How do you work out your cost per call (and save money using AI)?

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

What is cost per call?

Cost per call calculates the average expense to your company each time you handle a customer enquiry. It’s crucial for understanding the financial impact of each customer interaction on your business, helping with budgeting decisions and to optimise your operational costs.

By effectively managing and reducing your cost per call, you can improve your financial performance, allocate resources more efficiently, and enhance overall customer service quality, leading to increased customer satisfaction scores and overall loyalty.

How do you calculate cost per call?

Calculating the cost per call involves dividing the total operating expenses related to handling calls, like the cost of hiring support agents, technology costs, and overheads by the total number of calls received. This gives you a clear figure to represent the average cost for each customer call handled by your support teams, but you should also bear in mind, the introduction of an AI assistant will change this completely ― forever.

Rethinking cost per call strategies to suit the age of AI

Customers are now using AI automation tools in droves. Since 2020, chatbot use has doubled, and with large language models (LLMs) like GPT arriving in 2022, AI is no longer an alien buzzword ― everyone’s aware of it. That means your customers are getting more comfortable all the time in using and accepting AI automation because they’re now familiar with it. 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.

All of this means your cost per call is moving from the forefront of your calculations to take on new significance. What’s important now is to compare your cost per call for every enquiry your support teams handle to the cost per enquiry for all those your AI assistant can handle.

“The average cost per call is around £6 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

Calculate your savings

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

Monthly savings
Return on investment (ROI)
0 hours
Equivalent saved resource
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Total calls, emails & live chats
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Total calls, emails & live chats

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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How does AI-driven cost reduction impact customer service quality in the long run?

AI-driven cost reduction strategies not only lower your operational expenses but also elevate customer service quality over time. By using AI technology to optimise overall cost per enquiry, you can enhance service efficiency, improve first response times, and deliver personalised support, which is one of the biggest opportunities for customer service innovation to date. This dual benefit of cost savings and service excellence leads to increased customer satisfaction scores, loyalty, and overall operational effectiveness in your operations.

What are the implications of AI-driven cost per call optimisation on resource allocation in customer service?

The optimisation of cost per call through AI-driven solutions has significant implications for resource allocation in customer service operations. By automating routine enquiries and reducing the cost per call, you can allocate resources more efficiently, streamline work processes, and scale support operations effectively. This strategic resource management means you can enhance service quality, meet customer demands promptly, and achieve a balance between AI and human support to deliver cost-effective and high-quality customer experiences.

Why is it essential for businesses to regularly review and adjust their cost per call strategies in the evolution of AI technology?

You must regularly review and adjust your cost per call strategies to stay competitive, plus meet evolving customer needs. With the increasing adoption of AI assistants in customer service, you’ll need to adapt your cost per call metrics to reflect the impact of AI on operational costs and efficiency. By staying up-to-date with industry trends, technology advancements, and customer preferences, you can optimise your cost per call strategies, drive cost savings, and deliver exceptional customer service experiences that meet changing demands in every market.

How can AI-driven cost optimisation in customer service lead to improved financial performance and customer satisfaction simultaneously?

Using an AI assistant in customer service operations can result in simultaneous improvements in financial performance and customer satisfaction scores. By reducing operational costs through AI automation, you can enhance efficiency, allocate resources effectively, and provide timely support to your customers. This dual impact of cost savings and enhanced service quality leads to higher customer satisfaction levels, increased loyalty, and overall improvements in financial performance for your organisation.