Chatbots have taken the customer service industry by storm. In fact, experts predict that 90% of customer communications in banks will be automated by 2022. Consumers like chatbots; over 50% of internet users are satisfied with them and 60% of millennials use them regularly to buy basic products online.

However, other reports tell a different story. For instance, a recent survey conducted by NewVoiceMedia shows that 46% of consumers feel chatbots are used to prevent them from reaching a live person. And nearly 43% of consumers say they prefer to deal with a human assistant over a chatbot.

What’s the lesson? When using chatbots, you need to measure their effectiveness. Ask yourself these questions: What do customers think about your chatbot? Are they satisfied with the responses they get? Are they using this tool effectively? Does the chatbot have a positive impact on repeat purchases?

Having the right key performance indicators in place will help you get the answer to those questions.

Measuring the effectiveness of your chatbot is indispensable for tracking the results of using it, identifying any frustrations, and continuously improving its performance.

Five KPIs to Track and Analyze to Determine the Performance of Your Chatbot

Activation Rate

Before measuring the overall performance of your chatbot, you need to first make sure people are using it. The activation rate helps you to determine accurately the extent to which the chatbot option is being selected by customers.

This KPI incorporates multiple metrics, such as the total number of users, the number of customers who open a message sent by a chatbot, and the number of customers who engaged with the chatbot by sending back a message.

Using the activation rate, look at new, active, and engaged users separately on a monthly basis.

By comparing these monthly data sets, you’ll be able to determine the value of your investment and if necessary, find better ways to use the chatbot technology in a more engaging manner.

Volunteer Users

Analyzing the number of customers who interact with a chatbot on their own accord, without waiting for the chatbot to start a conversation, can help you discover customers’ preferences. This shows the success of your branding and marketing efforts.

Volunteer users are crucial; they’re what you want. These are customers who come to your website because they’ve heard about your chatbot and they see its value. These customers are coming in with a real purpose and they’re more engaged.

Retention Rate

Establishing that your customers continue to use your automated channels shows that they find value in the automated interaction.

A retention rate shows the number of customers who revisit your chatbot within a given timeline. This KPI will help you determine if your existing investment in chatbot technology is sustainable. It will also help you see if you should tweak certain aspects of the technology or refine to improve customer experience.

While multiple return visits to your chatbot may suggest that a customer’s issue wasn’t resolved, this could also mean your customers prefer using this channel to others.

By analyzing sentiments and natural language processing like the tone of voice, you can establish why customers are coming back. Also, these AI technologies can help you minimize friction areas and the accompanying customer frustration.

Customer Satisfaction

Any brand using customer service chatbots must measure the impact of this technology on customer satisfaction. The self-serve nature of messaging technology means your support center has limited or no access to the end users’ experience. It isn’t always clear what the customer thinks or feels about their chatbot interaction; this makes the evaluation of customer satisfaction compulsory.

You can achieve this by tracking chatbot errors and confusion triggers. This’ll show problems with the chatbot experience – alongside metrics such as Net Promoter Score (NPS), which is a loyalty metric that measures the possibility of your customers recommending your brand to others. Usually, the higher your customer satisfaction score resulting from a chatbot experience, the higher your NPS will be.

Also, look at common trends among customer complaints logged by your chatbot. And if a question is being asked frequently, take note and focus on resolving its root cause.

Response Time

Nearly 51% of consumers expect a chatbot to deliver instant responses to their questions or requests. Thus, the ultimate metric for chatbot performance is response time.

A good chatbot must process queries quickly and provide instantaneous responses. However, an instant response means nothing to customers if it’s incorrect and doesn’t fully address their issues.

Your goal should be to leverage all tools and technologies in your arsenal to offer a great customer service experience.

While the desire to implement chatbots in the customer journey is undeniable, their implementation shouldn’t be the end if you’re looking to offer excellent customer service. Choosing the right KPIs to track chatbot performance, and taking actionable results where applicable, are crucial steps for ongoing improvement and innovation.

NOTE: I shall continue sharing basic information about chatbot features in the next few series. You may view live demo on how chatbot work by clicking ‘Can I help you‘ featuring myself as a chatbot at the bottom right corner of this page. This demo was created using ConversioBot. If you need more information, please email your enquiry to services@ads.my

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