Triangle Forecasting: Why Traditional Impact Estimates Are Inflated (And How to Fix Them)
Accurate impact estimations can make or break your business case. Yet, despite its importance, most teams use oversimplified calculations that can lead to inflated projections. These shot-in-the-dark numbers not only destroy credibility with stakeholders but can also result in misallocation of resources and failed initiatives. But there’s a better way to forecast effects of gradual […] The post Triangle Forecasting: Why Traditional Impact Estimates Are Inflated (And How to Fix Them) appeared first on Towards Data Science.
Accurate impact estimations can make or break your business case.
Yet, despite its importance, most teams use oversimplified calculations that can lead to inflated projections. These shot-in-the-dark numbers not only destroy credibility with stakeholders but can also result in misallocation of resources and failed initiatives. But there’s a better way to forecast effects of gradual customer acquisition, without requiring messy Excel spreadsheets and formulas that error out.
By the end of this article, you will be able to calculate accurate yearly forecasts and implement a scalable Python solution for Triangle Forecasting.
The Hidden Cost of Inaccurate Forecasts
When asked for annual impact estimations, product teams routinely overestimate impact by applying a one-size-fits-all approach to customer cohorts. Teams frequently opt for a simplistic approach:
Multiply monthly revenue (or any other relevant metric) by twelve to estimate annual impact.
While the calculation is easy, this formula ignores a fundamental premise that applies to most businesses:
Customer acquisition happens gradually throughout the year.
The contribution from all customers to yearly estimates is not equal since later cohorts contribute fewer months of revenue.
Triangle Forecasting can cut projection errors by accounting for effects of customer acquisition timelines.
Let us explore this concept with a basic example. Let’s say you’re launching a new subscription service:
- Monthly subscription fee: $100 per customer
- Monthly customer acquisition target: 100 new customers
- Goal: Calculate total revenue for the year
An oversimplified multiplication suggests a revenue of $1,440,000 in the first year (= 100 new customers/month * 12 months * $100 spent / month * 12 months).
The actual number is only $780,000!
This 46% overestimation is why impact estimations frequently do not pass stakeholders’ sniff test.
Accurate forecasting is not just about mathematics —
It is a tool that helps you build trust and gets your initiatives approved faster without the risk of over-promising and under-delivering.
Moreover, data professionals spend hours building manual forecasts in Excel, which are volatile, can result in formula errors, and are challenging to iterate upon.
Having a standardized, explainable methodology can help simplify this process.
Introducing Triangle Forecasting
Triangle Forecasting is a systematic, mathematical approach to estimate the yearly impact when customers are acquired gradually. It accounts for the fact that incoming customers will contribute differently to the annual impact, depending on when they onboard on to your product.
This method is particularly handy for:
- New Product Launches: When customer acquisition happens over time
- Subscription Revenue Forecasts: For accurate revenue projections for subscription-based products
- Phased Rollouts: For estimating the cumulative impact of gradual rollouts
- Acquisition Planning: For setting realistic monthly acquisition targets to hit annual goals
The “triangle” in Triangle Forecasting refers to the way individual cohort contributions are visualized. A cohort refers to the month in which the customers were acquired. Each bar in the triangle represents a cohort’s contribution to the annual impact. Earlier cohorts have longer bars because they contributed for an extended period.
To calculate the impact of a new initiative, model or feature in the first year :
- For each month (m) of the year:
- Calculate number of customers acquired (Am)
- Calculate average monthly spend/impact per customer (S)
- Calculate remaining months in year (Rm = 13-m)
- Monthly cohort impact = Am × S × Rm
2. Total yearly impact = Sum of all monthly cohort impacts
Building Your First Triangle Forecast
Let’s calculate the actual revenue for our subscription service:
- January: 100 customers × $100 × 12 months = $120,000
- February: 100 customers × $100 × 11 months = $110,000
- March: 100 customers × $100 × 10 months = $100,000
- And so on…
Calculating in Excel, we get:
The total annual revenue equals $780,000— 46% lower than the oversimplified estimate!
