Close Rate Calculator

What's a healthy close rate for home service trades?

There's no reliable published benchmark by trade, so these are rules of thumb: overall lead-to-job around 10-18% for service work (high-ticket project trades often run lower), lead-to-appointment around 30-50%, appointment-to-job around 25-45%. The one published reference point is for Local Services Ads: SearchLight Digital's 2026 study found 43.9% of LSA leads booked, and a booked lead isn't yet a paid job. Compare your own rates by lead source and over time before anything else.

Why is my appointment-to-job rate so low?

A common cause is competing quotes: when a homeowner gets several quotes, each contractor wins a smaller share. Less common: pricing transparency issues, weak warranty positioning, or slow proposal turnaround. Audit the 48 hours between quote and decision — that's usually where you lose them.

How often should I check these numbers?

Monthly. Track last-90-days rolling rates so you smooth out single-week anomalies. Big changes month-over-month signal something material — new ad creative launching, new offer, seasonal demand shift, or team process changes.

Where do contractors' funnels commonly break down?

Speed to lead. The published lead-response research consistently finds that contacting a lead within minutes rather than hours makes a large difference to whether you ever reach them (the studies are in our speed-to-lead statistics guide). Automating an instant SMS with a calendar link is one of the cheapest fixes available.

Should I measure close rate per channel separately?

Yes — absolutely. A typical pattern is referrals closing at the highest rate, then Local Services Ads, then landing-page leads, with instant-form leads lowest; check it against your own CRM. Your own numbers will differ, which is exactly why you should measure them. Blending them into a single number hides the winners and losers. Track per-source close rate + cost per booked job for each channel — then shift budget to whichever source produces the lowest cost-per-booked-job for your trade.

How do I get my whole team to track these conversion rates?

Make ONE person responsible for the report. Tracking that everyone owns tends to lapse; one owner keeps it alive. Standard setup: receptionist or office manager logs every lead's status weekly (booked/no-show/closed/lost) into a simple sheet. 5 minutes per week. The owner reviews monthly. If no one owns the data, the data won't exist — and you'll be guessing about ROAS forever.

What's the relationship between speed-to-lead and close rate?

Tightly correlated. The published lead-response studies (collected, with their methods, in our speed-to-lead statistics guide) consistently find that the odds of reaching and qualifying a lead fall steeply as response time stretches from minutes to hours. Follow-up speed is easy to under-invest in because the cost is invisible; set up an automated SMS within 60 seconds and compare your close rate before and after.

How many follow-up attempts should I make before marking a lead 'lost'?

As a rule of thumb, about 7 attempts across 14 days. A cadence that works for many teams: (1) immediate SMS within 60 seconds; (2) call within 5 minutes; (3) voicemail + text combo at 1 hour; (4) call again next morning; (5) email with calendar link day 2; (6) text again day 4; (7) final 'closing the loop' call day 7-14. Giving up after one or two attempts loses leads who would have answered later; persistence, not sales talent, is often the difference. Set up automation so attempts 1-3 fire automatically; only attempts 4-7 need human time.

What's the highest-leverage place to improve close rate — is it the call script, the appointment, or the proposal?

Almost always the appointment-setting call (between lead submit and scheduled estimate). Many leads that never close are lost in that first conversation, not at the proposal stage. Common appointment-call mistakes: (1) leading with availability ('When are you free this week?') vs leading with qualification ('Tell me about the issue first'); (2) not pre-framing the in-home visit ('I'll bring a tablet, walk through the issue, and email you a written estimate within 48 hours'); (3) skipping the budget conversation ('Most projects run between $X and $Y — does that align with what you're expecting?'). Fixing the appointment-setting script is usually the fastest close-rate improvement available. It's easy to over-invest in proposal polish (CRM templates, glossy PDFs) and under-invest in the 5-minute conversation that decides whether the proposal even matters.

How do no-show rates typically affect close rate calculations, and how do I reduce them?

No-shows quietly drag down reported close rates (there's no reliable published no-show rate for contractors, so measure your own). Two-part fix: (1) MEASURE — track 'appointments scheduled' separately from 'appointments held.' Without separating these, your reported close rate looks worse than reality (because no-shows count as 'didn't close'); (2) REDUCE — confirmation cadence the day before + day of: SMS at 24 hours before ('Confirming your roofer visit at 10am tomorrow — reply CONFIRM or RESCHEDULE'); SMS again at 1 hour before ('On my way, ETA 10:05am'); call if no SMS reply by 30 min before. Confirmation reminders like these usually cut no-shows noticeably; measure yours before and after. The math: if 25% of scheduled appointments don't happen, your close rate on scheduled appointments is only 75% of your close rate on held ones — a 30% close rate on held visits shows up as 22.5%. Separating the two tells you whether the problem is sales or attendance.

How does close rate vary by service type within the same business — and should I track them separately?

Yes, separately. Close rates usually differ sharply by service type (the order below is a common pattern, not a published benchmark): (1) EMERGENCY services (plumbing leak, HVAC outage) — highest, because the customer needs it done now; (2) MAINTENANCE services (annual tune-up, recurring lawn care) — middle, lower friction but less urgency; (3) PROJECT services (roof replacement, kitchen remodel, solar install) — lowest, with a longer consideration cycle and multiple quotes. Tracking blended close rate hides which service type drives revenue. Best practice: run this calculator separately for each service line; report 3 close rates to your team monthly; set 3 different campaigns optimized to the close-rate-appropriate offer architecture (emergency = speed; maintenance = recurring billing; project = trust + risk-reversal). Blending all services into one number hides which line is actually paying back.

How do I diagnose whether my close rate problem is sales-skill, sales-volume, or systemic?

Use a 3-test diagnostic in this order: (1) SALES-SKILL test — pull the last 20 lost leads, ask each rep to write a one-line reason for the loss. Then YOU re-call 5 of them to ask 'what would have made you say yes?' If reps cite 'price' but customers cite 'communication delays,' the issue is rep skill or process — not pricing. Skill issues fix with training + script updates; (2) SALES-VOLUME test — measure first-touch response time per lead. If average response time is >30 minutes when you're at full volume but <5 minutes during slow weeks, the issue is volume capacity. Volume issues fix with hiring or automation; (3) SYSTEMIC test — pull close rates by lead source, by day-of-week, by service line. If the variance is small (say within 10 percentage points), the issue is systemic (offer too weak, brand reputation issue, market price-shopping). Systemic issues require strategic fixes — not faster phone answers. 'Close rate is bad' is often diagnosed as a sales-skill problem when it's actually one of the other two. Run all three tests before deciding what to fix.

What's the right number to incentivize sales reps on — close rate, revenue, or cost-per-booked-job?

REVENUE with a quality floor — not pure close rate. Three reasons: (1) PURE close-rate incentives encourage cherry-picking — reps avoid hard leads + game which leads they take; (2) COST-PER-BOOKED-JOB incentives create misalignment — reps don't control marketing spend, so blaming them for it is unfair; (3) REVENUE incentives align them with business outcome but pure revenue invites over-discounting (close at any price = lower margin). The ideal model: base salary + commission on revenue × close rate floor. Hypothetical example: 5% commission on revenue from booked jobs, paid only while the rep's close rate stays above a floor you set from your own history (say 18%). Encourages closing volume + closing quality without penalizing reps for marketing-team decisions. Set the floor from your own team's median (use this calculator's outputs). Adjust quarterly. Over-simple incentives produce reps who chase the wrong outcome. The right comp plan aligns rep behavior with business goals.

How do I get truthful close-rate data from my reps — they tend to round up to make themselves look better?

Decouple data from rep self-reporting. Three structural fixes: (1) AUTOMATIC tracking — your CRM should mark every lead as 'won' or 'lost' based on actual paid invoice status, not rep status updates. Tie close rate calculation to invoice data, not rep-marked deal status. Most CRMs (HubSpot, GoHighLevel, ServiceTitan) support this; (2) WEEKLY review of WIN/LOSS REASONS — reps fill out a one-line reason for every lost lead. Pattern-match across their list: if 'price too high' dominates one rep's list but rarely appears on another's, the issue isn't price (it's the rep's tendency to blame price). Forces honest categorization; (3) RANDOM AUDIT — call 2-3 lost leads per rep each month yourself. Verify what the rep recorded as the loss reason matches what the customer actually says. A few calls a month is enough to keep reports honest. Don't trust self-reported close rates without these structural checks; reps are rarely lying on purpose, but self-reported close rates tend to drift upward.

What's the right way to share close rate data with my marketing team or agency without creating finger-pointing?

Frame close rate data as a SHARED diagnostic across two teams (sales + marketing), not a sales-team-only metric. Three communication tactics: (1) DECOMPOSE the metric — 'Our cost per booked job is $385. That's CPL × (1/lead-to-appt rate) × (1/appt-to-close rate). Marketing owns cost per lead; sales owns the appointment-to-close rate; both share the lead-to-appointment rate, because it depends on lead quality and follow-up speed.' Each team has clear ownership; (2) SHARE the FULL chain in weekly reports — show CPL, lead-to-appt rate, AND appt-to-close rate in one view. When close rate drops, marketing can see they didn't suddenly start sending bad leads (CPL didn't drop). When CPL spikes, sales can see they're not at fault. Transparency prevents finger-pointing; (3) CO-OWNED IMPROVEMENT TARGETS — instead of 'marketing should hit X CPL' + 'sales should hit Y close rate' separately, set 'we should hit Z cost-per-booked-job' as a SHARED target. Forces collaboration on the metric that actually matters. Siloed close-rate data breeds rivalry between marketing and sales; shared metrics build collaboration.

What close rate trends should I track WEEKLY to catch problems before they become bad-month catastrophes?

Track 4 weekly leading indicators that tend to move before close rate does: (1) FIRST-TOUCH response time (median seconds from lead-submit to first contact) — when this slips from minutes to hours, expect close rate to follow; (2) APPOINTMENT-SET rate (% of leads who scheduled appointment within 48 hours) — predicts how many leads make it through the first funnel stage; (3) NO-SHOW rate at scheduled appointments — silent close-rate killer; rises before appointments-held drop; (4) PROPOSAL turnaround time (median hours from in-home visit to written estimate sent) — slow proposal turnaround correlates with prospects shopping competitors during the gap. All four checked weekly = 5-minute review. Catches issues before they show up in monthly close rate totals. Close rate itself is a lagging metric; these four move first. Build a 4-row dashboard for these alongside CPL + CPBJ; review every Tuesday morning + escalate any leading indicator that's drifted well off its baseline (say 15%+, a rule of thumb).