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In this article
High level metrics
Scalability
Metrics are the compass that guides product improvement. They provide objective data on how your product is performing, help you identify areas for improvement, and track the impact of your efforts over time.
High level metrics
Product Market Fit
Unfortunately, many promising ideas fail because they don't meet the needs of the market. The concept of product market fit is fundamental to the startup world. It defines the interaction between the product and the customer. When your customers start selling you your product by sharing their positive experiences with others, it shows true market fit. You need to create a product that people not only love, but that they need and will use daily. This determines the value of the product in the market.
The best way to evaluate a product-market-fit is to ask your current users variety of questions that will help build a detailed understanding of your product's positioning. The Sean Ellis survey is great for this kind of testing.
The Sean Ellis test assesses product-market fit by asking, "How would you feel if you could no longer use the product?". Participants choose from three options: "Very disappointed," "Somewhat disappointed," or "Not disappointed." The test focuses on users who have used the product or service, either once or regularly. If over 40% of respondents answer, "very disappointed", it suggests a product-market fit. However, even a low score doesn't mean failure but indicates areas for improvement. Additional questions can gather insights into adjustments to meet user needs better and improve market fit.
MoM (Month-over-Month) and CMGR (Compound Monthly Growth Rate)
MoM and CMGR scores are metrics used to measure the growth rate of a business or a specific metric overtime. MoM measures the percentage change in a metric from one month to the next. MoM is often used to track the growth of KPIs such as revenue, user acquisition, or user engagement on a month-to-month basis.
MOM Growth % = (Current Month – Previous Month) / Previous Month * 100
CMGR is a measure of the average monthly growth rate of a metric over a specified period if the growth happens at a steady rate each month. CMGR is useful for understanding the overall growth trajectory of a metric over time.
CMGR = (Final Month Value / Initial Month Value) ^ (1 / # of Months) – 1
While MoM and CMGR are valuable metrics for monitoring and analyzing business growth, they should be used with caution in the initial stages of a business or a new product launch due to the low base effect. The low base effect refers to the fact that when a business or product is starting from a small base, even small changes or fluctuations can result in significant percentage increases or decreases. This can lead to misleading interpretations of growth rates and make it difficult to assess the true performance of the business or product.
Instead, in the initial stages, it may be more meaningful to focus on absolute metrics or simpler growth measures that provide a clearer understanding of the business's performance without being skewed by the low base effect. As the business or product matures and the base grows larger, MoM and CMGR scores become more reliable indicators of growth.
Net Dollar Retention (NDR)
NDR is the most important SaaS business metric as it reflects customer retention and the ability to keep existing customers engaged while providing features that help them meet or exceed their goals. NDR helps answer 2 questions:
What growth does a SaaS product deliver without attracting new customers?
How satisfied are existing customers with the value the product provides, reflecting the stickiness of products and value proposition?
NDR = (Starting MRR + Expansion MRR – Contraction MRR – Churn MRR) / Starting MRR
A value greater than 100% indicates that the business has achieved negative churn, meaning that the expansion revenue from existing customers exceeds the revenue lost from churned customers.
NDR is important because it provides insights into the health of a business's customer base. A high NDR indicates that a business is effectively retaining and expanding its customer relationships, which can lead to sustainable growth. Conversely, a low NDR may indicate that a business is struggling to retain customers or is not effectively expanding its relationships with existing customers.
NDR is particularly useful for subscription-based businesses, and other businesses with recurring revenue models. It helps these businesses understand their customer retention and expansion dynamics, identify opportunities for growth within their existing customer base, and make informed decisions to improve customer lifetime value (CLTV) and overall business performance.
MRR (Monthly Recurring Revenue)
MRR is the most important metric for SaaS startups, representing the total amount of revenue a product generates each month. It is calculated by summing up the monthly payments of all customers. For example, if you have 100 users on a Main plan priced at $10 and 20 on a Pro plan priced at $40, your MRR would be MRR = 100 *$10 + 10* $40 = $1,400
LTV (customer lifetime value)
LTV measures the total revenue that should be expected from a customer over the entire time they are engaged with a product. It is a critical metric for assessing the long-term profitability of a business.
LTV is better calculated through cohort analysis to determine which groups stay with the product longer and from which sources they come - the results can be used to draw conclusions about the effectiveness of channels, optimize strategies and budgets.
Identify (select) cohort.
For particular this cohort identify Q1, Q2(median), Q3 MRR quantiles and lifetime expectation (or fact).
COGS include IaaS, 3rd party API, support team billing (except for registration issues).
LTV = (MRR—COGS) x LifeTime (months). If the cohort has a long observation period (usually more than 180 days, but it is case-by-case), you can get LTV through an analytics service. In the end, there are three LTV (Q1, Q2, Q3). The most common is use a median (Q2) LTV.
Vanity metrics
It's important to be cautious of “vanity metrics," which are often non-objective and appear impressive but don't provide meaningful insights into performance or outcomes. Encountering these metrics is common, but it's crucial to recognize that they are not effective for evaluating work. Despite their limited usefulness, it's still valuable to consider them in conjunction with other metrics.
The classic example of vanity metrics are DAU/WAU/MAU (these metrics measure the number of active users per day, week, or month). Differentiating between actionable metrics and vanity metrics involves several key factors:
A metric should prompt action when it changes. If a metric fluctuates without influencing behavior or strategy, it may not be a useful metric.
Metrics should be comparative and relative, providing context for interpretation and enabling comparisons over time or against benchmarks.
By evaluating metrics based on these principles, you can ensure that the metrics you use are meaningful and contribute to informed decision-making.
NSM (North Star Metric)
For thousands of years, Polaris has been an invaluable navigation tool. In business, the Polaris metric was invented to allow organizations to focus on a specific goal. Instead of being distracted by day-to-day business or individual projects, everyone can always determine success by whether they are advancing the company using this metric. Facebook's NSM, for example, is daily active users (DAUs). With more users on the Facebook platform, the team can optimize everyone's feed to bring more value to users.
If two companies have business objectives in generating revenue, then their NSM will not be the size of revenue. That's because revenue metric doesn't give an accurate picture of a company's future. It can be easily manipulated for short-term gains, which can lead to long-term consequences. For example, for a SaaS business, the DAU metric may carry more weight than the MRR metric. Why? Because user engagement is often a better indicator of future revenue streams than current revenue metrics.
North Star metric is a beacon that helps companies stay on course even in the vast sea of business metrics.
Scalability
Rule 40
Rule 40 implies that SaaS startups, whether marginally profitable (or unprofitable), can still be valued at a high operating ratio if their growth rate can offset their burn rate. That is when scaling, the combined value of revenue growth rates and profit margins should exceed 40% for healthy SaaS companies.
Rule 40 = YoY Revenue Growth + EBITDA Margin
Unit-economics
Unit economics helps companies understand the profitability of acquiring and serving customers. It provides answers to questions such as which customer segments, products or channels are most profitable. It helps prioritize resources and investments in those areas that provide the greatest return on investment (ROI). And it definitely helps answer the main question: “Is my company ready for scale?”
There are two main metrics here: CLTV:CAC ratio and CAC payback.
LTV:CAC ratio
Calculate by quantiles through division LTV to the corresponding CAC. The LTV:CAC ratio compares the lifetime value of a customer to the cost of acquiring that customer. 3:1 is considered a good ratio - the business gets 3 times what it spends to acquire the customer. So, the company (channel) is ready to scale up.
CAC payback
CAC payback is the time it takes a business to recoup the cost of acquiring a customer through the revenue generated. A shorter CAC payback period indicates the company can recoup the cost of customer acquisition faster, which can improve cash flow and profitability.
To calculate the LTV:CAC ratio, select a cohort/channel for the one you want to calculate it. And then:
For a selected cohort calculate all marketing expenses as described in allocation rules.
Identify CAC for each LTV quantiles.
Divide LTV to CAC.
When calculating CAC, you should be careful and remember that it isn't an ad budget; it's more about a marketing budget.
CAC = (Direct paid ads for this cohort + Support team billing (cohort) + Sales team billing (cohort)) / (amount of active users in this cohort).
Direct paid ads for this cohort - a budget that was spent to attract this target audience through all paid channels, including influencer marketing.
Support team billing (cohort) is the number of hours spent by the support team (based on data from customer support service) x support hour wages.
Sales team billing (cohort) is the hours spent on conversations with these users by the Sales team (based on data from CRM) x sales hour wages.
Use Pleadcop Unit Ecomonics free tool to calculate and verify your product's unit economics, as well as look at benchmark markets and get a personalized recommendation based on real data. [Link to unit economics tool]
Conclusion
The point of metrics is not to choose metrics for the sake of metrics, but to make informed decisions based on them. Understanding metrics and the concepts they reflect is critical. Knowing how to analyze metrics is a fundamental skill for product leaders. When you encounter complexity or ambiguity in data, it's essential to do thorough research. Many failed startups can attest that failure is not caused by a lack of metrics but by an inability to analyze them effectively.