Sales Metrics Glossary

The probabilities should come from your historical win rates per stage, not gut feelings. Pull actuals from your CRM quarterly and recalibrate.

If your win rate is 25%, you need at least a 4:1 coverage ratio just to hit target. Build coverage floors based on actual win rate, not industry benchmarks.

Run this by rep, not just by team. One rep dragging down a specific stage conversion usually signals a skill gap or a bad qualification habit.

ADS dropping over time isn't always bad — could be a volume play. The real question is whether revenue × margin is trending correctly.

Use median, not mean. One 18-month outlier will destroy an average that otherwise looks healthy. Track separately by segment and deal size.

Pipeline velocity is the one metric that tells you whether growth efforts are working systemically. If you improve win rate but cycle length explodes, net velocity may not budge.

Slippage is a leading indicator of a forecast problem or a culture where reps commit without real buyer intent confirmed.

High no-decision rates usually mean you're engaging too early in the buyer's journey or failing to create urgency. Fix discovery and business case building, not discounting.

Track this by competitor AND by deal size. You might crush a competitor in SMB but lose every enterprise deal to them — that's a positioning and product gap, not a sales problem.

Self-reported win/loss reasons from reps are biased. Supplement with buyer interviews on lost deals — what the buyer says often differs significantly from what the rep logged.

Don't annualize one-time fees or services into ARR. ARR should only include contractually committed, recurring revenue.

NRR above 100% means you could stop acquiring new customers and still grow. It's the most important metric for SaaS businesses at scale.

GRR is the floor. NRR is the ceiling. A company with 98% GRR but 105% NRR has healthy expansion. 88% GRR but 102% NRR is masking churn with upsells — unsustainable.

Revenue per rep should increase over time as enablement, tooling, and territory mature. Flat or declining rep productivity during headcount growth is a major red flag.

Channel attribution is hard — don't let perfect be the enemy of good. Use first-touch or last-touch consistently and note your methodology.

Expansion revenue is cheaper to generate than new logos — lower CAC, faster cycle, higher trust. If you're not tracking it separately, you're leaving insight on the table.

Rising contraction is an early warning system. Customers downgrade before they churn. If contraction is climbing, your CS team should be engaging those accounts immediately.

Reactivation is cheap revenue — the customer already knows you. Track why they left and why they came back. Those insights improve both retention and re-engagement strategy.

Decompose net new ARR into its components every quarter. The mix tells you whether you're growing by acquiring, expanding, or just slowing churn. Each has different strategic implications.

Investors use payback period to model how much capital you'll need to grow. A 24-month payback means you're out of pocket for 2 years per customer before breaking even.

A ratio above 8:1 often means you're not spending enough on growth. Below 3:1 means the business loses money at scale. Target the 3–6 range.

LTV is always an estimate. Build conservative, base, and optimistic scenarios. Most companies use LTV from power users to justify spend that only works for the top 20% of their customer base.

This metric is most useful broken down by lead source. Inbound organic and cold outbound should be tracked and budgeted separately.

MQL definitions become meaningless if marketing inflates them. Audit MQL quality quarterly by checking closed-won rates on MQLs vs other lead types.

Track SQL rejection rates by rep. A rep rejecting 60% of MQLs is either over-qualifying or sandbagging. One rejecting 5% is likely accepting junk leads.

Calculate win rate by competitor, deal size, industry, and rep. These cuts tell you where you're actually competitive versus where you're wasting sales cycles.

CPL alone is a vanity metric. A $10 CPL channel that converts at 0.1% is worse than a $200 CPL channel converting at 5%. Always pair CPL with lead-to-customer rate.

Track cost per MQL by channel. Paid channels often have higher CPL but sometimes lower cost-per-MQL because they attract higher-intent leads that qualify more frequently.

Companies over-reliant on paid acquisition are one algorithm change or CPM increase away from a growth crisis. Invest in organic channels even when paid is working — it's your long-term moat.

Track revenue churn alongside customer churn. If a small number of churned customers cause disproportionate revenue churn, you have a customer concentration risk problem.

NPS is a lagging indicator — by the time someone rates you a 3, they've already mentally churned. Pair with health scores and usage data to catch problems early.

The inputs that matter most vary by product. Don't copy someone else's model — instrument your own based on what behaviors correlate with renewal in your cohort data.

A 92% annual retention rate means 8% annual churn. Use whichever framing resonates with your team for the strategic narrative you need to tell.

Not all engagement is equal. Define your 'power actions' — the features correlated with retention — and weight those higher in engagement scoring.

Track renewal rate 90 days out. If you're doing churn saves in the last 30 days you're already behind — the decision to not renew usually happens 60–90 days earlier.

Define your value milestone clearly. For a CRM, it might be 'first deal closed in-app.' For a project management tool, 'first project completed.' Vague milestones produce meaningless TTV data.

DAU/MAU varies enormously by product type. A tax filing app will never match a messaging app's ratio, and that's fine. Benchmark against your category, not the industry overall.

If your logo churn is 5% but revenue churn is 12%, you're losing your biggest customers. That's a product-market fit problem at the enterprise tier, not a generic retention issue.

Track meetings set against meetings held. A rep booking 20 meetings with 50% show rate generates the same as one booking 10 with 100% show rate.

If attainment is above 85%, quotas are too easy. Below 50%, you have a hiring, enablement, or quota-setting problem. Target the 60–70% zone.

Model ramp time into your headcount plan. If you need $2M in new ARR in Q4 and ramp takes 6 months, you needed to hire 6 months ago.

A rep with a very short cycle might be discounting aggressively. Pair velocity with ADS and margin — speed at the cost of deal quality isn't a win.

Research found reps who respond in 5 minutes are dramatically more likely to qualify a lead than those who wait 30 minutes. Most companies respond in 42 hours. This is a quick win.

Standardize proposal templates and pricing tiers. Most proposal delays come from custom pricing approvals and legal review, not from rep speed. Fix the process, not the people.

SSI correlates with pipeline generation in B2B, especially for AEs selling to mid-market and enterprise. Encourage reps to post weekly and engage with prospects' content.

Abandoned cart emails sent within 1 hour have 40%+ open rates and recover 5–15% of lost revenue. One of the highest-ROI automations in eCommerce.

Your top 20% by frequency likely drive 60%+ of revenue. Design retention programs specifically for them, not for the average customer.

Always cut CVR by device, traffic source, and landing page. A 3% overall CVR can hide a 1% mobile CVR that's killing revenue from your fastest-growing channel.

Segment returns by product, channel, and acquisition source. Influencer-sourced customers often have high return rates — CAC looks great, profit reality looks different.

RPV is better than CVR alone for optimizing ad spend, because it accounts for AOV differences between traffic sources.

GMV is a vanity metric unless paired with net revenue and take rate. A marketplace can grow GMV by cutting fees, which inflates volume but destroys economics.

Free shipping isn't free. Model the AOV threshold where free shipping is margin-accretive vs margin-destructive. Many brands set thresholds too low and lose money on every free-shipping order.

If your repeat purchase rate is below 25%, you're essentially running a single-transaction business. Fix the post-purchase experience, email flows, and product quality before spending more on acquisition.

Sales teams prefer TCV for larger-looking numbers. CFOs prefer ACV for planning. Know which metric your leadership actually makes decisions from.

Map stakeholder influence (Champion, Economic Buyer, Blocker, Influencer) in CRM. Deals stall because a blocker was never engaged, not because the champion lost interest.

If you know an account has 500 eligible users and you have 40 seats, you can model $X in expansion at current price per seat. This is how you build expansion pipeline.

If MQL→SAL rate drops, it's either a quality problem or a discipline problem. Distinguish these two before optimizing.

ARPA by cohort (Q1 2024 vs. Q1 2025 customers) tells you more than ARPA overall. It shows whether recent GTM changes attract bigger or smaller customers.

Research consistently shows multi-threaded deals close at 2–3× the rate of single-threaded deals. Build multi-threading into your sales methodology and inspect it weekly in pipeline reviews.

Bookings and revenue are NOT the same. A $500K annual contract signed Dec 31 may only generate $42K in Q4 revenue. Build both into reporting.

A company growing 10% MoM will dramatically exceed its current run rate. Always layer growth assumptions alongside run rate.

If productivity drops as headcount grows, you're adding reps faster than you can support them — common in companies that hire their way to growth.

Long TTR creates a gap between bookings and revenue that can mislead investors. Track both bookings and billings if TTR is long.

If your 'commit' category closes at 60%, it's not a commit — it's a best case. Recalibrate the criteria for each forecast category until commit actually means commit.

Use this to validate (or invalidate) the stage probabilities in your weighted pipeline. If your 'proposal' stage shows 60% probability but historically only 35% of proposal-stage value closes, your forecast is systematically inflated.

Contribution margin tells you whether scaling makes economic sense. If contribution margin is negative, every new customer costs you money — growing faster just accelerates losses.

Burn rate should decrease as a ratio to revenue growth over time. If you're burning $500K/month and adding $100K in net new MRR, your burn multiple is 5× — that needs to come down as you scale.

Burn multiple is what investors look at to determine if you're growing efficiently. A company adding $5M in net new ARR while burning $10M has a 2× burn multiple — functional but needs improvement.

A magic number above 0.75 means it's generally efficient to increase S&M spend. Below 0.5 means every dollar spent on growth is returning less than half — time to fix unit economics before scaling.

A company growing 80% with -30% margins scores 50 (healthy). A company growing 10% with 15% margins scores 25 (concerning). The Rule of 40 makes explicit the tradeoff between growth and profitability.

SER dropping while revenue grows means your sales org is getting less efficient — typically from over-hiring, poor territory design, or rising comp costs without proportional productivity gains.

Most companies have 10–20% of customers who are actually unprofitable when you allocate all costs. Identifying them isn't about firing them — it's about changing the service model or pricing to fix the economics.

Partner-influenced revenue is harder to measure but often larger than partner-sourced. Build co-sell tracking into your CRM — if you don't measure it, you can't justify partner investment.

Attach rate tells you if your partner program is actually being used. Low attach rate with a large partner roster means you have a partner enablement problem, not a recruitment problem.

Most partner programs follow a power law — a few partners drive almost all the revenue. Focus enablement and co-selling resources on your top 10–20% of partners rather than spreading thin.

Referral revenue has the best unit economics of any channel — lower CAC, faster cycle, higher win rate. If you don't have a structured referral program, you're leaving your cheapest growth lever untouched.

Co-sell deals almost always close at higher rates than direct-only deals because the partner adds credibility and relationships. Track the win rate lift to justify co-sell investment.

Most reps spend only a third of their time selling. The biggest time killers are CRM data entry, internal meetings, and manual prospecting. Every 5% improvement in selling time compounds into significant pipeline growth.

CRM hygiene isn't a rep discipline problem — it's a process design problem. If updating CRM is painful, reps won't do it. Reduce required fields to the 5–7 that actually matter for forecasting and reporting.

Most training ROI is never measured because companies don't baseline before training. Run a pre-training assessment, train, then measure the same metrics 90 days later. Without this, training is just cost.

Shelfware is expensive. Audit tool usage quarterly. If a tool has under 30% adoption after 6 months, either the tool is wrong, the training was insufficient, or the problem it solves isn't real. Cut or fix it.

Measure onboarding effectiveness, not just completion. A rep who completes onboarding but can't deliver a compelling demo hasn't really been onboarded. Build skills assessments into the program.

Each rep departure costs 6–12 months of productivity (vacancy + ramp of replacement). If you have 30% annual attrition on a 20-rep team, you're replacing 6 reps per year — that's ~$2M+ in lost productivity.