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Metrics and Financial Definitions
A collection of definitions and calculations for common startup financial terms and metrics for startups.
Active Users (MAU, WAU, DAU, HAU)
The definition for “active users” varies per business. For instance, Facebook defines “active” as a registered user who logged in and visited the site via any device, or as a user who took an action to share content or activity with Facebook friends via 3rd-party sites integrated with Facebook.
The important things to remember when measuring your active users are to: (1) clearly define it; (2) make sure it’s a true representation of “activity” on your platform; and (3) be consistent in applying that definition.
Here are a few other examples for different sites:
- Social Sites: common metrics of measure for activity are MAUs (monthly active users), WAUs (weekly active users), DAUs (daily active users), and HAUs (hourly active users).
- Content Sites: a common measure of active users and activity on all kinds of content-based sites has been “uniques” (monthly unique visitors) and visits (pageviews or sometimes “sessions” is defined as a minimum period of complete activity).
- E-Commerce Sites: these businesses have a much more telling metric — revenue (and gross margin).
Average Revenue Per User (ARPU)
ARPU is defined as total revenue divided by the number of users for a specific time period, typically over a month, quarter, or year. This is a meaningful metric as it demonstrates the value of users on your platform, regardless of whether those users buy subscriptions (such as telecom monthly subscriptions) or click on ads as they consume content.
For pre-revenue companies, investors will often compare the prospects of a company against the known ARPU for established companies. For example, Facebook generated $9.30 ARPU in FY2015Q2 from its U.S. and Canada users.
Bookings are the value of a contract between the company and the customer. It reflects a contractual obligation on the part of the customer to pay the company.
A common mistake is to use bookings and revenue interchangeably, but they aren’t the same thing. In addition, letters of intent and verbal agreements are neither revenue nor bookings.
Burn rate is the rate at which cash is decreasing. Especially in early stage startups, it’s important to know and monitor burn rate as companies fail when they are running out of cash and don’t have enough time left to raise funds or reduce expenses. As a reminder, here’s a simple calculation:
Monthly cash burn = cash balance at the beginning of the year minus cash balance end of the year / 12
It’s also important to measure net burn vs. gross burn:
Net burn [revenues (including all incoming cash you have a high probability of receiving) – gross burn] is the true measure of amount of cash your company is burning every month.
Gross burn on the other hand only looks at your monthly expenses + any other cash outlays.
Investors tend to focus on the net burn to understand how long the money you have left in the bank will last for you to run the company (referred to as your “Runway”, typically in months). They will also take into account the rate at which your revenues and expenses grow as monthly burn may not be a constant number.
Cash flow is the net amount of cash and cash-equivalents moving into and out of a business. Positive cash flow indicates that a company’s liquid assets are increasing, enabling it to settle debts, reinvest in its business, return money to shareholders, pay expenses and provide a buffer against future financial challenges. Negative cash flow indicates that a company’s liquid assets are decreasing.
Net cash flow is distinguished from net income, which includes accounts receivable and other items for which payment has not actually been received. Cash flow is used to assess the quality of a company’s income, that is, how liquid it is, which can indicate whether the company is positioned to remain solvent.
There are all kinds of churn — dollar churn, customer churn, net dollar churn — and there are varying definitions for how churn is measured. For example, some companies measure it on a revenue basis annually, which blends upsells with churn.
Investors look at it the following way:
Monthly unit churn = lost customers/prior month total
Retention by cohort:
Month 1 = 100% of installed base
Latest Month = % of original installed base that are still transacting
It is also important to differentiate between gross churn and net revenue churn —
Gross churn: MRR lost in a given month/MRR at the beginning of the month.
Net churn: (MRR lost minus MRR from upsells) in a given month/MRR at the beginning of the month.
The difference between the two is significant. Gross churn estimates the actual loss to the business, while net revenue churn understates the losses (as it blends upsells with absolute churn).
Customer Acquisition Cost (CAC, Blended CAC)
Customer acquisition cost or CAC should be the full cost of acquiring users, stated on a per-user basis. Unfortunately, CAC metrics come in all shapes and sizes.
One common problem with CAC metrics is failing to include all the costs incurred in user acquisition such as referral fees, credits, or discounts. Another common problem is to calculate CAC as a “blended” cost (including users acquired organically) rather than isolating users acquired through “paid” marketing. While “Blended CAC” [total acquisition cost / total new customers acquired across all channels] isn’t wrong, it doesn’t inform how well your paid campaigns are working and whether they’re profitable.
This is why investors consider paid CAC [total acquisition cost/ new customers acquired through paid marketing] to be more important than blended CAC in evaluating the viability of a business — it informs whether a company can scale up its user acquisition budget profitably.
Customer Lifetime Value (LTV)
Lifetime value is the present value of the future net profit from the customer over the duration of the relationship. It helps determine the long-term value of the customer and how much net value you generate per customer after accounting for customer acquisition costs (CAC).
A common mistake is to estimate the LTV as a present value of revenue or even gross margin of the customer instead of calculating it as the net profit of the customer over the life of the relationship.
Reminder, here’s a way to calculate LTV:
- Revenue per customer (per month) = average order value multiplied by the number of orders.
- Contribution margin per customer (per month) = revenue from customer minus variable costs associated with a customer. Variable costs include selling, administrative and any operational costs associated with serving the customer.
- Avg. lifespan of the customer (in months) = 1 / by your monthly churn.
- LTV = Contribution margin from customer multiplied by the average lifespan of the customer.
Note, if you have only a few months of data, the conservative way to measure LTV is to look at historical value to date. Rather than predicting average lifespan and estimating how the retention curves might look, we prefer to measure 12 month and 24 month LTV.
Cohort analysis breaks down activities/ behavior of groups of users (“cohorts”) over a specific period of time that makes sense for your business — for example, everyone who signed up for your service in the first week of January — and then follows this group of users longer term: Who’s still using your product after 1 month, 3 months, 6 months, and so on?
A good cohort analysis helps reveal how users engage with your product over time. Startup investors especially appreciate this because it helps us gauge how much people really love your product since many startups are pre-revenue and so users may not have voted with their wallets just yet.
Here are the steps for a cohort analysis:
- Pick the right set of metrics rather than a vanity metric (like app downloads)
- Pick the right period for a cohort — this will typically be a day, a week, or a month depending on the business (shorter time periods typically make sense for younger businesses, and longer ones for more mature businesses)
- Period 1 (day, week, or month) — 100% of install base takes some action that is a leading indicator for revenue, such as buying a product, listing a product, sharing a photo, etc.
- Period 2 — calculate the % of install base that is still engaging in that action a week or month later
- Repeat the analysis for every subsequent cohort to see how behavior has evolved over the lifetime of each cohort
The two trends investors like to see in cohort analyses are:
- Stabilization of retention in each cohort after a period such as 6 or 12 months. This means you are retaining your users and that your business is building a progressively larger base of recurring usage.
- Newer cohorts performing progressively better than older cohorts. This typically implies that you are improving your product and its value proposition over time.
Fixed Costs versus Variable Costs
A fixed cost is exactly what it sounds like, a cost that does not change with increases or decreases in the volume of goods or services that are produced by your company. These costs are obviously the easiest to predict and plan for. Rent, salaries, and utilities all usually fall into this category.
Variable costs are just the opposite. They can vary depending on a what a company is producing (such as Amazon Web Services usage), and as a result are much harder to forecast.
Gross margin is expressed as a percentage and represents the percent of total sales revenue that a company keeps after subtracting the cost of producing its goods or services. The higher the percentage, the more the company keeps on each dollar of sales (that will eventually go toward paying its other costs and obligations). In simple terms, if a company’s gross margins are 25 percent, for every dollar of revenue that is generated, the company will retain $0.25 before paying its overhead, which includes salaries, rent, and more.
While top-line bookings growth is super important, investors want to understand how profitable that revenue stream is. Gross profit provides that measure.
What’s included in gross profit may vary by company, but in general, all costs associated with the manufacturing, delivery, and support of a product/service should be included.
Month-over-Month Growth (MoM Growth)
MoM (Month-over-Month) changes in levels expressed with respect to the previous month. It is calculated like so:
(Month X – Month Y numbers/Month X ) x 100 = Percentage Growth
Net Promoter Score (NPS)
Net promoter score is a metric used to gauge customer satisfaction and loyalty to your offering. It is based on asking “How likely is it that you would recommend our company/product/service to a friend or colleague”?
To calculate NPS:
- Ask your customers the above question and let them answer on a 0-to-10 Likert-type scale, with 10 being definitely likely
- % of promoters = number of respondents who ranked 9 or 10, divided by total number of respondents
- % of detractors = number of respondents who ranked ≤ 6, divided by total number of respondents
- NPS = % of promoters minus % of detractors
To state the obvious, the higher the score the better. It indicates satisfied users, and satisfied users are more likely to be retained over time.
Simply put, a product or service has a network effect when it becomes more valuable as more people use it/ devices join it (think of examples like the telephone network, Ethernet, eBay, and Facebook). By increasing engagement and higher margins, network effects are key to helping software companies build a durable moat that insulates them from the competition.
Revenue (Annual Recurring Revenue, Monthly Recurring Revenue)
Revenue is the amount of money that can be recognized according to accounting policy.
Even if it is paid for upfront, usually subscription revenue (“Recurring Revenue”) can only be measured over time as the service is delivered. If more money has been paid that can be recognized, the difference goes into a balance sheet item called “Deferred Revenue”.
Revenue is often calculated as:
ARR (annual recurring revenue) is a measure of revenue components that are recurring in nature. It should exclude one-time (non-recurring) fees and professional service fees.
MRR (monthly recurring revenue): Often, people will multiply one month’s all-in bookings by 12 to get to ARR. Common mistakes with this method include: (1) counting non-recurring fees such as hardware, setup, installation, professional services/ consulting agreements; (2) counting bookings (see #1).
The number of users registered for your service. In most cases, the preferred user metric is active users, which is more indicative of actual product use — and often translates directly to revenue potential over the long term.
There is no one way to measure the retention of your users, but here is a simple one:
Retention Rate = ((CE-CN)/CS)) X 100
CE = number of customers at end of period
CN = number of new customers acquired during period
CS = number of customers at start of period
Retention is important because it typically costs 3-5x more to close a deal with new customers than it does to upsell a current one.
Run Rate (Annualized Run Rate or ARR)
Annualized Run Rate = MRR x 12ARR is annual run-rate of recurring revenue from the current installed base. This is annual recurring revenue for the coming twelve months if you don’t add or churn anything.
ARR is the measure of recurring revenue on an annual basis. It should exclude one-time fees, professional service fees, and any variable usage fees. This is important because in a given month you may recognize more revenue as a result of invoicing one-time services or support, and multiplying that number by 12 could significantly overstate your true ARR potential.
Total Addressable Market (TAM)
TAM is a way to quantify the market size/ opportunity.
The best way to do this is through a “bottom-up analysis”, which takes into account your target customer profile, their willingness to pay for your product or service, and how you will market and sell your product. By contrast, a top-down analysis calculates TAM based on market share and a total market size.
Why do we advocate for the bottom-up approach? Let’s say you’re selling toothbrushes to China. The top-down calculation would go something like this: If I can sell a $1 toothbrush every year to 40% of the people in China, my TAM is 1.36B people x $1/toothbrush x 40% = $540M/year. This analysis not only tends to overstate market size (why 40%?), it completely ignores the difficult (and expensive!) reality of getting your toothbrush into the hands of 540M toothbrush buyers: How would they learn about your product? Where do people buy toothbrushes? What are the alternatives? Meanwhile, the bottoms-up analysis would figure out TAM based on how many toothbrushes you’d sell each day/week/month/year through drugstores, grocery stores, corner mom-and-pop stores, and online stores.
This type of analysis forces you to think about the shape and skillsets of your sales and marketing teams — required to execute on addressing market opportunity — in a far more concrete way.
Unit economics are the direct revenues and costs associated with a particular business model expressed on a per unit basis.
For instance: in a consumer internet company, the unit is a user. The fundamental unit economics in this case are:
Lifetime value (LTV): the amount of revenue a single user generates during the entire duration of their usage of your service.
Customer Acquisition Cost (CAC): How much it costs to acquire a user.
To the extent that LTV exceeds CAC, you have a business. One of the major jobs of an entrepreneur is to understand the levers that impact those unit economics, and figure out ways to create structural advantages that shift them in your favor.
In this example, LTV and CAC are the primary metrics, but they are really the outputs of many other secondary metrics, which are the things you can most easily measure and influence. You can improve LTV by finding ways to increase the amount of money each user spends, or by figuring out how to improve user retention. CAC can be tweaked by optimizing your virality or improving the effectiveness of your online advertising.
Unit Economics are extremely important for startups, because they show (1) that you have a fundamentally sound business, and (2) that your business can scale.
Virality is often measured by the viral coefficient or k-value — how much users of a product get other people to use the product [average number of invitations sent by each existing user * conversion rate of invitation to new user]. The bigger the k-value, the more this spread is happening.
Here’s the basic math behind the k-value [there are some other more nuanced and sophisticated calculations here]:
- Count your current users. Let’s say you have 1,000 users.
- Multiply that count by the average number of invitations that your user base sends out. So if your 1,000 users send an average of 5 invites to their friends, the total number of users invited is 5,000.
- Figure out how many of those invited users took the desired action within a defined period of time. As with all measurements, pick a meaningful metric for this action. For example, app downloads are not a great metric, because someone could easily download your app but never actually launch it. So let’s say you instead count users who register and play the first level of your game, and that comes out to 15% of the people who got invited or 750 people.
- This means you started with 1,000 people and ended up with 1,750 people through this viral loop during your defined time period. The viral coefficient is the number of new people divided by the number of users you started with; in this case, 750/1000 = 0.75.
Anything under 1 is not considered viral; anything above 1 is considered viral. The higher the number, the better, because it means your cost to acquire new customers will be lower than a product with a lower virality coefficient. Now if you can marry that with a high ARPU or lifetime value per customer, you have the beginnings of a great business.See more for