What is cost per resolution and why does AI change everything?

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

What is cost per resolution?

Cost per resolution measures the average cost to your business to resolve each customer query. This metric helps you assess the efficiency and effectiveness of your customer service operations, especially when using technologies like chatbots and AI.

Achieving a low cost per resolution shows you’re efficiently handling customer enquiries while controlling operational costs. In particular, you might be effectively using AI chatbots to address customer queries, reducing the time spent by your human agents on routine tasks, and ultimately giving quicker resolutions to customers.

How do you calculate cost per resolution?

To calculate cost per resolution, divide the total expenses related to resolving customer queries (including hiring the best people and the associated technology and training costs) by the total number of queries resolved in any given period.

In tracking cost per resolution regularly, your teams can identify areas for improvement, set goals for better performance, and allocate resources effectively to improve overall customer satisfaction.

Rethinking cost per resolution strategies to suit the age of AI

Since 2020, chatbot use has doubled, and with large language models (LLMs) like GPT arriving in 2022, AI is no longer an alien buzzword. That means customers are now far happier to accept AI automation can ― and does, resolve their issues. For Legal & General Insurance, even before 2020, 83% of customers using their AI assistant were already turning to it first over traditional methods of contact like phone and email.

What’s great for customers, like the instant responses to their queries at any time of the day or night, on any channel and in any language, is also good for your business, since the cost of a phone call is significantly higher than the cost of an AI assistant response. For that reason, it’s important now to track this shift in enquiry handling, ready to compare your cost per resolution for every enquiry your support teams handle to the cost per resolution for all those your AI assistant deals with.

“The average cost per call is around £5 in the UK and we’ve reduced this to 5p per enquiry with our next-generation AI assistants. Barking & Dagenham Council, for example, worked out they were spending £4.60 on every call coming into their contact centre. In their first six months after the launch of their AI assistant, they saved £48,000 and went on to expand their AI-powered service to five more departments at no extra cost with a ROI of 533%.” ~ Abbie Heslop, Head of Customer Journey at EBI.AI

Dishing up the customer service pie differently

Like many organisations, your telephone communications might currently command the largest piece of what we call the customer service pie, where customer service operations hinge on standard business hours. The problem is, if your support is only active for 8 hours from 9-5, how do you help people for the rest of the 16 hours in a day? Using an AI assistant keeps your support open 24/7 and is a far less expensive ‘pie strategy’.

Rethinking the customer service pie: 80% AI chatbot, 15% live chat, 5% phone

Using an AI assistant is not only about saving money, it’s about saving you valuable time, too. “Having an AI assistant can help reduce the number of enquiries you have overall,” says Aaron Gleeson, Implementation Lead at EBI.AI, “resulting in your support agents having more time to provide a better quality and experience to your customers.”

Calculate your savings

Calculate the cost savings that will be achieved by adding an AI assistant to your website

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25,000+

Move the slider above to match your total customer service load per month (including calls, emails and live chats).
To calculate accurate savings for your business, put your real figures in the boxes below to replace these benchmarks.

your current average cost per enquiry (calls, emails, and live chats)
of enquiries you wish to be handled by your AI assistant (without the need for a call, email or live chat)
your average hourly rate for customer service rep / agent (including costs such as training, equipment, recruitment)

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FAQs

How can AI-driven support channels enhance customer satisfaction?

AI-driven support channels like chatbots and more advanced AI assistants, offer customers instant responses, 24/7 availability, and multichannel support, leading to improved customer satisfaction scores thanks to enhanced customer experiences.

How does AI-driven cost optimisation extend beyond metrics like cost per resolution?

AI-driven cost optimisation means you can explore ways to be innovative in customer service to reduce your costs while enhancing operational efficiency and driving growth. Besides this, you can use AI to improve processes, automate repetitive tasks, and personalise customer chatbot interactions. By embracing AI technologies across various functions, you can unlock new avenues for revenue generation and value creation for long-term sustainability.

What role does AI scalability play in maximising cost efficiencies and performance for businesses?

AI scalability allows seamless expansion of AI solutions to meet growing customer demands and adapt to changing requirements. Using AI, you can efficiently handle increasing volumes of customer queries, optimise resource allocation and enhance your operational agility. You can also improve productivity, and deliver exceptional customer experiences at scale.

How is AI reshaping the concept of cost efficiency in customer service operations?

AI is introducing advanced algorithms and automation tools that optimise resource allocation, enhance productivity, and reduce customer support costs. With AI-driven analytics, businesses can gain real-time insights into cost drivers and identify areas for cost reduction. Transform cost efficiency measurement from a static metric to a dynamic, data-driven process that adapts to your changing business needs and customer expectations, ultimately driving performance improvements and sustainable cost savings.