About This Template
Knowing which metrics to track — and tracking them consistently — is one of the most important disciplines in growth-stage finance. Companies that define their KPIs clearly, populate them monthly, and review them against targets have a measurable advantage in fundraising conversations, board meetings, and operational decision-making. Investors at Series A and B will ask for historical KPI data as a standard part of due diligence; having two years of clean, consistently calculated data in a single view is a powerful signal of financial management quality.
This template provides a complete KPI framework for a growth-stage SaaS or recurring-revenue business. The KPI Dashboard tab is designed as a single-page executive summary showing the current month, prior month, MoM change, YTD average, target, RAG status, and trend indicator for every metric. The Monthly Data tab provides the underlying 24-month data store — January 2024 through December 2025 — from which the Dashboard tab pulls its calculations automatically via cell references.
The template covers twenty metrics across four categories: Revenue and Growth (MRR, ARR, new MRR, expansion MRR, contraction MRR, churned MRR, NRR); Unit Economics (CAC, LTV, LTV:CAC, CAC payback, gross margin, contribution margin); Cash and Burn (cash balance, net burn, gross burn, burn multiple, runway); and Operational (headcount, revenue per FTE, NPS). Each metric includes a precise definition so that anyone reading the dashboard calculates it the same way.
What's Included
- Instructions tab — Overview, metric definitions, and guidance on populating monthly data
- KPI Dashboard tab — Single-page summary view: current month, prior month, MoM %, YTD average, target, RAG status, and trend indicator for all metrics
- Monthly Data tab — 24-month data store (Jan 2024 – Dec 2025) with all metric values; Dashboard tab references these cells automatically
How to Use This Template
- Read the metric definitions carefully before entering any data. The Instructions tab contains the precise calculation for every metric. Where a metric can be calculated multiple ways (particularly NRR, CAC, and LTV), the template has made a specific definitional choice. Ensure your team is aligned on these definitions before populating data — changing definitions mid-series makes historical comparisons meaningless.
- Back-fill historical data first. Start by populating the Monthly Data tab with historical data going back as far as you have clean records. At minimum, aim for 12 months of history. The 24-month structure (Jan 2024 – Dec 2025) is a starting point — extend it as needed by adding columns to the right.
- Enter MRR movements decomposed by category. The Revenue and Growth section requires MRR broken down into: New MRR (new customer acquisitions), Expansion MRR (upsells and cross-sells to existing customers), Contraction MRR (downgrades from existing customers), and Churned MRR (cancellations). Total MRR = Prior month MRR + New + Expansion - Contraction - Churned. If you do not currently track these components separately, begin doing so now — investors at Series A will ask for them.
- Calculate NRR carefully. NRR in this template is calculated on a cohort basis: take the MRR from existing customers at the start of a 12-month period, and measure their MRR at the end of that period (including expansion and contraction, but excluding new customers acquired during the period). An NRR above 100% means existing customers are growing faster than they churn. This is the metric that most clearly signals the strength of product-market fit for a subscription business.
- Enter CAC as a blended figure. CAC in this template is blended: total Sales and Marketing spend in the month divided by new customers acquired in the same month. This is the simplest and most consistent CAC calculation for early-stage companies. More sophisticated payback period modelling using the CAC payback column requires LTV, which is calculated as ACV ÷ gross monthly churn rate.
- Update the Dashboard tab reference month. The Dashboard tab automatically calculates RAG status, MoM change, and trend based on the two most recent months of data. Set the reference month in the Dashboard header to the current reporting month so the calculations pull from the correct columns in the Monthly Data tab.
- Set your targets before the year begins. The Target column in the Dashboard tab should be set at the start of the financial year in the annual budgeting process. Do not change targets mid-year — if you miss a target, record the miss honestly and explain it in the board commentary. Changing targets to avoid reporting a miss destroys the value of the RAG system entirely.
- Use the trend indicator to communicate direction. The Trend column uses an upward arrow, downward arrow, or horizontal arrow to communicate month-on-month direction at a glance. For some metrics (MRR, NRR, gross margin), up is good. For others (net burn, CAC), down is good. The template labels trend direction relative to the metric's target direction.
- Share the dashboard monthly with the board as an attachment to the board pack. The KPI Dashboard tab is designed to be printed or exported as a single page for inclusion in the monthly board pack. If you are using the Board Pack template from CrunchSpark, the KPI Dashboard tab in that template links directly to this one when used alongside it.
- Review and evolve the metrics annually. The KPIs that matter most at seed stage differ from those at Series A and Series B. At seed, MRR growth and gross margin are most important. At Series A, NRR and CAC payback become critical. At Series B, burn multiple and NRR efficiency dominate. Review the dashboard at the start of each financial year and adjust the metrics to reflect what investors at your next fundraising round will scrutinise most.
Frequently Asked Questions
What is the difference between ARR and MRR multiplied by 12?
For most SaaS businesses, ARR and MRR×12 are functionally equivalent — ARR is simply the annualised version of the current MRR run-rate. However, the distinction matters in two cases. First, if you invoice customers annually upfront, ARR should reflect the contracted annual value of all current customers (not MRR×12), because the MRR recognition may differ from the contracted value. Second, if you have customers on multi-year contracts with fixed pricing, ARR should reflect the contracted annual value rather than the average monthly billing. For most early-stage SaaS companies on monthly or simple annual billing, MRR×12 is a reliable proxy for ARR and is what this template uses.
How do I calculate NRR correctly?
NRR (Net Revenue Retention, also called NDR or Net Dollar Retention) measures how much revenue you retain and expand from an existing cohort of customers over a 12-month period, expressed as a percentage. The formula is: NRR = (Starting MRR + Expansion MRR - Contraction MRR - Churned MRR) ÷ Starting MRR × 100, measured over the same cohort of customers. A NRR above 100% means your existing customers are growing in value faster than they churn. For a SaaS company with genuine product-market fit and a land-and-expand motion, NRR of 110-130% is excellent. Below 100% means your existing customer base is shrinking — even without churning customers, the base is declining in value, which makes growth dependent entirely on acquiring new customers.
What metrics do Series A investors focus on most?
At Series A (typically £1-5m ARR), the metrics that investors scrutinise most are: MRR growth rate (both absolute and MoM %); NRR (is the product retaining and expanding revenue from existing customers?); gross margin (is the unit economics defensible?); CAC payback (how long does it take to recoup the cost of acquiring a customer?); and burn multiple (how much cash is being burned to generate each pound of new ARR?). The metrics that get less weight at Series A but become critical at Series B are: LTV:CAC ratio, headcount efficiency (revenue per FTE), and the predictability of the revenue model. A company with strong MRR growth and high NRR will command more interest than one with similar headline growth but poor retention and a high burn multiple.
How should I define and track CAC for a product-led growth company?
For a product-led growth (PLG) company where customers acquire through the product itself (free trial, freemium, self-serve), the traditional blended CAC (sales and marketing spend ÷ new customers) will be artificially low because the product itself is the primary acquisition channel. In this case, it is more useful to calculate two CAC figures: a fully-loaded CAC that includes the cost of the product's free tier (infrastructure cost per free user) and a sales-assisted CAC that applies only to customers who required sales engagement. Many PLG companies also track a "time to value" metric instead of or alongside traditional CAC, since the conversion journey from free to paid is the key variable in their unit economics rather than upfront acquisition cost.
What is a good burn multiple benchmark?
The burn multiple (net burn ÷ net new ARR in the same period) has emerged since 2022 as the primary capital efficiency metric for growth-stage investors. Benchmarks as of 2025: under 1.0x is exceptional, under 1.5x is strong, 1.5-2.0x is acceptable for a company with strong growth, 2.0-3.0x is concerning and will attract investor scrutiny, and above 3.0x makes Series A fundraising at growth valuations very difficult. The burn multiple should be calculated on a rolling three-month average rather than a single month, which can be distorted by timing of large hires or marketing campaigns.
How do I handle metrics I cannot yet calculate accurately?
The honest answer is to leave them blank rather than populate them with approximate figures that will later need to be restated. For example, if you do not yet track MRR by revenue movement category (new, expansion, contraction, churned), do not make up proxy figures — instead, start tracking these from the current month and build the history forward. When presenting the dashboard to investors, be transparent about which metrics have full historical data and which are being tracked from a recent start date. Investors respect financial rigour and honesty about data gaps; they are very sensitive to data that appears precise but turns out to be estimated.
