conversations. This could either be good or bad depending on your industry and use case.
But measuring session duration alone isn’t enough. It should always be analysed together with bounce rate to actually understand the performance.
For example, if your session durations are the desired length and the bounce rates are low, that means your chatbot is actually holding meaningful conversations with users. But if the bounce rates are high, it means that your visitors don’t find the conversations helpful and are ending the sessions in frustration.
If you want to know at which times of the day your customers are most frequently consulting your chatbot, then you need to look at the usage distribution by hour metric.
This metric can help you get an idea about how a 24/7 chatbot is enabling you to assist your customers with their queries even at odd hours of the night or day which were previously neglected.
By finding out the most active hours for customer queries, you can even tweak your agent chat support to provide a more comprehensive customer service experience.
Measuring this metric can help you find out how many questions on average does it take in a conversation between your chatbot and visitor for your visitor to get the information they need and make a purchase.
With the data collected in this metric, you can optimize your chatbot and make improvements for a rich Yes
so that it takes fewer questions for your visitors to reach the point of conversion.
The faster your visitors can get their questions answered, the higher will be their satisfaction, making it more likely for them to become repeat customers.
This is one of the most important chatbot metrics because it tells you how effective your chatbot is at successfully meeting the goals that you set for your users to complete.
These goals will depend on what your objective is. For example, if you’re a real estate agent, you would want your chatbot users to give you their contact details so you can reach out to them. Hence, your chatbot’s goal would be to get as many people to fill up a contact form as possible.
If your goal completion rate is high, it means your chatbot is actually helping you get more leads or sales. But if it’s low, it means you need to look at your conversation metrics to troubleshoot the problem.
This is a measure of the average number of messages that are exchanged between your chatbot and a user during a conversation.
Higher interaction rates could mean that your chatbot is engaging your visitors, or it could also mean that it’s taking your visitors longer to receive the information they’re looking for because the chatbot is unable to resolve their queries faster.
That’s why interaction rate should always be held in comparison with other metrics such as bounce rate and goal completion rate to make an informed and accurate analysis.
Just like matched response rate, non-response rate can help you figure out whether your chatbot is able to provide your website visitors a satisfactory response to their queries or not.
Non-response rate measures the number of times your chatbot fails to answer the user’s question. It could be because your chatbot doesn’t have a suitable response to the question being asked, or because it is unable to understand the question at all.
This metric can help you fill the gaps in your chatbot’s conversational abilities by finding out where exactly it’s lacking.
If you know the common queries your customers have, you can program your chatbot to be better equipped in answering those specific questions with specialized answers.
FAQs can help you improve your bot’s overall performance and comprehension by providing you critical data on your target audience’s behaviour and telling you the areas you need to focus on more.
When looking at the frequently asked questions, you should also look at the chatbot conversion rates and customer satisfaction rates to make a proper evaluation on your chatbot’s efficacy.
In your chatbot’s analytics, you’ll be able to figure out the comprehension level of your chatbot.
Every chatbot has a different comprehension level depending on what it’s used for. For example, a chatbot that is built for ecommerce websites cannot comprehend questions of real estate and vice versa.
If your chatbot isn’t able to answer a specific inquiry, it’s either because the question is irrelevant to the use case or your chatbot doesn’t have any knowledge about it and its database must be updated.
This is a measure of the percentage of people who successfully obtain the help they want from the chatbot itself, without reaching out to a human customer support executive.
This metric can help you get an idea about whether your customers are satisfied with the responses they receive from your chatbot or not.
If your chatbot’s self-service rate is low, you need to figure out why exactly your chatbot is unable to give satisfactory responses to the users.
This is one of the most important performance metrics you should keep your eye on because it comes directly from your target audience.
Customer feedback is invaluable because it helps you understand where your chatbot is lacking and make subsequent improvements. You can ask your chatbot users whether they were satisfied with the responses they received from the chatbot or not with a series of questions.
This can help you figure out how effective your chatbot is at customer support and sales, and continually work on making it better in the long term.
This metric tells you the number of sessions that are active simultaneously on your chatbot and is really helpful when it comes to determining the quality of traffic and the popularity of your chatbot.
The average number of open sessions during a given period is a key information that will help you figure out whether your chatbot is actually being used or not by your customers.
If it’s low, then you can tweak your chatbot to focus more on proactive outreach so your customers are compelled to use it.
If you’re trying to reach a specific audience, then this metric can help you figure out the penetration rate for this audience and whether they’re making use of the chatbot to get their queries answered or not.
A chatbot that’s not being put to its intended use is just an empty feature, so it’s imperative you know your customers’ attitude towards your chatbot.
This metric can also help you ascertain whether the traffic you’re bringing in is the right one or not because if wrong people are coming in, they obviously wouldn’t interact with your chatbot or convert at all.
This is an important metric that can tell you how successful your chatbot is at answering customer queries with relevancy.
Human takeovers happen for two primary reasons. It’s either because the chatbot fails to answer the customer query or because the user prefers talking to another human because they have a complex question only a human agent can answer.
If a higher ratio of users opt for a human agent, then you need to figure out why by looking at other user metrics and update your chatbot accordingly.
After you measure all of the above, it is important that your chatbot leads to actual conversions - and at this stage, we mean “sales”.
Always keep a close watch on how it impacts your sales - either on a day to day or weekly, or monthly basis.
As the saying goes, if you cannot measure it, you cannot improve it. Any marketing effort that isn’t measured is a waste of money and conversational marketing is no exception.
To evaluate the success or failure of your chatbot, you need to set actionable goals in place and then decide on the corresponding KPIs that you need to measure.
Chatbot analytics can provide you invaluable insights on not just your bot’s performance and effectiveness but also on how you can better satisfy your customers so you can keep providing them the best customer service experience possible.
That’s why QuickReply.ai comes with an advanced analytics dashboard so you can make sure your conversational marketing efforts are headed in the right direction.
Tool and strategies modern teams need to help their companies grow.
Leverage the untapped growth potential of WhatsApp marketing to acquire and retain customers.
You may assess the efficiency of your chatbot and how well it is being utilized by your target market using quantitative key performance indicators.
The percentage of people who join a chat and then exit without interacting with the chatbot is known as the bounce rate. Always strive to have the lowest bounce rate possible. A high bounce rate indicates that the chatbot is not engaging enough, does not deliver accurate answers, and does not assist users with their needs.
Better customer data analysis. Businesses can examine how well the chatbot performs in terms of successful business outcomes, sales generated, and in-depth insights on how customers interact with the company and what they are requesting with the use of chatbot analytics.
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