Having one large enterprise client (also known as a "whale") seems to be a great success for a startup in the early stages of development.
Then once it comes time to negotiate a term sheet, suddenly a major veteran contract becomes viewed as more of a weakness than an asset, due to concentration issues.
Both lenders and investors (including potential acquiring companies) will look at how much of the startup's revenue comes from one single client's contract, and discount your valuation accordingly based on the worst-case scenario.
Most startup founders and some (fractional) CFOs typically think of this metric as a static number derived from "backward" calculations.
To arrive at the customer concentration ratio, most (if not all) founders will usually do a "quick web search" for a generic formula, divide a customer's invoice total by the total revenue generated by the company and place a % figure on a presentation slide.
This methodology will likely not hold up under due diligence scrutiny.
A true financial model requires that an analyst conducts a forward-looking risk assessment, pipeline weighting and scenario-based runway impact modelling.
To accurately assess your startup's customer concentration risk, you need to build a dynamic, board-ready Customer Concentration Analysis into your Financial Model.
Below you will find a condensed summary of the behind-the-scenes calculations to determine customer concentration risk.
Summary of customer concentration risk
Before you begin building the underlying spreadsheet logic, you need to get a clear understanding of how your customers' concentrations risks signal to the market.
Customer concentration risk is the percentage of total revenue for the company (in dollars) that comes from a small number of customers.
If the company has a high concentration of customers, a single churn event could significantly shorten the company's cash runway and lead to a negative impact on the company's venture debt covenants.
Additionally, it could also significantly decrease the likelihood of the company being able to successfully raise additional capital.
In order to build a reliable model to measure customer concentration risk, an analyst needs to identify and build four layers of customer concentrations into the model.
The first layer is the total revenue generated from a single customer.
The second layer is the cumulative revenue generated from the top three to five customers.
Renewal risk, based on the health of your contract, is the third aspect of your model.
The last requirement of your model is to identify the exact scenario loss for the startup’s operating cash flow.
How most startups miscalculate the math
When searching for guidance on this topic, you will find numerous references to basic calculations and the ubiquitous warning to ‘diversify your client base.’
However, you will rarely see a guide that focuses on how to incorporate these calculations into a forecast.
This lack of a clear path leads to two significant errors in financial forecasting for many startups.
Invoicing history vs. forecasted ARR
The majority of founders gauge their exposure to risk based on the recognized revenue or invoices paid over the previous twelve months (trailing twelve months or TTM).
When considering SaaS (Software as a Service) and other subscription revenue models, this is a flawed methodology.
In all cases, historic revenue will include chargebacks for implementation, one-off consulting fees, and contracts that are already churning, which all lead to additional distortions of potential future volatility.
When creating financial models, it is critical that you evaluate the exposure by utilizing only the CURRENT Annual Recurring Revenue (ARR) and contracted future revenue and removing any and all instances of non-recurring revenue.
The funding narrative Gap
Risk metrics are not assessed in a vacuum.
Investors link these metrics directly to a valuation of your company.
If a venture-backed Series B company, for example, had 35% of its ARR from two enterprise-level contracts, the investor (venture capital firm) will generally create a model to account for the possibility that both of those contracts may churn.
If the startup will not be able to survive such a churn event without additional funding (i.e., bridge round), then the risk associated with this potential scenario becomes heightened.
Consequently, the terms of the investment will reflect these heightened risk feeds — i.e., harsher terms, lower valuations, requirements for immediate diversification of the company’s sales pipeline.
How to assess startup financial model customer concentration risk
In order to develop a customer concentration risk calculator in a spreadsheet, it is important to develop a tracked formula that can grow with the business as it transitions from a few beta users to hundreds of paying customers.
A founder/financial analyst should organize their calculations into layers within Excel or Google Sheets.
Layer 1 - One customer concentration rate
This layer is used to determine the greatest risk associated with having a single customer.
To calculate the concentration of a customer, the annualized recurring revenue (ARR) of the customer should be divided by the company's total ARR.
So, if your company has an ARR of $2,500,000 with your biggest customer representing $500,000, the concentration of that customer is 20%.
In the financial model, this number should be dynamic and automatically update as you change MRR schedules.
Layer 2 - Concentration rate of top customers combined
Investors will likely not only pay attention to your most significant customer.
They want to know what percentage of your total accounts are included when you consider the ARR of all of the top three and top five customers.
In your spreadsheet, create another row that will allow for you to add the ARR of your top three customers and the top five customers together, and divide both totals by your total ARR.
For example, a company can have a risk concentration of 12% with one customer but can also have a combined concentration with the top 5 customers of 60%.
If that company continues to have growth from their long-tail customers and the cumulative top five concentration continues to grow at a faster rate than the individual whale customer, it shows growth within their board.
Layer 3 - Risks associated with future renewal
Basic calculators cannot provide a complete view of how to analyse future revenues to identify Risks with your start up; and they also do not provide a complete view of how to use Risk Modifiers.
All revenue concentrations are not as risky as one another.
An example would be that if your % revenue concentration from a particular client is 20%, but the contract is for multiple years & they pay you an entire year up front, then that is very different than having a 20% concentration from your top client on a month to month agreement.
Add a Risk Modifier column to your existing model.
Create a “Renewal Probability” for each Top Account based upon the account duration of their contract, contract renewal probability, and usage activity metrics; AND, then multiply a customer’s annual recurring revenue (ARR) percentage share by their churn probability to determine the expected annual revenue at risk.
Layer 4 - Business loss from scenarios
Concentration percentages are meaningless if you cannot answer one critical question; what happens to your business when your top client stops doing business with you?
Incorporate a toggle option into your Forecast Model, which will allow you to input a potential churn scenario for your number one client.
When you activate this toggle option, the model will automatically calculate and provide the following metrics; a decrease in Gross Margin, an increase in Monthly Cash Burn Rate, and a reduction in your Cash Runway (monthly runway to reach profitability).
By demonstrating the potential negative impacts of key account churn to your Investors, it proves to them that you are mitigating this risk, and not just enabling it to passively affect your business.
Creating your financial forecasting logic
When working through the logic required to build a working financial model, you need to start creating your Financial Forecast based upon different scenarios.
Creating a Projection based on Base, Down Side, or Investor Cases are standard best practice for Financial Planning.
An accurate Financial Forecast will be difficult to create with Mix and Match data from your CRM system; therefore, you will need to identify Recurring Software Revenue only and remove any associated One Time Implementation Fee Amounts.
Base case
To establish a Base Case, you should take into account a startup's regular operation.
This should come directly from a startup's billing system or customer relationship management (CRM) software.
The customer data should include a detailed list of the ten to fifteen biggest customers as they exist at the moment, including their current ARR, historical growth and renewal dates.
Smaller customers can be aggregated into one single line item because of the many customers in that category (known as “the long tail”).
Under the Base Case, a startup would apply the same historical churn percentage across the board.
Downside scenario
The Downside Scenario is the stress test.
For the Downside Scenario, you would manually force the churn of the two biggest customers at their next available renewal date.
Then, you would strip this projected revenue from the ARR waterfall.
You’ll then see how this impacts your cash flow statement, and if this churn requires your startup to either lay off employees or raise emergency capital, you will want to know this is a serious concentration risk.
This exercise will clearly identify where expenses need to be cut should a major customer be lost.
The investor case
The Investor Case is about being clear when sending a model to a data room.
Provide a separate “Risk and Concentration” summary tab, and show the percentage of ARR from the single biggest customer along with the percentage of ARR from the top five biggest customers as well as the expected cash runway and the overall expected churn rate.
Use a waterfall chart to illustrate how the concentration risk is projected to be reduced in the next 18 months as a result of closing new mid-market deals.
Take control of the message before an investor even asks the question.
Stage-dependent thresholds: Red flags and benchmarks
A common flaw in financial advisory documents is to treat all startups equally and not consider their different stages of development.
Thirty percent (30%) is a concentration risk at Seed and Series C.
Benchmarks tend to be used as heuristics but are not rigidly defined.
However, most in a given market will agree that the following are indicative of "critical boundaries" to stay within.
Seed stage context
Funding at the Seed stage with a high concentration of customers was expected.
A startup that has only been in business for a short period (less than 8 months) can often consider it a success to have secured one large enterprise pilot program.
It is not surprising to find that in the Seed stage, having one customer that represents 30%–40% of total revenue is common practice/acceptable to early-stage venture capitalists.
During this stage, the objective is not to punish the startup for having such a concentration but to evaluate the startup's strategy for expanding its customer base.
Series A to B expectations
When moving to Series A, the story changes completely.
At this stage, the company should be achieving its product-market fit and establishing a viable and repeatable sales process.
If a single customer represents more than 20% of the company's total revenue or if the top 5 customers account for more than 40% of total revenue, the company should view this as an issue.
Future investors at Series B will value the company lower if the company's customer concentration exceeds the aforementioned thresholds.
They will be looking for evidence that the sales team is successfully closing diverse accounts instead of depending on the founder's network of initial customers.
Growth stage (Series C, etc.)
At the Growth Stage, the expectation of predictability is paramount.
At this point, private equity firms and other late-stage financing sources become more active.
For a Series C company that is close to breakeven or is preparing to go public, a single customer that makes up over 10% of total revenue is viewed very negatively by investors.
The overall percentage made up by the top five customers should not be greater than 25%.
If a business exceeds either of these thresholds, it may be perceived by investors as a custom development company rather than being a highly scalable software platform.
Mitigating the impact on valuation
If your company's model shows that it has extremely high customer concentration, your first reaction may be to panic.
Instead, focus on making operational changes and developing a strong financial narrative to address the issue.
Because you cannot simply tell your sales team to quit selling to large clients (which would reduce growth potential) but rather, you should work to quickly gain a large number of small to mid-sized clients to dilute the large client's share of the total revenue.
Additionally, work with your largest clients to re-negotiate the contract terms in exchange for small discounts (5-10%) for locking in long-term contracts (36+ months).
Investors will be much more comfortable with a company that has a 25% customer concentration when that 25% of the revenue comes from a three-year locked contract.
Evaluate the risk.
Model the downside.
Control the story.
Frequently asked questions
Does customer concentration ruin a startup's valuation immediately?
No, concentration does not guarantee a low valuation.
However, it makes raising capital a significant challenge for companies with high concentrations because investors will apply a discount for the level of risk associated with customers with concentrated revenues.
Buyers and investors will typically exclude a portion of revenues related to concentrated clients in their valuation multiples or will bundle a large percentage of the revenue into a heavily contingent earnout that is tied to those concentrated customers renewing their contracts.
Should I use the total contract value (TCV) or annual recurring revenue (ARR) when determining customer concentration?
You should always use ARR or the annualized run rate for recurring revenue business models when calculating customer concentration.
TCV can be very misleading given that a one-off five-year deal could create an extremely low average monthly revenue rate.
If your business is a transaction-based or project-based startup, you might want to consider using the trailing twelve months of recognized revenue but exclude any one-offs or abnormal spikes.
How often should a CFO review customer concentration risk analysis?
CFOs should review customer concentration risk analysis continuously, as opposed to just once as a static calculation.
As such, high-growth startups should review their customer concentration metrics each month, along with other common SaaS metrics, such as Net Revenue Retention (NRR) and gross churn.
CFOs should perform a full update and stress test to customer concentration analysis before every board meeting and at the start of every fundraising or debt negotiation.
Is it possible to use the Herfindahl-Hirschman Index (HHI) when analyzing a startup's customer concentration?
Yes.
Although the traditional quick customer concentration calculations are based on both the largest customer and the largest five customers, HHI calculations can also be very effective for internal deep-dive analysis of a startup's customer base.
HHI calculations square each customer's market share and sum them to come up with an overall market share.
The squared portion of the calculation adds significant weight to any large outliers in comparison to smaller customers.
Overall, HHI is a highly effective way for startups to evaluate their overall customer diversification and risk beyond just the top five customers.
