Forecasting is an integral part of any business, especially startups. The only certainty about forecasts is that they will be inaccurate. The goal is to ensure that when the future unfolds, the inaccuracies are more in your favor than against. Revenue forecasts are a crucial starting point, as they form the basis for all other projections. A systematic approach to forecasting and tracking key revenue metrics can significantly improve your chances of success.

Key Drivers and Metrics in Revenue Modeling

A robust revenue model is built on key drivers and metrics. These include annual recurring revenue (ARR), monthly recurring revenue (MRR), and recent month-to-month growth to help create projections of future growth. For e-commerce businesses, Gross Merchandise Volume (GMV) might be more relevant than revenue. For SaaS companies, it’s crucial to clarify how you plan to monetize users. This could be through transaction fees, monthly or yearly subscriptions, listing fees, etc. Any market conditions that affect your revenue model, such as seasonal goods, should also be explained

Understanding Customer and Revenue Traction

Underpinning these figures are key metrics for customer and revenue traction. First, you need to identify your customer distribution channel for your product or service. This could be indirect distribution channels involving wholesalers and/or retailers, or direct distribution channels that sell directly to the consumer. While working on this step, calculate the cost of customer acquisition (CAC), which is used in conjunction with customer lifetime value (CLV) to understand your investment in customer relationship management (CRM).

The Ever-Changing Customer

Remember, “the customer” is not a homogeneous group; it’s a group that’s constantly changing. Your goal is to set up your company in such a way that you can acquire more customers and increase the value derived from each one. This involves keeping people in your store once they’ve entered and turning one-time customers into loyal patrons. These concepts can be quantified. A customer’s lifetime value takes into account the average value of a sale, the number of transactions, and the retention period. Churn rate is the proportion of customers or subscribers who leave a supplier during a given time. As your startup moves from the alpha to beta stage, you can start to see the churn rate and its converse, logo retention.

Insights from Revenue Modeling and Traction Analysis

If done analytically, revenue modeling and traction analysis can provide key insights into the inner workings of your startup. By understanding these aspects, you can make more informed decisions and increase the likelihood of your startup’s success.

This post was written by Jeffrey Camp.