What is goal completion rate and what’s a good benchmark?

Natalie Smithson
AI enthusiast | Tea addict | Focused on using AI assistants to win the working week

What is goal completion rate?

In customer service automation, goal completion rate measures the efficiency and effectiveness of chatbots and AI tools. Simply put, it shows the percentage of user interactions with a chatbot that successfully achieves the intended goal, like answering a question, resolving an issue, or finishing a transaction.

Understanding and optimising goal completion rate is crucial for customer service teams if you’re looking to enhance operational performance and deliver seamless user experiences.

A high goal completion rate shows your AI chatbot is effectively meeting customer needs, reducing your average response time, and increasing overall customer satisfaction scores. This metric’s success helps you improve operational efficiency, reduce service costs, and encourage greater customer loyalty.

How do you calculate your goal completion rate?

This involves dividing the number of successful goal completions by the total number of customer interactions with the chatbot and then multiplying by 100 to get a percentage. For example, if your AI chatbot successfully resolves 800 out of 1,000 customer interactions, the goal completion rate would be 80%.

Why does the goal completion rate matter?

The goal completion rate directly reflects your chatbot’s ability to meet the needs of your customers efficiently. By focusing on improving this metric, your teams can keep customer chatbot interactions smooth, improve customer engagement levels, and nurture positive relationships with your customers.

What is a good goal completion rate benchmark?

Our AI assistants average a 96% success rate, which means it has understood the request from your customer and been able to answer a query without any input from your contact teams. Many of our AI assistants get much higher, like Legal & General Insurance and Barking & Dagenham Council who both have a 98% success rate, and Mytime Active with 97% to date.

The thing is, AI assistants are starting to do so much more for customer service teams than simply answer routine enquiries ― they perform tasks, carry out transactions, and complete your goals for you. For that reason, you might choose to split out your goal completion rate in future to know your AI assistant is saving your teams time and money, and increasing in value every day. Already, it’s increasingly important to choose an experienced AI provider who can manage these goals and transitions for you as well as provide self-service tools for you to manage them easily yourself as AI-powered tools become more and more commonplace.

“Coop wants to build a level of customer experience that is unparalleled in the Swedish retail marketplace. The work that EBI.AI is doing gives us a tool to build strong relationships with our customers and support them with an important part of their daily life.” ~ Amer Mohammad, Chief Digital Officer for Coop Sweden

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FAQs

Why is tracking customer intent important for improving goal completion rates?

By analysing customer queries, behaviour patterns and feedback, your AI chatbot can be used to better anticipate customer needs, personalise responses, and improve goal achievement. Tracking customer intent also contributes to enhancing your customer satisfaction score.

How can personalisation strategies impact goal completion rates?

Implementing personalised interactions based on individual user preferences, past interactions, and browsing history can significantly impact goal completion rates. By tailoring responses, recommendations, and solutions to specific customer needs, AI chatbots can help you increase customer engagement, build stronger relationships with customers, and drive higher goal completion rates.

What role does continuous training play in maintaining high goal completion rates?

Continuous training for your AI chatbot involves updating and refining it’s knowledge base, language processing capabilities, and problem-solving skills over time (on our platform, this is all automatically done for you). Regularly training your AI chatbot helps you quickly adapt to evolving customer needs, industry trends, and business objectives, so you can maintain high goal completion rates.

How does sentiment analysis contribute to improving goal completion rates?

Sentiment analysis involves analysing user emotions, attitudes, and satisfaction levels expressed during chatbot interactions with customers. By using sentiment analysis, you could gain insights into customer perceptions, identify potential issues or pain points, and tailor responses to improve the overall customer experience. Sentiment analysis data can help optimise goal completion rates by enhancing communication effectiveness.