Average Cost of Service (ACS)
Average Cost of Service (ACS) is another important SaaS metric for finance to track and to educate the company about. When used in isolation, it doesn’t tell us much. When used in combination with annual recurring revenue (ARR) and customer acquisition costs (CAC) to name a few, it is very powerful. It can help answer questions about pricing effectiveness, margins, and payback.
Excel template can be downloaded below
What is Average Cost of Service (ACS)?
With many SaaS metrics, there are no set definitions or standards. Your company may have a slightly different business model or department structure that will determine how you calculate ACS and make it relevant to your business model.
I calculate ACS using the following components.
- R&D Amortization – the economic cost of your current release(s)
- Technical Support – typically, your call center handling inbound customer questions
- R&D Net of Cap – I look at the expenses in my development cost center and exclude software capitalization. What remains, in my mind, is the cost of software maintenance and supporting current releases. Not new development.
- Account Management – the sales team responsible for taking care of current customers.
- Hosting – your hosting and data center costs.
- Customer Success – I could see this as either an ACS expense or in your Service department and counted in your service margins.
Simply put, I sum up these expenses on an annual basis and divide by customer count to derive ACS.
Taking It Further – Economies of Scale
Once you have ACS, you can run scenarios to determine how your variable and unit costs will change when you add more customers to your cost structure.
Will adding 100 customers drive down your unit costs significantly? Or will it take 1,000 customers? Calculating economies of scale helps me answer these questions and educate the leadership team about our cost structure and the impact of customer growth on our unit costs.
Maybe, your customer growth is great but your cost structure is so bloated that your unit costs are not improving like you thought they would – i.e. insensitive to customer count changes. The Excel model I built helps me understand the balance between cost structure and customer counts.
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