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Glossary · 233 terms

Operating intelligence glossary.

Every metric, formula, and framework operators and founders need to know — from ARR to Rule of 40 to cohort LTV.

Profit Intelligence

Profit Intelligence

95 terms
6

60-Day Repeat Rate

The percentage of customers from a cohort who place a second order within 60 days of their first. The most-used checkpoint in the D2C 30/60/90 cohort series because it balances early-signal speed with meaningful repeat depth. For consumables, healthy 60-day repeat is 15–30%; for apparel, 10–18%. The right window for tactical mid-quarter cohort decisions.

A

Ad-to-Gross-Profit Ratio

The ratio of paid-advertising spend to gross profit dollars in the same period — calculated as ad spend / gross profit. For D2C, healthy ad-to-GP ratio is 0.25–0.50; above 0.70 indicates advertising is consuming most of the gross profit produced. The ratio is the cleanest top-line check on whether advertising is producing affordable customer growth or burning gross-profit dollars at unsustainable rates.

A

aMER (advertising MER)

A variant of <a href="/glossary/mer" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">MER (Marketing Efficiency Ratio)</a> that includes only paid-advertising spend in the denominator — excluding non-advertising marketing costs (content, PR, organic). For D2C, healthy aMER is 3.0–6.0; below 2.5 is concerning. aMER is the cleanest top-line measure of paid-advertising efficiency at the brand level, free of attribution-platform noise.

A

AOV (Average Order Value)

Total revenue divided by the number of orders in a given period. AOV measures how much a customer spends per transaction on average. It is one of three levers that drive revenue — alongside traffic and conversion rate — and directly affects <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> payback, <a href="/glossary/roas" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ROAS</a> thresholds, and unit economics.

A

ARR (Annual Recurring Revenue)

ARR is the total value of recurring subscription revenue normalized to one year. The north-star metric for SaaS companies and the primary input for valuation multiples.

A

ARR Per Employee

Total annualized recurring revenue divided by the number of full-time employees, expressed as a dollar figure. A company with $12M <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> and 60 employees has $200K ARR per employee. It is the most widely used measure of workforce efficiency in SaaS and a key input to <a href="/glossary/burn-multiple" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">burn multiple</a> and capital efficiency analysis.

B

Basket Size

Basket size is the average value or quantity of a single completed order — used interchangeably with <a href="/glossary/aov" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">AOV</a> (when measured in dollars) or with <a href="/glossary/upt-units-per-transaction" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">UPT</a> (when measured in units). The term is genuinely ambiguous; always specify whether you mean basket dollars or basket units. The cleanest pattern is to report all three components: AOV, UPT, and Average Unit Retail.

B

Bessemer Efficiency Score

A SaaS efficiency framework popularised by Bessemer Venture Partners that combines net revenue retention, growth rate, and burn multiple into a single 0–100 score. Top-quartile public SaaS companies score above 60; the median is closer to 35–45. The score is most useful for cross-company peer benchmarking because the methodology is consistent across companies that report it.

B

Blended CAC

Total sales and marketing spend divided by the total number of new customers acquired across all channels in a given period. Blended CAC averages the cost of every acquisition source — paid, organic, referral, and direct — into one number. It is the headline metric for investor reporting but can be misleading for channel allocation decisions.

B

Blended ROAS

Total revenue divided by total advertising spend across all paid channels, without attributing revenue to any single channel. Blended ROAS removes attribution model bias by treating all ad spend as one investment and all revenue as one outcome. It answers whether the total paid media budget is producing an acceptable return.

B

Burn Multiple

Net cash burn divided by net new <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> added in the same period. A burn multiple of 1.5x means the company burned $1.50 for every $1 of new ARR generated. Lower is better. Burn multiple measures capital efficiency — how much cash it costs to generate each incremental dollar of recurring revenue.

C

CAC (Customer Acquisition Cost)

CAC is the total cost of acquiring a new customer — sales, marketing, and overhead — divided by new customers won in the same period.

C

CAC Payback Period

The number of months required to recover the cost of acquiring a customer through the <a href="/glossary/gross-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross margin</a> those customers generate. A 12-month payback means it takes one year of a customer's gross profit to recoup the <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> invested to win them. Shorter payback means faster cash recovery and lower risk.

C

CARR (Committed ARR)

Committed Annual Recurring Revenue — the total annualised value of all signed customer contracts including those not yet active but committed via signed order forms. CARR is typically 3–8% larger than <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> for B2B SaaS because it includes ramp deals, future-start contracts, and signed expansions that haven't taken effect. CARR is the right metric for hiring math; ARR is the right metric for income statement reporting.

C

Cash Conversion Cycle

The number of days between when a company pays its suppliers and when it collects payment from its customers. CCC combines Days Inventory Outstanding, Days Sales Outstanding, and Days Payable Outstanding into a single metric that measures how efficiently a business converts its investments in inventory and operations into cash.

C

Channel Mix

The breakdown of revenue (or customers) across distribution and acquisition channels — DTC vs wholesale vs marketplace, or paid vs organic vs referral, depending on context. The unqualified term is ambiguous and used in two distinct ways: <a href="/glossary/customer-acquisition-mix" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">acquisition channel mix</a> (how new customers come in) and revenue channel mix (where revenue is recognised). Always specify which scope is in use.

C

Churn Rate

The percentage of customers (logo churn) or revenue (revenue churn) lost during a given period, relative to the starting base. Churn is the inverse of retention — it measures how fast a company is losing the customers or revenue it has already earned. For SaaS companies, churn is the single biggest determinant of long-term growth potential.

C

COGS (Cost of Goods Sold)

The direct costs of producing or delivering the goods a company sells, including raw materials, manufacturing, packaging, and shipping. COGS is subtracted from revenue to calculate <a href="/glossary/gross-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross margin</a>. It excludes indirect costs like marketing, sales salaries, and office rent, which belong in operating expenses.

C

Cohort Analysis

A method of grouping customers by a shared characteristic — typically their acquisition date — and tracking their behavior over time. Instead of measuring aggregate metrics across all customers, cohort analysis isolates each group to reveal retention trends, revenue patterns, and <a href="/glossary/customer-lifetime-value" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">lifetime value</a> trajectories that averages obscure.

C

Cohort LTV

The total revenue generated by a group of customers acquired in the same period, divided by the number of customers in that group. Unlike blended LTV, which averages all customers regardless of when they were acquired, cohort LTV shows whether newer customers are worth more or less than older ones over the same lifecycle window.

C

Contraction Revenue

The umbrella metric capturing all recurring revenue lost from existing customers in a defined period. Contraction combines two distinct mechanisms: <a href="/glossary/churn-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">churn revenue</a> (full cancellations where the customer leaves entirely) and <a href="/glossary/downgrade-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">downgrade revenue</a> (partial reductions where customers stay active but reduce tier, seats, or usage). For B2B SaaS, healthy total contraction is below 8–12% of starting ARR annually.

C

Contribution Margin

Revenue minus all variable costs, expressed as a percentage or absolute dollar amount. Contribution margin measures the profitability of a specific product, channel, campaign, or customer segment after deducting every cost that scales with revenue — including <a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a>, ad spend, sales commissions, and variable fulfillment costs. It is the metric that tells operators where money is actually being made.

C

Contribution Margin 1 (CM1)

Revenue minus cost of goods sold (<a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a>), expressed as a dollar amount or percentage. CM1 measures the most basic layer of product profitability before any selling, fulfillment, or marketing costs are deducted. It tells operators whether the product itself generates enough margin to fund the rest of the business.

C

Contribution Margin 3 (CM3)

Revenue minus cost of goods sold, fulfillment costs, and marketing costs. CM3 is the fully-loaded unit margin that shows whether each customer, channel, or product generates profit after all variable costs of acquiring and serving them. It is the metric that determines whether growth is profitable or just expensive.

C

Cost of Customer

A generic term for the total cost of acquiring and serving a single customer — used somewhat ambiguously to mean either <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> alone or CAC plus <a href="/glossary/cost-to-serve" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">cost to serve</a>. The unqualified term reliably causes cross-team confusion. Use 'CAC' for acquisition-only or 'lifetime cost of customer' for the full lifetime cost; reserve 'cost of customer' for retail-conversation contexts where the term is established.

C

Cost to Acquire

Another name for <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC (Customer Acquisition Cost)</a> — the total cost of acquiring a single new customer. The two terms are interchangeable. 'Cost to Acquire' is more common in telecom, financial services, and traditional retail; 'CAC' is dominant in SaaS and D2C. Both refer to the same calculation: total acquisition spend divided by new customers in a period.

C

Cost to Retain

The spend specifically allocated to keeping existing customers — including customer-success retention headcount, retention marketing, loyalty programs, win-back campaigns, and renewal-process tooling. For B2B SaaS, healthy cost to retain is 8–15% of recurring revenue annually; for D2C, 4–10% of customer revenue. Cost to Retain is the third leg of full-lifetime customer cost, alongside <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> and <a href="/glossary/cost-to-serve" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">cost to serve</a>.

C

Cost to Serve

The total operational cost of serving a single customer over a defined period — including support, hosting, fulfilment, payment processing, and CS allocations. For B2B SaaS, healthy annual cost to serve is 8–18% of customer ARR; for D2C, healthy cost per order is 6–14% of order value. Cost to Serve is the operational complement to CAC and a key input to <a href="/glossary/contribution-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">contribution margin</a> per customer.

C

Cross-Sell Revenue

The dollar value of recurring revenue added when an existing customer purchases a different product line, module, or add-on beyond their original purchase. Cross-sell expands the portfolio of products attached to a customer (selling Product B to a Product A customer); <a href="/glossary/upsell-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">upsell</a> expands within an existing product line. Cross-sell typically requires a separate sales touch and produces lower attach rates but higher per-customer ACV when it lands.

C

CRR (Customer Retention Rate)

The percentage of customers retained over a defined period — the inverse of customer churn, calculated as (ending customers from starting cohort) / (starting customer count) × 100. CRR is the customer-count complement to revenue retention. For B2B SaaS, healthy annual CRR is 92%+ for enterprise, 85–92% for mid-market, and 70–85% for SMB. It is closely related to <a href="/glossary/logo-retention" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">logo retention</a>.

C

Customer Acquisition Mix

The breakdown of new customers by acquisition source — paid media, organic search, referral, partner, content, etc. — typically reported as a percentage of new customers per source. Healthy customer acquisition mix is diversified: no single channel above 50% for sustainable D2C, and no single channel above 70% for growth-stage SaaS. Concentrated mixes create channel-dependency risk that is visible in the data months before it manifests as a growth crisis.

C

Customer Lifetime Value (LTV)

The total revenue (or profit) a business expects to earn from a single customer over the entire duration of the relationship. LTV accounts for repeat purchases, subscription renewals, expansions, and upsells. It is the counterweight to <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> — together, they determine whether acquiring a customer creates or destroys value.

D

D2C Unit Economics

The full profit-per-order calculation for a direct-to-consumer business, measured through a layered margin stack: Average Order Value minus Cost of Goods Sold equals <a href="/glossary/contribution-margin-1" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Contribution Margin 1</a>, minus fulfillment and shipping equals CM2, minus customer acquisition cost equals <a href="/glossary/contribution-margin-3" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Contribution Margin 3</a>. Each layer reveals where margin is created or lost.

D

Dollar Churn

The absolute dollar value of recurring revenue lost in a defined period — distinct from <a href="/glossary/gross-churn" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross churn</a> (a percentage) and <a href="/glossary/logo-churn" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">logo churn</a> (a customer count). Most useful when comparing across periods of changing scale or assessing customer-success ROI; especially important above $20M ARR where percentage views obscure absolute dollars at stake.

D

Downgrade Revenue

The recurring revenue lost when an existing customer reduces their commitment without fully cancelling — moving from Pro to Starter, removing seats from a seat-based plan, or stepping down to lower usage tiers. Downgrades are one of two <a href="/glossary/contraction-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">contraction revenue</a> components, alongside cancellation churn. For B2B SaaS, downgrade revenue typically runs 1–3% of starting MRR annually; concentrated downgrades (5%+ annually) signal pricing or value-perception problems.

D

DTC (Direct-to-Consumer)

A business model where a brand sells products directly to end customers through its own channels (website, app, retail stores) without wholesalers, distributors, or third-party retailers. DTC brands own the customer relationship, the transaction data, and the margin that intermediaries would otherwise capture.

E

EBITDA

Earnings Before Interest, Taxes, Depreciation, and Amortization. EBITDA strips out non-operating costs to show how much cash the core business generates from operations. It is the standard profitability measure for comparing companies across different capital structures, tax situations, and accounting methods.

E

EBITDA Margin

The percentage of revenue that remains as earnings before interest, taxes, depreciation, and amortization. Calculated by dividing <a href="/glossary/ebitda" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">EBITDA</a> by total revenue and multiplying by 100. It measures how efficiently a company converts revenue into operating profit, independent of capital structure, tax strategy, and accounting methods.

E

Efficiency Score

A generic term for any composite SaaS efficiency metric — most commonly used to refer to one of several proprietary scoring frameworks (<a href="/glossary/bessemer-efficiency-score" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Bessemer Efficiency Score</a>, <a href="/glossary/rule-of-40" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Rule of 40</a>, magic number, etc.) that combine growth and profitability into a single number. The unqualified term is ambiguous: when reported, the specific scoring methodology must be specified.

F

First Order Profitability

The profit or loss generated on a customer's initial purchase, calculated by subtracting COGS, fulfillment costs, and customer acquisition cost from the first order's average order value. It measures whether a business makes money from day one or relies on repeat purchases to recover acquisition spending.

F

Fully-Loaded CAC

Customer Acquisition Cost calculated to include all expenses contributing to acquisition — paid media, sales and marketing salaries and commissions, GTM tooling, allocated overhead — divided by new customers acquired in the period. Distinct from <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">simple CAC</a> (paid media only). For B2B SaaS, fully-loaded CAC typically runs 2–4× simple CAC. Investors recalculate CAC on a fully-loaded basis during diligence regardless of how a company reports it.

G

GMV (Gross Merchandise Value)

The total dollar value of merchandise sold through a platform or channel over a given period, calculated before returns, discounts, cancellations, and fees are deducted. GMV measures top-line transaction volume. It is not revenue — it is the gross value of all completed sales before any adjustments.

G

Gross Churn

The percentage of recurring revenue lost from existing customers over a period — measured before any expansion is added back. Unlike <a href="/glossary/net-churn" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">net churn</a>, gross churn isolates the impact of cancellations, downgrades, and contraction. For B2B SaaS, healthy gross revenue churn is under 1% per month (12% annualised); top-quartile is under 0.5% monthly.

G

Gross Margin

Revenue minus cost of goods sold (<a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a>), expressed as a percentage of revenue. Gross margin measures how much of every dollar earned remains after the direct costs of delivering the product or service. It is the foundational profitability metric — the starting point before operating expenses, marketing costs, and overhead are considered.

G

Gross Profit

The dollar amount remaining after subtracting cost of goods sold (<a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a>) from total revenue. Gross profit represents the absolute dollars available to cover operating expenses, marketing, R&D, and general overhead. It is the dollar counterpart to <a href="/glossary/gross-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross margin</a>, which expresses the same relationship as a percentage.

G

Growth Efficiency

The umbrella category of SaaS metrics that measure how efficiently a company turns capital and effort into revenue growth — including <a href="/glossary/burn-multiple" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">burn multiple</a>, <a href="/glossary/magic-number" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">magic number</a>, <a href="/glossary/rule-of-40" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Rule of 40</a>, <a href="/glossary/cac-payback-period" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC payback</a>, and <a href="/glossary/ltv-cac-ratio" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">LTV:CAC</a>. No single metric captures growth efficiency completely; mature operators track 3–5 of these together.

I

Incremental ROAS

The revenue generated per additional dollar of ad spend, isolated from revenue that would have occurred without advertising. Measured through holdout tests, geo-lift studies, or matched market experiments, incremental ROAS separates true ad-driven revenue from organic baseline. It answers whether increasing spend actually produces more revenue — or just takes credit for it.

I

Inventory Turnover

A ratio that measures how many times a company sells and replaces its inventory during a given period. Calculated by dividing cost of goods sold by average inventory value. Higher turnover indicates efficient stock management and strong demand. Lower turnover may signal overstocking, weak sales, or obsolescence risk.

L

Landed COGS

Landed COGS (Landed Cost of Goods Sold) is the total cost to deliver a unit of inventory to its destination — including manufacturing cost, freight, duties, customs, and inbound logistics. Landed COGS is typically 1.15–1.40× the manufacturer-quoted unit cost depending on origin and freight terms. For accurate <a href="/glossary/gross-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross margin</a> calculation, landed COGS is the right input — using ex-factory unit cost overstates gross margin by 5–15 points.

L

Logo Churn

The percentage of customers (logos) lost in a defined period, regardless of their contract value. It is the customer-count counterpart to revenue churn — a team that loses 5% of logos but only 1% of revenue is losing small accounts. For B2B SaaS, healthy annual logo churn is under 8% for enterprise, 8–15% for mid-market, and 15–30% for SMB.

L

LTV (Lifetime Value)

The total revenue a business expects to earn from a single customer over the entire duration of the relationship. LTV combines average revenue per customer with retention rate to estimate long-term value. It is the counterpart to <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> — together they determine whether a business model is sustainable.

L

LTV Payback

The number of months it takes for the cumulative gross profit from a customer to equal or exceed the cost of acquiring that customer. Unlike simple <a href="/glossary/cac-payback-period" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC payback</a>, LTV payback accounts for expansion revenue and upsells over the full customer lifetime, not just the initial contract value.

L

LTV:CAC Ratio

<a href="/glossary/customer-lifetime-value" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Customer lifetime value</a> divided by <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">customer acquisition cost</a>, expressing how many dollars of lifetime value each acquisition dollar produces. A 3:1 ratio means $3 of lifetime value for every $1 spent on acquisition. It is the single most important unit economics metric for subscription and recurring revenue businesses.

M

Magic Number

A SaaS efficiency metric that measures how much net new <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> is generated for every dollar spent on sales and marketing. Calculated by dividing the quarter-over-quarter increase in ARR by the prior quarter's S&M spend. A magic number above 0.75 signals efficient growth worth scaling. Below 0.5 signals the go-to-market engine needs optimization.

M

Margin Compression

The gradual decline of profit margins over time, measured as the percentage-point drop in gross margin, contribution margin, or EBITDA margin across consecutive periods. Margin compression signals that costs are growing faster than revenue — or that pricing power is eroding — and typically requires investigation at the channel, product, or customer segment level.

M

Margin Intelligence

Margin intelligence is the practice of calculating gross and contribution margin by channel, segment, SKU, and customer — automatically and continuously — instead of as a quarterly spreadsheet exercise. The point is to catch margin leaks within 7–14 days instead of the typical 60–90.

M

Marketing Mix Modeling (MMM)

A statistical method that uses regression analysis to measure how each marketing channel (paid search, social, email, TV, events) contributes to business outcomes like revenue and leads. MMM works with aggregate data over time, making it privacy-safe and independent of user-level tracking.

M

MER (Marketing Efficiency Ratio)

Total revenue divided by total marketing spend across all channels. MER is a channel-agnostic measure of overall marketing efficiency that avoids the attribution problems inherent in per-channel <a href="/glossary/roas" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ROAS</a>. Instead of asking "which channel drove this sale," MER asks "for every dollar we spent on marketing, how much total revenue did we generate?"

M

MRR (Monthly Recurring Revenue)

The predictable revenue a company earns each month from active subscriptions. MRR normalizes all recurring contracts — monthly, quarterly, and annual — into a single monthly figure. It is the operational heartbeat metric for SaaS companies, used to track growth trends, detect churn, and forecast cash flow.

N

nCAC (New Customer CAC)

The cost of acquiring genuinely new customers — distinct from blended CAC which dilutes the calculation by counting reactivated customers as 'new'. nCAC is the more honest unit-economics view because it isolates the cost of expanding the customer base. For D2C, nCAC typically runs 1.4–2.0× simple paid CAC. Investors increasingly require nCAC reporting alongside blended CAC during fundraising due-diligence.

N

NDR (Net Dollar Retention)

The percentage of recurring revenue retained from existing customers including expansion — mathematically identical to <a href="/glossary/nrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">NRR</a>. 'NDR' and 'NRR' are interchangeable; investor-side firms tend to favour NDR while operator-side companies favour NRR. For B2B SaaS at scale, healthy NDR is 105–120% annually; top-quartile public SaaS exceeds 130%.

N

Net Churn

The percentage of recurring revenue lost from existing customers after subtracting expansion revenue — the inverse of <a href="/glossary/nrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">net revenue retention</a>. Negative net churn (NRR > 100%) means expansion exceeds losses and the customer base grows without new logos. For B2B SaaS at scale, healthy net churn is below 0% (NRR > 100%); top-quartile is below −10%.

N

Net Revenue

The actual revenue a company collects after subtracting returns, refunds, discounts, chargebacks, and allowances from gross revenue. Net revenue reflects the cash a business retains from sales and is the correct starting point for calculating <a href="/glossary/gross-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross margin</a>, <a href="/glossary/contribution-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">contribution margin</a>, and unit economics.

N

Net Revenue Retention

The percentage of recurring revenue retained from existing customers over a period, including expansion (upgrades) and contraction (downgrades and churn). NRR above 100% means the existing customer base grows in revenue without acquiring a single new customer — the strongest indicator of sustainable product-market fit.

N

New Customer ROAS

The ratio of revenue generated by first-time customers to the advertising spend used to acquire them. Unlike <a href="/glossary/blended-roas" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">blended ROAS</a>, which includes returning customer revenue, new customer ROAS isolates acquisition performance. It reveals whether ad dollars are attracting new buyers or subsidizing repeat purchases.

N

NRR (Net Revenue Retention)

The percentage of recurring revenue retained from existing customers over a defined period, after accounting for expansion, contraction, and churn. An NRR above 100% means the company grows from its existing base alone — without acquiring a single new customer. It is the strongest indicator of product-market fit and long-term value.

O

Overhead Allocation

The process of distributing indirect business costs (rent, utilities, administrative salaries, software subscriptions) across departments, products, or revenue streams using a chosen allocation base such as revenue, headcount, or direct labor hours. It converts shared costs into unit-level profitability data operators can act on.

P

Paid CAC

Customer acquisition cost calculated using paid-media spend only — divided by new customers acquired in the same period. The simplest CAC variant and the one most reported in marketing dashboards. For D2C, paid CAC typically runs 40–70% of <a href="/glossary/fully-loaded-cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">fully-loaded CAC</a>. Reporting only paid CAC understates true acquisition cost; pair it with fully-loaded CAC for honest unit economics.

P

Payback on Customer

The time required to recover the cost of acquiring a customer through gross profit produced from that customer. Calculated as <a href="/glossary/cac" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC</a> divided by gross profit per customer per month. For B2B SaaS, healthy payback is 12–18 months; for D2C, healthy is 0–6 months. Mathematically identical to <a href="/glossary/cac-payback-period" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">CAC Payback Period</a>; the term varies by industry convention.

P

Profit Intelligence

The ability to identify which customers, channels, and products are most and least profitable at any point in time. Profit intelligence goes beyond top-line revenue to calculate true <a href="/glossary/contribution-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">contribution margin</a> after variable costs — showing operators where money is actually being made and where it's leaking.

P

Profit Leak

A profit leak is a recurring, often invisible cost that erodes margin without showing up clearly on the P&L — a money-losing channel, a misconfigured discount, an unprofitable customer segment, or an under-attributed cost line. Mid-market operators typically have 2–4 active leaks at any time, each running 60–90 days before detection.

R

Refund Rate

The percentage of orders (or revenue) refunded within a defined period — typically reported as % of orders refunded or % of revenue refunded. For D2C apparel, healthy refund rate is 20–35% (apparel sizing returns); for consumables, 2–6%; for B2B SaaS, 1–4% of new MRR. The metric is the per-order frequency view of returns, while <a href="/glossary/return-margin-impact" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">return margin impact</a> is the dollar-cost view.

R

Rep Productivity

The umbrella category of metrics measuring how much output an individual sales rep produces relative to capacity, time, or cost. It includes <a href="/glossary/revenue-per-rep" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">revenue per rep</a>, <a href="/glossary/quota-attainment" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">quota attainment</a>, deals per rep, pipeline generation per rep, and activity productivity. No single metric captures rep productivity; the framework requires triangulation across 3–5 measures to produce honest assessment.

R

Repeat Purchase Rate (D2C 30/60/90)

The percentage of customers from a starting cohort who place a second order within a defined window — most commonly measured at 30, 60, and 90 days for D2C brands. For consumables, healthy 90-day repeat rate is 25–40%; for durables 5–15%. Repeat purchase rate is the cleanest leading indicator of brand strength and unit-economics health because it forecasts <a href="/glossary/ltv" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">LTV</a> before LTV is realised.

R

Repurchase Rate

The percentage of customers who make at least one additional purchase after their first order within a defined period. Repurchase rate measures the ability of a business to convert first-time buyers into repeat customers — the single most important transition in <a href="/glossary/dtc" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">DTC</a> and e-commerce unit economics.

R

Return Margin Impact

The gross-profit reduction caused by customer returns — including refunded revenue, return-shipping cost, restocking labour, and unsellable returned inventory. For D2C apparel, return margin impact typically runs 8–18% of gross-profit dollars; for non-apparel D2C, 2–6%. The metric is often understated in standard reporting because returned-inventory unsellability and return-shipping costs are tracked in different systems.

R

Return Rate

The percentage of sold units or orders that customers send back within a defined period. Calculated by dividing the number of returns by total orders and multiplying by 100. Return rate directly reduces <a href="/glossary/net-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">net revenue</a> and erodes margin on every channel where it runs above industry norms.

R

Returning Customer ROAS

Return on ad spend computed against revenue from returning (repeat) customers only — distinct from blended ROAS which includes new-customer revenue. For D2C, returning-customer ROAS typically runs 3–8× while new-customer ROAS runs 1.0–2.0×. Reporting only blended ROAS conflates the two and obscures whether spend is acquiring genuinely new customers or just buying back existing ones.

R

Revenue Leakage

The difference between revenue a company should have collected and the revenue it actually collected. Leakage sources include billing errors, failed payment retries, untracked discounts, missed renewal opportunities, and uncaptured upsells. It is expressed as a dollar amount or as a percentage of expected revenue.

R

Revenue per Rep

The annualised revenue produced per fully-ramped sales rep — calculated as total revenue divided by the average number of fully-ramped reps in the period. For B2B SaaS, healthy revenue per rep ranges from $300K (SMB) to $1.5M+ (enterprise). The metric is one of the cleanest measures of sales-productivity efficiency at scale and is closely related to <a href="/glossary/arr-per-employee" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR per employee</a>.

R

Revenue Retention

The percentage of recurring revenue retained from existing customers over a defined period — typically reported as <a href="/glossary/grr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">gross revenue retention</a> (loss only) and <a href="/glossary/nrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">net revenue retention</a> (loss minus expansion). For B2B SaaS at scale, healthy GRR is 88–95% annually and healthy NRR is 105–120%. It is the single most important metric for SaaS valuation.

R

ROAS (Return on Ad Spend)

The revenue generated for every dollar spent on advertising, calculated by dividing ad-attributed revenue by ad spend. A ROAS of 4:1 means $4 in revenue for every $1 spent. ROAS measures the efficiency of paid acquisition channels — not profitability, which requires factoring in <a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a> and <a href="/glossary/contribution-margin" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">contribution margin</a>.

R

Rule of 40

A SaaS benchmark stating that a company's revenue growth rate plus <a href="/glossary/ebitda" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">EBITDA</a> margin (or free cash flow margin) should equal or exceed 40%. A company growing 30% with 15% EBITDA margin scores 45 — healthy. One growing 25% with 10% margin scores 35 — below the threshold. The Rule of 40 balances growth against profitability.

R

Rule of X

An emerging SaaS efficiency framework that varies the canonical <a href="/glossary/rule-of-40" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Rule of 40</a> formula to weight growth more (or less) heavily than profitability. Common variants: Rule of 60 (faster-growth bias), Growth-weighted Rule of 40 (multiplies growth rate by 1.5–2× before summing), and Rule of X with FCF margin. Reflects that growth-stage SaaS often deserves higher growth weighting than the symmetric Rule of 40 implies.

S

SaaS Quick Ratio

The SaaS Quick Ratio (popularised by Mamoon Hamid) measures growth efficiency as (new MRR + expansion MRR) / (churned MRR + contraction MRR) — how many dollars of new and expansion revenue come in for every dollar lost. A Quick Ratio above 4 is healthy; above 8 is excellent. Distinct from the financial-services Quick Ratio (current assets / current liabilities), which measures liquidity.

S

SKU Margin

The profit margin on an individual stock-keeping unit (SKU) — calculated as the selling price minus product-specific costs (COGS, shipping, returns, and allocated ad spend), expressed as a percentage of selling price. SKU margin reveals which specific products make money and which ones erode it.

S

SKU-Level Profitability

The profit or loss generated by a single stock-keeping unit (SKU) after deducting its direct <a href="/glossary/cogs" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">COGS</a> and allocated marketing costs from its revenue. SKU-level profitability reveals which specific products, plans, or line items make money and which ones erode margin — a view that product-line or company-level margins cannot provide.

S

Subscriber Churn (DTC)

The rate at which subscribers to a D2C subscription product cancel or fail to renew — specifically applied to physical-goods D2C brands like consumables, beauty, food, and apparel. DTC subscriber churn is structurally higher than B2B SaaS churn (8–18% monthly is typical) and is driven by inventory accumulation, purchase fatigue, and CAC-channel quality.

S

Subscription Churn

The rate at which subscribers cancel or fail to renew a recurring subscription product — applicable to D2C subscription brands, B2C apps, and consumer SaaS. Unlike B2B SaaS churn (typically measured monthly at low single digits), consumer subscription churn often runs 5–15% monthly because consumer cancellation friction is low and there's no organisational lock-in. The first 30 and 90 days drive most of the lifetime churn outcome.

T

TACOS (Total Advertising Cost of Sale)

The percentage of total revenue spent on advertising across all paid channels. Calculated by dividing total ad spend by total revenue and multiplying by 100. Unlike ACOS, which measures a single channel, TACOS captures the blended efficiency of your entire paid acquisition program against all revenue — including organic.

T

True ROAS

Return on ad spend adjusted for product returns, order cancellations, discounts, and cost of goods sold. While standard <a href="/glossary/roas" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ROAS</a> measures gross revenue per ad dollar, true ROAS measures the actual profit contribution per ad dollar. It is the version of ROAS that reflects what the business kept, not what it invoiced.

U

Unit Economics

The revenue and cost analysis of a single unit of a business — typically one customer, one order, or one subscription. Unit economics measures whether each unit contributes profit, combining metrics like CAC, LTV, LTV:CAC ratio, payback period, and contribution margin per customer.

U

Upsell Revenue

The dollar value of recurring revenue added when an existing customer expands their commitment within the same product line — moving from Starter to Pro, adding seats to an existing seat-based plan, or upgrading to higher usage tiers. Upsell is one of two primary <a href="/glossary/expansion-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">expansion revenue</a> components, alongside <a href="/glossary/cross-sell-revenue" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">cross-sell revenue</a>. For B2B SaaS, healthy upsell-driven expansion contributes 8–15% of starting ARR annually.

U

UPT (Units per Transaction)

UPT (Units per Transaction) is the average number of units in a single completed order — calculated as total units sold divided by total orders. For D2C, healthy UPT is 1.4–2.5 depending on category; for apparel and consumables it is one of the most-managed levers because it compounds with <a href="/glossary/aov" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">AOV</a> directly. UPT growth is achievable through bundling, free-shipping thresholds, and cross-sell merchandising.

W

Working Capital

The difference between a company's current assets (cash, accounts receivable, inventory) and current liabilities (accounts payable, short-term debt, accrued expenses). Working capital measures whether a business has enough liquid resources to cover its short-term obligations and fund day-to-day operations without relying on external financing.

Business Intelligence

Business Intelligence

26 terms
B

Business Intelligence (BI)

Business intelligence turns raw data into reports and dashboards. It tells you what happened — operating intelligence tells you what to do next.

C

CDC (Change Data Capture)

The technique of identifying and tracking changes in source databases — inserts, updates, deletes — and propagating those changes to downstream systems incrementally. CDC enables low-latency, low-load data pipelines compared to full-table scans. Modern CDC tools (Debezium, Fivetran HVR, Airbyte, native AWS DMS / GCP Datastream) read database transaction logs to capture changes without impacting source-system performance. CDC is the backbone of modern <a href="/glossary/elt" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ELT</a> at scale.

D

Data Catalog

A centralised inventory of organisational datasets — typically with metadata (schema, ownership, classification, freshness), documentation (descriptions, business context), and discovery features (search, browse, lineage). Modern data catalogs (Atlan, Castor, OpenMetadata, DataHub, Alation) auto-populate metadata from data systems and turn the catalog into the front door for data discovery. Without a catalog, organisations rapidly accumulate data assets nobody knows exist or how to use.

D

Data Governance

The discipline of policies, standards, and processes that ensure data is managed responsibly — covering quality, security, privacy, access control, retention, and compliance. Modern data governance balances enabling self-service analytics (analysts need access to do their jobs) with regulatory obligations (GDPR, CCPA, HIPAA, SOC 2) and ethical responsibilities (PII protection, bias mitigation, documented decisions). Effective governance is increasingly automated through tooling rather than enforced via manual review.

D

Data Lake

A centralised storage repository for raw structured, semi-structured, and unstructured data at any scale — typically built on cheap object storage (S3, GCS, Azure Blob). Unlike a data warehouse, a data lake stores data in its original format with minimal transformation; schema is applied on read rather than on write. Data lakes were the dominant analytical-storage pattern 2010–20 before being superseded by <a href="/glossary/data-lakehouse" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">data lakehouses</a> for most new builds.

D

Data Lakehouse

A data platform architecture that combines the low-cost storage and flexibility of a <a href="/glossary/data-lake" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">data lake</a> with the schema enforcement and analytical-query performance of a data warehouse. Lakehouses store data in open file formats (Parquet, ORC) on object storage, with a metadata layer (Delta Lake, Apache Iceberg, Apache Hudi) providing ACID transactions, schema evolution, and time-travel queries. The lakehouse pattern emerged 2020–22 and is now the dominant analytical-data architecture for new builds.

D

Data Lineage

The documented path that data takes from its source through transformations to its consumers — what tables produce which downstream tables, what columns flow into which metrics, what reports depend on which models. Lineage is critical for impact analysis (what breaks if I change this?), governance (who has access to what?), debugging (where did this number come from?), and trust (can I rely on this metric?). Modern data-stack tools (dbt, OpenLineage, Datafold, Castor, Monte Carlo) make lineage capture mostly automatic.

D

Data Mart

A subject-area-focused subset of a data warehouse — typically dedicated to a single team, function, or analytical domain (sales mart, finance mart, marketing mart). Marts contain only the data relevant to that domain, modelled for the team's specific reporting needs. Data marts emerged as a way to scale warehouse access without overwhelming general-purpose users with the full dimensional model. The pattern remains relevant today as a logical organisation principle even as physical implementation has shifted.

D

Data Normalization

The process of cleaning and standardizing data from multiple sources so it can be compared and analyzed together. For operating intelligence, normalization covers field mapping, type harmonization, deduplication, and currency standardization across CRM, finance, marketing, and e-commerce systems.

D

Data Product

A productised, well-documented, SLA-backed dataset (or data interface) treated as a product with explicit consumers, ownership, and quality standards. The data-product concept emerged 2020–22 as a response to data-stack chaos: instead of treating analytical datasets as ephemeral by-products of pipelines, treat them as managed products with users, lifecycle, and accountability. Data products are the central concept in data mesh architecture but are widely useful even in centralised data teams.

D

Data Warehouse

A centralized storage system that collects, structures, and stores data from multiple business systems (CRM, ERP, finance, marketing) in a format optimized for querying and analysis. Data warehouses use ETL pipelines to extract, transform, and load data into a consistent schema that supports reporting and dashboards.

D

Dimension Table

A dimension table provides the descriptive context for facts in a dimensional model — the who, what, where, when, why surrounding business events. Dimensions tend to be wide (many descriptive attributes) and short (typically thousands to millions of rows, vs billions for facts). Common dimensions include Customer, Product, Date, Store, Employee, and Geography. Dimensions are the backbone of analytical queries — every BI question is fundamentally a fact aggregated by dimension attributes.

D

Dimensional Modeling

The discipline of designing analytical-database schemas around facts (the events being measured) and dimensions (the context for those events). Popularised by Ralph Kimball in the 1990s, it remains the dominant approach to warehouse and lakehouse schema design. Dimensional models optimise for analytical-query simplicity and performance — distinct from transactional (3NF) modeling which optimises for write performance and update integrity.

E

ELT (Extract, Load, Transform)

The modern data-pipeline pattern where raw data is extracted from sources, loaded into the warehouse first, and then transformed inside the warehouse using SQL-based tools (typically dbt). ELT became dominant in the mid-2010s when cloud warehouses (Snowflake, BigQuery, Redshift) made warehouse-side transformation cheaper and easier than staging-environment transformation. ELT preserves raw data for reprocessing and centralises transformation logic in version-controlled SQL.

E

Embedded Analytics

Analytics capabilities built directly into a software product's interface, so users access dashboards, reports, and data visualizations without leaving the application they already use. Embedded analytics eliminates the context switch between an operational tool and a separate BI platform.

E

ETL (Extract, Transform, Load)

The data-pipeline pattern where data is extracted from source systems, transformed in a staging environment, and then loaded into the target warehouse. ETL was the dominant pattern from the 1990s through the early 2010s, when storage and compute were expensive and transformations needed to happen before data hit the warehouse. Modern data stacks have largely shifted to <a href="/glossary/elt" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ELT</a> (Extract, Load, Transform) — but ETL remains relevant for specific use cases.

F

Fact Table

The central table in a dimensional model — containing the rows that record business events (sales, logins, page views) along with their measures (quantities, dollar amounts, counts). Fact tables are typically tall (millions to billions of rows) and narrow (a small number of foreign keys to dimensions plus a small number of measure columns). Every fact table has a defined grain — the smallest unit of measurement that one row represents.

H

Headless BI

An architectural pattern where the metric definition layer (the 'semantic layer' or 'metric store') is decoupled from the visualization layer — allowing the same metric definitions to power dashboards, embedded analytics, AI assistants, and reverse-ETL workflows. Headless BI emerged 2020–22 as the response to metric-fragmentation in modern data stacks; products in this space include Cube, dbt Semantic Layer, MetricFlow, AtScale, and LookML.

K

KPI Dashboard

A visual display that shows an organization's key performance indicators in real time, combining metrics, trend lines, and status indicators on a single screen. KPI dashboards are designed for at-a-glance monitoring, surfacing whether critical business metrics are on track, off track, or trending in the wrong direction.

M

Metric Layer

Metric layer is a synonym for <a href="/glossary/metric-store" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">metric store</a> and closely related to <a href="/glossary/headless-bi" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">headless BI</a> — referring to the architectural layer that centralises business-metric definitions and exposes them to consumers (dashboards, AI, reverse-ETL, embedded analytics). The terms 'metric layer', 'metric store', 'semantic layer', and 'headless BI' are used interchangeably in the modern data stack vocabulary; specific tools tend to favour specific terms.

M

Metric Store

A centralised system for defining, computing, and serving business metrics — replacing the pattern where the same metric (revenue, customer count, churn) is defined differently in every BI tool, dashboard, and operational system. Metric stores expose definitions via API to any consumer, ensuring metric consistency across the organisation. The category emerged 2020–22 alongside <a href="/glossary/headless-bi" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">headless BI</a>; products in the space include dbt Semantic Layer (MetricFlow), Cube, AtScale, and LookML.

R

Reverse ETL

The data-pipeline pattern that pushes warehouse-modeled data back into operational systems — Salesforce, HubSpot, Marketo, Zendesk, Stripe, ad platforms — so that operational tools can use the curated, joined, dimensionally-modeled views that analytics teams have built. The pattern emerged 2019–22 as the operational-side complement to ELT. Dominant tools are Hightouch and Census; some warehouses (Snowflake) and pipelines (dbt) have native reverse-ETL features.

S

Self-Serve Analytics

A data access model where non-technical users (operators, managers, executives) can explore, query, and visualize business data without relying on an analyst or data team. Self-serve tools typically offer drag-and-drop interfaces, pre-built templates, or natural language queries against a governed data layer.

S

Semantic Layer

A translation layer that sits between a <a href="/glossary/data-warehouse" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">data warehouse</a> and reporting tools, defining business metrics (revenue, churn, margin) in a single place so every dashboard and query uses the same calculation. It governs what terms mean, who can access them, and how they are computed.

S

Snowflake Schema

A dimensional-modeling pattern where dimension tables are normalised into multiple sub-tables — producing a more complex shape than a <a href="/glossary/star-schema" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">star schema</a> but with stricter normalisation. Snowflake schemas save storage at the cost of query complexity and performance. They were more common when storage was expensive; modern columnar warehouses have made the storage savings nearly irrelevant, leaving star schemas as the dominant default.

S

Star Schema

A dimensional-modeling pattern where a central <a href="/glossary/fact-table" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">fact table</a> joins to multiple <a href="/glossary/dimension-table" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">dimension tables</a> in a star-shaped layout, with dimensions kept denormalised for query simplicity. Star schemas are the dominant dimensional pattern in BI and remain the default schema choice for analytical-warehouse design — easier to query, faster than normalised alternatives, and better-supported by BI tools.

Sales Forecasting

Sales Forecasting

15 terms
B

Bottom-Up Forecast

A revenue forecasting method that builds the total number from individual deal-level data. Each opportunity in the pipeline is weighted by its stage probability and expected close date, then aggregated from rep to team to company. The forecast reflects what the pipeline actually contains rather than what a target assumes.

C

Commit Forecast

A revenue projection built from rep and manager judgment about which specific deals will close within a defined period. Deals are categorized into commit (high confidence), best case (moderate confidence), and upside (possible but uncertain). Unlike weighted forecasts, commit forecasts rely on human assessment rather than stage-based probabilities.

D

Deal Slippage

When a deal's close date moves beyond the originally forecasted period without closing. Deal slippage measures the percentage of pipeline that pushes from one period to the next, reducing forecast accuracy and creating revenue shortfalls. It is distinct from deal loss — slipped deals remain active but close later than expected.

F

Forecast Accuracy

<strong>Forecast Accuracy</strong> measures how close a revenue forecast was to actual revenue in a given period. Expressed as a percentage, it quantifies the reliability of your forecasting process. High forecast accuracy means leadership can trust the number for hiring, budgeting, and capacity decisions. Low accuracy means the business is planning on fiction.

F

Forecast Bias

The systematic tendency of a sales forecast to be consistently too high or too low — not random error, but a directional pattern. Positive bias (sandbagging or overcommitment) inflates pipeline; negative bias understates risk. It is distinct from <a href="/glossary/forecast-accuracy" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">forecast accuracy</a>, which measures error magnitude rather than direction.

F

Forecast Confidence

A score or rating that indicates how reliable a revenue forecast is, based on the composition and quality of the underlying pipeline data. Forecast confidence accounts for pipeline coverage, historical close rates, deal velocity, and stage distribution to distinguish between forecasts backed by strong data and those built on assumptions.

M

MAPE (Mean Absolute Percentage Error)

Mean Absolute Percentage Error — the average percentage distance between forecasted and actual values, calculated as the mean of |((Actual − Forecast) / Actual)| × 100 across periods. MAPE is the standard accuracy metric for sales, demand, and revenue forecasts because it is scale-independent — a 12% MAPE means 12% off whether the underlying numbers are $100K or $10M.

P

Pipeline Coverage Ratio

Total pipeline value divided by the revenue target for a given period, expressed as a multiple. A 3:1 ratio means $3 in pipeline for every $1 of quota. Pipeline coverage answers whether there are enough deals in the pipeline to hit target, given historical <a href="/glossary/win-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">win rates</a> and deal progression patterns.

P

Pipeline Health

A composite assessment of how likely a sales pipeline is to convert into closed revenue, based on five signals: coverage ratio, deal velocity, stage distribution, deal aging, and activity recency. Pipeline health distinguishes between a pipeline that will produce revenue and one that looks full but is unlikely to close.

P

Pipeline Velocity

How fast deals move through pipeline stages, expressed as days-per-stage operationally or as the dollars-per-day <a href="/glossary/sales-velocity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales velocity</a> formula financially. Velocity decline always precedes win-rate decline by 1–2 quarters, making it the single best leading indicator for revenue plan risk.

S

Sales Forecast

A time-bound estimate of expected revenue based on current pipeline, historical close rates, and deal progression data. Sales forecasts translate open opportunities into projected revenue for a given period. They differ from revenue projections, which model future growth using assumptions beyond the current pipeline.

U

Unweighted Pipeline

The total dollar value of all open opportunities at face value — without any stage probability, win rate, or confidence adjustment applied. It is the gross pipeline number used for <a href="/glossary/pipeline-coverage-ratio" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">coverage ratio</a> calculations and capacity planning. For forecasting, <a href="/glossary/weighted-pipeline" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">weighted pipeline</a> is the more decision-useful view.

W

WAPE (Weighted Absolute Percentage Error)

A forecast accuracy metric calculated as the sum of absolute errors divided by the sum of actual values — weighting each period by its size rather than averaging period-level percentages. WAPE is the right metric when actual values vary widely (e.g., enterprise SaaS forecasts where a single $2M deal dominates a quarter). It pairs naturally with <a href="/glossary/mape" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">MAPE</a>.

W

Weighted Forecast

A revenue projection method that multiplies each open deal's value by its probability of closing based on pipeline stage. A $100K deal at a stage with 40% historical close rate contributes $40K to the weighted forecast. The method produces a probability-adjusted view of expected revenue.

W

Weighted Pipeline

The total value of open sales opportunities adjusted by each deal's probability of closing, based on its current pipeline stage. A $100K deal at a stage with 40% historical win probability contributes $40K to the weighted pipeline. It provides a probability-adjusted view of expected revenue from active deals.

Revenue Operations

Revenue Operations

55 terms
A

Activation Rate

The percentage of new users or customers who complete a defined set of key actions within a specified time window after sign-up. Activation measures whether new customers reach the "aha moment" — the point where they experience enough product value to become retained users. It is the leading indicator of <a href="/glossary/churn-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">churn</a> and <a href="/glossary/customer-lifetime-value" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">LTV</a>.

A

Average Deal Size

<strong>Average Deal Size</strong> is the mean revenue generated per closed-won deal over a given period. It is calculated by dividing total revenue from closed deals by the number of deals closed. Operators use it to forecast revenue, set quotas, and evaluate whether the sales team is moving upmarket or downmarket over time.

A

Average Sales Cycle

The mean number of calendar days from opportunity creation to closed-won across deals in a defined period. It is one of the four inputs to <a href="/glossary/sales-velocity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales velocity</a> and a leading indicator of pipeline health. For B2B SaaS, healthy ranges are 14–45 days for SMB, 45–90 for mid-market, and 90–180+ for enterprise.

B

BANT Framework

<strong>BANT</strong> is a sales qualification framework that evaluates prospects across four criteria: Budget (can they pay), Authority (can they decide), Need (do they have the problem), and Timeline (when will they act). Sales teams use BANT to prioritize deals and avoid spending cycles on opportunities that will not close.

C

Capacity Planning

The discipline of matching sales hiring, ramp expectations, and quota assignment to a revenue plan — answering the question 'how many fully-ramped reps do we need by which quarter to hit the plan?' Capacity planning is the operating bridge between the financial model and the GTM org chart. Inaccurate capacity planning is the most common cause of revenue plans missing by structural amounts that could have been predicted in January.

C

Closed-Lost Analysis

The structured review of deals that ended in closed-lost — categorising each loss by reason, stage, competitor, ICP, and deal size to produce actionable patterns for product, pricing, and competitive positioning. Done well, it is one of the highest-leverage operating practices for revenue operations; done poorly (single-line CRM 'reason' fields), it produces noise that nobody acts on.

C

Closed-Won Analysis

<strong>Closed-Won Analysis</strong> is the systematic review of deals that reached closed-won status to identify patterns in what made them convert. It examines common attributes — buyer profile, deal size, sales cycle length, touchpoints, and objections handled — to build a repeatable model of what a winning deal looks like.

C

Competitive Loss

The subset of pipeline losses where the deal went to a specific named competitor — distinct from no-decision losses (the prospect chose status quo) and product-fit losses (the prospect chose a different product category). For B2B SaaS, competitive losses typically account for 30–45% of all losses; concentration in one or two competitors is the most actionable competitive-positioning signal available.

C

Connected Data

Data from multiple business systems — CRM, finance, e-commerce, and marketing — unified into a single normalized model for cross-functional analysis. Connected data eliminates manual reconciliation by mapping fields across sources, resolving duplicates, and maintaining a consistent record of revenue, cost, and pipeline activity.

C

CPL (Cost Per Lead)

The total marketing spend divided by the number of leads generated in a given period. CPL measures acquisition efficiency at the top of the funnel. It tells operators how much they pay to get a prospect into the pipeline, before qualification or conversion.

C

CRM Hygiene

<strong>CRM Hygiene</strong> is the ongoing practice of keeping your CRM data accurate, complete, and current. It covers deal stage accuracy, contact completeness, stale deal management, duplicate removal, and field standardization. Poor CRM hygiene corrupts every downstream metric — from pipeline coverage to forecast confidence — because every report is only as reliable as the data it reads.

D

Deal Velocity

<strong>Deal Velocity</strong> measures how fast individual deals progress through each stage of a sales pipeline. Unlike sales velocity, which aggregates portfolio-level throughput, deal velocity isolates the pace of a single opportunity — expressed in average days per stage. It helps operators identify where deals stall and which stages need intervention.

D

Discovery Call

A structured first conversation between a sales rep and a prospective buyer, designed to qualify fit, uncover pain points, and determine whether both parties should continue the sales process. Discovery calls assess budget, authority, need, and timeline before investing further selling time.

E

Expansion Revenue

Additional recurring revenue generated from existing customers through upsells, cross-sells, seat additions, or tier upgrades. Expansion revenue increases <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> without new customer acquisition. When expansion revenue exceeds churned revenue, the company achieves <a href="/glossary/nrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">NRR</a> above 100% — meaning the existing customer base grows without adding a single new logo.

G

GRR (Gross Revenue Retention)

The percentage of recurring revenue retained from existing customers over a period, excluding any expansion or upsell revenue. GRR isolates the impact of churn and contraction to show how well a company holds onto its existing revenue base without relying on growth within accounts.

I

ICP (Ideal Customer Profile)

A documented description of the company type most likely to buy, succeed with, and retain your product. ICP defines firmographic, technographic, and behavioral attributes of best-fit accounts. Unlike buyer personas, ICP describes the organization, not the individual. It is the foundation of <a href="/glossary/revenue-operations" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">revenue operations</a> targeting.

L

Lead-to-Opportunity Rate

The percentage of leads that progress to qualified opportunity stage — calculated as opportunities created / leads in the same period, measured cohort-by-cohort. For B2B SaaS, healthy lead-to-opportunity rate is 8–18% for inbound and 1–4% for outbound. The metric is the central pipeline-conversion diagnostic between marketing-generated demand and sales-pipeline outcomes.

L

Logo Retention

The percentage of customers (logos) retained over a given period, regardless of changes in their contract value. A company that starts a quarter with 200 customers and loses 12 has 94% logo retention. Unlike <a href="/glossary/nrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">net revenue retention</a>, logo retention counts customers, not dollars — making it the clearest measure of product-market fit at the account level.

L

Loss Rate

The percentage of pipeline opportunities that close lost — the contra-metric to <a href="/glossary/win-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">win rate</a>. It measures sales engine inefficiency from the loss side: every percentage point represents pipeline that consumed sales effort but produced no revenue. For B2B SaaS, healthy loss rate runs 50–70% (corresponding to 25–40% win rates). The diagnostic value comes from segmenting losses by reason, stage, and competitor.

M

Marketing Attribution

The process of identifying which marketing channels, campaigns, and touchpoints contribute to a conversion or sale. Attribution assigns credit to specific interactions along the buyer journey, enabling operators to allocate spend toward channels that actually produce revenue — not just clicks.

M

Marketing-Sourced Pipeline

The dollar value of qualified opportunities created where marketing was the original source — typically defined as the first qualified-touch channel before sales engagement. For B2B SaaS at scale, healthy marketing-sourced pipeline is 35–55% of total pipeline build. Distinct from <a href="/glossary/marketing-attribution" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">marketing-attributed</a> pipeline, which assigns fractional credit across all touchpoints.

M

MEDDIC / MEDDPICC

<strong>MEDDIC</strong> is an enterprise sales qualification framework that evaluates six criteria: Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, and Champion. MEDDPICC extends this with Paper Process and Competition. Sales teams use MEDDIC to navigate complex deals with multiple stakeholders and long sales cycles.

M

MQL (Marketing Qualified Lead)

A lead that meets predefined demographic and behavioral criteria set by marketing, indicating a higher likelihood of becoming a customer. MQLs are scored on engagement signals (content downloads, page visits, email interactions) and fit signals (company size, industry, role). MQL is the entry point to the <a href="/glossary/revenue-operations" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">revenue operations</a> funnel.

M

Multi-Threading

<strong>Multi-threading</strong> is the practice of building relationships with multiple stakeholders within a prospect account during a sales deal. It reduces single-point-of-failure risk by ensuring no deal depends on one contact. Sales teams measure it by the number of engaged contacts per opportunity and the stakeholder coverage ratio across the buying committee.

M

Multi-Touch Attribution

<strong>Multi-touch attribution</strong> is a marketing measurement approach that distributes credit for a conversion across every touchpoint in the buyer's journey, rather than assigning all credit to a single interaction. It uses models like linear, time-decay, U-shaped, W-shaped, or data-driven to weight each touchpoint's contribution to revenue.

N

Next-Best Action

A specific, data-informed recommendation identifying the single highest-leverage action an operator or team should take right now. Unlike generic alerts or dashboard notifications, a next-best action names the problem, quantifies the impact, and prescribes a concrete response based on connected operating data.

N

North Star Metric

The single metric that best captures the long-term value a product delivers to customers — used as the central organising goal that all teams orient toward. Originally popularised by Sean Ellis in PLG and consumer SaaS, the North Star is typically a usage-based metric (sessions, sends, transactions) rather than revenue. Famous examples: Slack uses 'Daily Active Teams sending 2,000+ messages'; Airbnb uses 'Nights Booked'; Spotify uses 'Time Spent Listening'.

O

Operating Cadence

The recurring rhythm of meetings, reviews, reports, and decisions that keeps a business aligned on goals, aware of risks, and able to act on changing conditions. A strong operating cadence turns raw data into weekly actions. A weak one turns Monday mornings into a scramble for numbers that are already stale.

O

Operating Dashboard

A single-screen view that aggregates revenue, margin, pipeline, and forecast data from multiple business systems into one unified display for operators. Unlike BI dashboards built for analysts, an operating dashboard is pre-modeled, action-oriented, and designed for weekly operating reviews — not ad-hoc data exploration.

O

Opportunity-to-Close Rate

The percentage of qualified opportunities that result in closed-won deals — calculated as closed-won / total opportunities created, measured cohort-by-cohort. For B2B SaaS, healthy opportunity-to-close rate is 20–35% for SMB, 15–25% for mid-market, and 18–28% for enterprise. The metric is the central diagnostic for sales-stage execution and closely related to <a href="/glossary/win-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">win-rate</a>.

P

Partner-Sourced Pipeline

The dollar value of qualified opportunities created where a partner — channel reseller, technology alliance, system integrator, or co-sell partner — was the original source. It typically converts 30–45% (higher than marketing or sales-sourced) and costs the lowest per qualified opportunity. Healthy share is 5–15% for mid-market SaaS, scaling to 30–45% for channel-led motions.

P

Pipeline Build

The cross-functional activity of generating new qualified pipeline — through SDR outbound, marketing campaigns, partner sourcing, AE prospecting, and customer expansion. <a href="/glossary/pipeline-generation" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">Pipeline generation</a> is the dollar output; pipeline build is the operating discipline that produces it. Effective build has weekly accountability, channel-level targets, and named owners per source.

P

Pipeline Conversion

The percentage of qualified pipeline that converts to closed-won revenue across the full funnel — equivalent to overall win rate measured at the dollar level. For B2B SaaS, healthy pipeline conversion is 20–35% for SMB, 18–28% for mid-market, and 12–22% for enterprise. The metric is more useful as a stage-decomposed view than as a single aggregate number.

P

Pipeline Generation

The dollar value of new qualified opportunities created in a defined period — the top-of-funnel input to every downstream pipeline metric. For B2B SaaS, healthy weekly pipeline generation should equal roughly 25–30% of the next-quarter quota target, building cumulative coverage of 3:1 by quarter start. Generation shortfalls always become forecast shortfalls 1–2 quarters out.

P

Pipeline Hygiene

The ongoing discipline of keeping CRM opportunity data accurate, complete, and current — correct stages, realistic close dates, scrubbed stale deals, removed duplicates, and consistent fields. Poor hygiene corrupts every downstream pipeline metric: forecast accuracy, coverage ratio, win rate, sales velocity. The single biggest forecast-accuracy lever for most B2B SaaS teams is not better forecasting — it's hygiene.

P

PQL (Product Qualified Lead)

A prospect who has demonstrated meaningful product engagement that signals readiness to buy — typically through usage of free or freemium product. Distinct from MQL (Marketing Qualified Lead, based on marketing engagement) and SQL (Sales Qualified Lead, based on sales conversation). PQLs are the central GTM mechanism for product-led growth motions; conversion rates from PQL to paid customer typically run 15–35%, dramatically higher than MQL conversion (3–10%).

P

Product-Led Growth (PLG)

A go-to-market strategy where the product itself is the primary driver of customer acquisition, activation, and expansion. Users sign up, experience value, and convert to paid without requiring sales-led engagement. PLG companies measure success through <a href="/glossary/activation-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">activation rate</a>, self-serve conversion, and product-qualified leads rather than traditional <a href="/glossary/sales-velocity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales velocity</a>.

Q

Quota Attainment

The percentage of a sales rep's quota target that they actually closed in a given period, measured per rep and rolled up to team and company level. For B2B SaaS, healthy company-level attainment is 60–70% — meaning roughly two-thirds of reps hit quota. Below 50%, the issue is usually quota over-assignment or pipeline shortfall, not rep performance.

Q

Quota Capacity

The total quota the sales team can theoretically carry, calculated as (fully ramped reps × per-rep quota) plus partially ramped contributions. It is the central input to revenue planning: a $20M new-business plan with $400K average quota and 65% expected <a href="/glossary/quota-attainment" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">attainment</a> requires roughly 77 fully-ramped reps, not 50.

R

Revenue Attribution

<strong>Revenue Attribution</strong> is the process of connecting closed revenue to the specific marketing and sales activities that influenced the deal. Unlike marketing attribution, which tracks leads and conversions, revenue attribution ties touchpoints directly to actual dollars collected — showing which channels, campaigns, and interactions produce profitable customers.

R

Revenue Intelligence

A category of software that captures, analyzes, and surfaces insights from buyer interactions (calls, emails, meetings) and CRM data to improve forecast accuracy, deal execution, and pipeline visibility. Revenue intelligence automates the data capture that reps forget and surfaces the patterns that spreadsheets miss.

R

Revenue Operations (RevOps)

The strategic alignment of sales, marketing, and customer success operations under a unified data model and process framework. RevOps eliminates silos between go-to-market teams so that pipeline, revenue, and retention data flow into one operating view — giving operators a single source of truth for forecasting, attribution, and resource allocation.

R

RevOps (Revenue Operations)

A business function that aligns sales, marketing, and customer success operations under a single team to drive revenue efficiency. RevOps manages the systems, data, processes, and operating cadence that connect go-to-market teams into a unified revenue engine.

S

SAL (Sales Accepted Lead)

A marketing-generated lead that the sales team has reviewed and accepted as worth contacting — distinct from MQL (which sales hasn't yet accepted) and SQL (which has been qualified through discovery). SAL is the formal handoff checkpoint between marketing and sales. For B2B SaaS, healthy MQL-to-SAL acceptance rate is 40–70%; below 30% signals misalignment between marketing's qualification criteria and sales's accept criteria.

S

Sales Cycle Length

The average number of days from when a sales opportunity is created to when it closes (won or lost). Sales cycle length measures how long the selling process takes and is one of four inputs to <a href="/glossary/sales-velocity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales velocity</a>. Shorter cycles mean faster revenue recognition and lower cost per deal.

S

Sales Productivity

The team- and motion-level umbrella concept measuring how efficiently the sales organisation as a whole produces revenue. It encompasses <a href="/glossary/rep-productivity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">rep productivity</a> plus motion-level factors: rep-to-SDR ratios, AE-to-AM ratios, ramp time, territory design, and tooling effectiveness. Sales productivity diagnosis requires both individual-rep and motion-level views; either alone misses critical signal.

S

Sales Quota

A specific revenue, unit, or activity target assigned to an individual sales rep or team for a defined period, typically monthly or quarterly. Quotas translate company-level <a href="/glossary/revenue-operations" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">revenue operations</a> goals into rep-level accountability. Attainment is measured as actual closed revenue divided by the assigned quota target.

S

Sales Velocity

The speed at which deals move through the pipeline and generate revenue, calculated by multiplying the number of opportunities by average deal value by <a href="/glossary/win-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">win rate</a>, then dividing by <a href="/glossary/sales-cycle-length" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales cycle length</a>. Sales velocity quantifies pipeline throughput in dollars per day — the single metric that connects pipeline activity to revenue output.

S

Sales-Sourced Pipeline

The dollar value of qualified opportunities created where sales was the original source — typically SDR outbound prospecting, AE self-sourced opportunities, and customer-expansion deals identified by account managers. For B2B SaaS at scale, healthy sales-sourced share is 20–35%; enterprise motions skew higher (25–40%) because outbound carries more weight when buying committees are larger.

S

SQL (Sales Qualified Lead)

A lead that has been reviewed and accepted by the sales team as ready for direct engagement. SQLs have met both marketing qualification criteria and sales-specific readiness signals — budget, authority, need, and timeline. SQL is the handoff point between marketing and sales in <a href="/glossary/revenue-operations" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">revenue operations</a>.

S

Stage Conversion Rate

The percentage of opportunities that move from one specific pipeline stage to the next within a defined period — measured per stage, not aggregated. It is the most diagnostic pipeline-health metric because it isolates exactly where deals stall. For B2B SaaS, healthy stage-to-stage conversion sits at 40–60% in early stages and 60–80% in late stages.

S

Subscription Revenue

Recurring income generated from customers who pay on a regular billing cycle (monthly, quarterly, or annually) in exchange for ongoing access to a product or service. Unlike one-time sales, subscription revenue is predictable and compounds over time. It forms the basis of <a href="/glossary/mrr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">MRR</a> and <a href="/glossary/arr" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">ARR</a> calculations.

T

Time to Value (TTV)

The number of days between a customer's sign-up or purchase and the moment they experience their first measurable outcome from the product. A company where new users generate their first report within 3 days has a 3-day TTV. Shorter TTV correlates directly with higher <a href="/glossary/activation-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">activation rates</a>, lower early-stage <a href="/glossary/churn-rate" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">churn</a>, and stronger trial-to-paid conversion.

W

Weekly Revenue Review

The recurring 30–60 minute leadership meeting where the team examines actuals-vs-plan, pipeline movement, forecast confidence, and the next-best operating actions for the coming week. Done well, it is the single highest-leverage operating ritual in a B2B SaaS or D2C company; done poorly, it consumes 4 hours of leadership time every week to confirm what everyone already knew.

W

Win Rate

The percentage of sales opportunities that result in a closed-won deal, calculated by dividing won deals by total resolved opportunities (won + lost) in a given period. Win rate measures sales effectiveness — how well the team converts qualified pipeline into revenue. It is one of four inputs to <a href="/glossary/sales-velocity" class="text-brand-600 underline decoration-brand-200 underline-offset-2 hover:text-brand-700">sales velocity</a>.

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