Demystifying Math: A guide to startup metrics
In this episode of the Prime Venture Partners Podcast, Amit Somani and Shripati Acharya, Managing Partners at Prime Venture Partners, an early-stage VC fund, cover the nuances of metrics at startups.
It is easy to fall into traps that can lead to misleading conclusions from metrics. Metrics shouldn’t lie, they are meant to be an objective view of the business. Metrics are backward as well as forward-looking. They help with monitoring the current health of the business as well as enabling accurate forecasts.
The right way to use TAM
Total Addressable Market or TAM as it is called, helps you to understand the market opportunity. Most entrepreneurs use a simplistic top-down model when describing TAM and that is where they go wrong. Somani and Acharya encourage the audience and young startups to opt for a bottoms-up model instead.
“What’s the ideal customer profile? What is it that the willingness to pay for this is? And what is your ability to address that customer?” Somani then goes on to explain how he would take into consideration the serviceable market segment, the willingness to pay and your ability to reach out to the customer; which will ultimately lead you to acquire that customer.
Put emphasis on customer lifetime value
The objective of LTV is to ascertain how ‘valuable’ a customer is to the business once they start using the service or product. The higher the LTV, the lesser the number of customers the business has to acquire to hit their revenue targets.
LTV (Customer Lifetime Value) is a subject often miscalculated by entrepreneurs. The panellists explain this using the example of a $100 mug that most likely will not get you a repeat order, since it is not consumable and lasts long. In such a case, you as a business need to reacquire the customer.
Solve queries using churn metrics
Churn is arguably the cornerstone of all SaaS businesses. Measured right it can inform impactful product decisions and done wrong can lead to a minefield of product mishaps.
“Churn refers to any customer who is retained in the current period as compared to a comparable previous period. So, if you’re measuring month over month churn, then all customers from last month who are no more customers this month contribute to churn. Similarly, quarter over quarter churn is measured against customers that were paying for the product in the previous quarter vs current quarter. Churn calculations should not include any new customers acquired in the current quarter.”
Think in cohorts
From fashion, travel, to gaming and various other industries, all rely on not just bringing in new customers, but also retaining old clients who will keep contributing to your growth. To meet the customer’s needs, you need to know exactly what they want and how and when they are consuming a product. Thus, it becomes imperative to think in cohorts.
For example, “Time-based cohorts are the most common and usually more useful. I did a particular promotion in a particular month or from a particular channel. What happened or how is that cohort behaving? For instance, you might also look at how a segment, how Android users versus iOS users behave, and so forth,” says Acharya.
Averages hide the truth
“Averages hide the behaviour of the power users versus the naive or new onboarded users versus your typical user. Because average and medians are synonymous when the distribution is uniform or a more normal distribution,” Somani highlights how averages can get extremely misleading.
He further appeals to the founders about the necessity to know where money and engagement are being generated from. “I would say look at the 90th percentile user or the business that you're serving and the 10th percentile user that gives you a true picture.”
Somani and Acharya, in their closing comments, advise to measure, visualise, and capture everything possible. So that when you return to the data you will be able to discover if you missed something. But this also does not mean you get lost in the noise, which is why they suggest picking three to five metrics and focusing on them during a particular stage of a startup.
You can listen to the full episode here
01:30 - Common Pitfalls When Calculating TAM
07:20 - What is a Good TAM from an Investor’s Perspective
09:00 - Calculating TAM for a Category-Creating Company
11:00 - The Right Way to Calculate CAC
18:30 - How to Think About Churn
28:00 - Change the Question from LTV to Payback
30:15 - Revenue, Retention & Cohort Based Analysis
41:00 - Returns, Promotions, Discounts & Refunds
46:00 - Averages Vs Medians
50:00 - Smile Curve for SaaS Companies
Edited by Megha Reddy