Tracking Metrics and KPIs with Conversational AI

Although chatbots have been around for quite some time, it has only been over the past few years that we’ve seen businesses integrate this technology as part of their marketing strategies.

Today’s chatbot-fueled organizations

Although chatbots have been around for quite some time, it has only been over the past few years that we’ve seen businesses integrate this technology as part of their marketing strategies. For example, Deloitte notes that “70 percent of businesses are rapidly leveraging artificial intelligence to change the way they interact with customers dramatically.”

True chatbot-fueled organizations have started to rethink the way that humans and robots can collaborate and interact within working environments. In addition, deploying other cognitive tools and machine learning–supported systems have proven to drive better decision-making and smoother operations within companies. Artificial intelligence (AI) technology is becoming more standardized across industries—making it not just the trend but the table stakes for success.

Chatbot benefits for organizations

The capabilities of chatbots and AI have led many businesses to scale up, providing enhanced external operations and delivering better services to customers. Without a doubt, the introduction of conversational AI chatbots has allowed businesses to take customer communications to the next level by developing meaningful relationships, recognizing what customers want, and offering the right solutions to satisfy their needs.

As chatbots continue to help companies leverage customer service inquiries, internal teams are also discovering more capabilities in which chatbots can help to streamline tasks. In fact, three out of the top five benefits of AI involve helping internal teams enhance their operations and decisions in some way. (See the following chart.)

Likewise, other important benefits that chatbots offer for internal businesses operations include:

- Easy access to information. Many businesses use chatbots to help further train their employees. They can help boost the knowledge that employees have by providing them with easy access to information. They can also be used during training to create conversations so employees can interact with them to stimulate creative thinking.

- Administrative tasks. Since AI bots are available 24/7, businesses can help remote workers with a personal assistance feature. These bots can help schedule meetings, generate emails, and create appointments, giving employees more time for priority projects and other important tasks.

- Human resource assistance. Chatbots can help employees by answering questions regarding internal processes, such as how to request time off, how to send in a timesheet, and more. Chatbots can also collect tax forms, new employee information, certain agreements, and other legal documents, like those required for new hires.

Using chatbot metrics to measure goals

As the chatbot world continues to expand, chatbot creators face critical questions. How will we measure success? And how do we ensure that our approach to development drives successful outcomes?

A simple way to determine the efficacy of your approach is through chatbot analytics, which can help you to measure a bot’s performance in relation to a predefined objective. Simply automating business tasks with an AI chatbot isn’t enough. It’s not just about implementation—it’s also about constantly calibrating the chatbot to achieve your desired goals.

Melanie Longdon, Senior Vice President, Transformation at LivePerson, works with some of the largest businesses in the world to help them optimize their conversational experiences. According to Longdon, it can be useful to set conversational metrics in a larger strategic framework. An example of this kind of thinking is LivePerson’s 4E Framework, which was developed in working with hundreds of leading brands and delivering more than one billion brand-to-consumer conversations. The “4Es” are:

Efficiency: How are resources being applied to meet customer needs?
Effectiveness: How well are consumer intents being fulfilled?
Effort: How well is friction, such as repetition and wait times, being addressed?
Emotion: How do customers feel about interactions during and after their experience?

"We created the “4Es” to help anyone more effectively design and optimize conversational experiences," says Longdon. "By understanding and delivering on a strategic framework like the 4Es, you can select and optimize the metrics that matter most to your conversational experiences.”

Why do chatbot metrics matter?

Analyzing chatbot metrics not only helps to determine your chatbot’s success but also helps to uncover growth opportunities and to develop marketing strategies accordingly.

Some key areas where chatbot analytics are critical include:

Chatbot effectiveness
Assessing how your customers perceive chatbots and how they’re being assisted is key in learning whether your chatbot is contributing to your business objectives.
Customer satisfaction
Learn how the interactions with your chatbot and customers lead to positive impacts on your business brand and voice.
Return on investment (RoI)
Measure the total leads and issues solved by your chatbot that could contribute to sales or visits with less or minimal effort.

After you understand how a chatbot works, you can measure its performance with the help of analytics and metrics. Although KPIs might vary from business to business, the following are common metrics to evaluate a chatbot.

User metrics

Activity volume. Measuring the activity volume of a chatbot requires looking into the number of interactions—from the moment a user asks a simple question to the moment a constructive dialogue takes place. This metric helps you discover whether your chatbot is actually being used by users and whether the number of interactions is increasing or decreasing.

Response volume. This is a concrete indicator of the number of responses your chatbot has answered. When looking at response volume, you also want to evaluate the quality behind each response and whether these responses can be fine-tuned to better address customer inquiries.

Bounce rate. Bounce rate can indicate how useful users find your chatbot. This is measured by the volume of user sessions that were dropped before the chatbot could finalize its final intent. An elevated bounce rate means that your chatbot is not addressing the subjects that matter to your audience, and this can lead to a poor customer experience.

Retention rate. This refers to the proportion of users who have consulted your chatbot on repeated occasions over a given period. Retention rate can indicate the level of relevance and acceptance of your chatbot.

Conversation metrics

Questions per conversation. This indicator helps you determine how many questions your chatbot needs to be asked before it can provide necessary information to its users. The more questions users have to ask, the more time it will take for them to receive the right information.

Human vs. chatbot interactions. Sometimes chatbots are designed with the intent to transfer the user to a human agent to lead to more sales. Other times, humans have to take over the conversation due to repeated chatbot conversation failure. Whichever way the chatbot is set up, you want to make sure that it operates in a way that requires a determined amount of interaction between humans vs. chatbots.
Interaction rate. If you want to measure user engagement during conversations with your chatbot, you definitely want to observe this indicator. It allows you to measure the average number of messages exchanged per conversation.

Non-response rate. This metric measures the number of times your chatbot fails to respond to a question. Such failure may be the result of a lack of content or of your bot’s difficulty in comprehending user inquiries.

Customer satisfaction metrics

Goal completion rate. This captures the percentage of successful engagement through the chatbot. Users will probably try to reach different information or services, like clicking a CTA button or link, filling out a form, and proceeding to make a purchase, among other actions.

Sentiment score. Customers or others engaging with the chatbot can rate their experience to achieve further product excellence. Simple questions like, “Did the bot perform well?” can create more complex evaluation forms to rank and provide points for each different category.

Conclusion

Although this list is not exhaustive and there are many other KPIs to take into consideration when evaluating your chatbot, it’s important to consider these KPIs to help reach your goals and objectives. Therefore, begin by defining an objective or goal, since it becomes the most important step in building a successful chatbot.

. . .

Sources

https://www.revechat.com/blog/chatbot-analytics-metrics/
https://landbot.io/blog/chatbot-metrics-kpi/
https://thechatbot.net/kpis-chatbot-success/
https://research.aimultiple.com/chatbot-analytics/