Reading the funnel: inquiry, viewing, offer, close ratios

Five hundred inquiries last month. Forty viewings, eight offers, three completions. Everyone in the Monday meeting agrees the funnelfunnelThe customer journey from awareness to purchase, typically Awareness, Interest, Consideration, Decision, Action, with prospects narrowing at each stage.View full definition → is soft, and nobody agrees where. That disagreement is expensive, because the fix for a viewing problem (response times, photography, qualification) has nothing in common with the fix for a closing problem (mortgage delays, down valuations, collapsed chains). The stages themselves and who owns each handoff are settled in the foundations lesson on building the acquisition funnel. This one is about the three numbers that sit between those stages, and about reading them without fooling yourself.

The three ratios and what each one accuses

• Inquiry-to-viewing = viewings ÷ inquiries. Accuses lead quality and response speed.
• Viewing-to-offer = offers ÷ viewings. Accuses price and property fit: they saw it and did not want it at that number.
• Offer-to-close = completions ÷ offers. Accuses execution: financing, survey, chain, legal.

The brokerage above runs 8%, 20% and 37.5%. Two stages are weak, not one. Before arguing about which to attack, price both repairs in completions. Lift inquiry-to-viewing from 8% to 12% and hold everything downstream: 60 viewings, 12 offers, 4.5 completions. Leave the top of the funnel alone and repair offer-to-close from 37.5% to 60% instead: still 8 offers, but 4.8 completions. Similar gain, entirely different department, and one is a hiring decision while the other is a conveyancing one. Do that arithmetic before the meeting rather than during it.

Count cohorts, not calendar months

The most common way to misread these ratios is to divide this month's completions by this month's inquiries. In UK resale, offer accepted to completion often runs three months or more, and inquiry to completion longer again. A brokerage growing lead volume 10% a month will show a falling offer-to-close rate every single month while nothing is actually deteriorating: the denominator is fresh and the numerator is old.

Cohort by inquiry date instead. March's inquiries produce March viewings, May offers, August completions, and you read each cohort at a fixed age: inquiry-to-viewing at day 14, viewing-to-offer at day 60, offer-to-close at day 120. The most recent two or three cohorts are immature and belong greyed out on the dashboard, not averaged into the total. Teams that skip this replan media budgets against noise, then wonder why the correction never shows up.

Two counting traps

Multiple offers on one property. Six offers on the same flat, one completion: lead-level offer-to-close reads 17%, property-level reads 100%. Nothing is broken, five buyers lost a bidding contest. Carry both denominators, or a hot market will look like an execution failure and someone will restructure a legal team that is performing fine.

Stage skipping. A returning buyer who offers sight unseen, or an off-market deal logged straight in at offer, gives you offers with no parent viewing, and enough of them push viewing-to-offer past what is arithmetically possible. The reverse is more common and more damaging: viewings recorded only when they led somewhere, which inflates viewing-to-offer and hides the leak one stage up.

One blended benchmark will misdiagnose most of a mixed portfolio

Resale (existing units, individual sellers). Viewing-to-offer is the volatile stage, because buyers compare several near-identical listings at once. Directional for the US, 2025 to 2026: 15 to 30% viewing-to-offer in competitive metros, per brokerage data aggregated in National Association of Realtors research. Offer-to-close sits higher, roughly 70 to 85% once financing is pre-qualified, because the buyer has already self-selected into one specific unit.

New developments. Inquiry volume is large and inquiry-to-viewing low, perhaps 5 to 12%, because a good share of those inquiries are reacting to renderings rather than shopping for a home. Offer-to-close can also be weak, perhaps 50 to 65%: cooling-off periods, and 12 to 36 months of construction during which buyers' circumstances change.

Rentals. Inquiry-to-viewing is high, maybe 30 to 50%, and the whole funnel resolves in days. Application submitted stands in for offer, referencing and signature for close. Thin margin per lead, high velocity, and the binding constraint is viewing capacity rather than demand.

Offer-to-close is also not portable across borders. In England and Wales an accepted offer binds nobody until exchange, and fall-through rates on agreed sales are commonly reported somewhere between a quarter and a third. In Scotland, concluded missives lock the deal far earlier, so a Scottish agent's offer-to-close will look structurally better without anyone being better at the job.

Instrumenting it

Stage transitions only compute cleanly if one person is one lead. A portal inquiry through Rightmove that arrives again as a phone call two weeks later counts as two leads unless identity is resolved, which halves your inquiry-to-viewing rate for no real reason. Customer data platformsCustomer data platformsSoftware that unifies customer data from every source into one persistent profile that marketing, sales and service teams can act on.View full definition → such as Segment exist to stitch those events into one identifier, though Segment sells the pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.View full definition → in question, so treat vendor framing of "unified funnel visibility" with the scepticism you would apply to any supplier. The query itself is unremarkable:

SELECT
  asset_type,
  COUNT(DISTINCT CASE WHEN stage >= 'viewing' THEN lead_id END)::float
    / COUNT(DISTINCT CASE WHEN stage >= 'inquiry' THEN lead_id END) AS inq_to_view,
  COUNT(DISTINCT CASE WHEN stage >= 'offer' THEN lead_id END)::float
    / COUNT(DISTINCT CASE WHEN stage >= 'viewing' THEN lead_id END) AS view_to_offer,
  COUNT(DISTINCT CASE WHEN stage = 'closed' THEN lead_id END)::float
    / COUNT(DISTINCT CASE WHEN stage >= 'offer' THEN lead_id END) AS offer_to_close
FROM leads
GROUP BY asset_type;

Grouping by asset_type, and by inquiry cohort, is the whole design decision. Everything else is formatting.

Where you get paid decides which ratio anyone watches

Purplebricks built its UK business on a fixed fee charged up front, payable whether or not the property sold. Revenue recognised at instruction, which makes instructions won the number that governs the week, and pushes offer-to-close into somebody else's report. Critics spent years comparing its listings taken against sales completed, and the group was sold to Strike in 2023 for a nominal £1. The general point survives the specific case: the stage your revenue books at gets the management attention, and the stages after it quietly rot. If your commission lands at completion but your dashboard leads with inquiries, you have the same misalignment pointing the other way.

Where leaks actually get fixed

• An inquiry-to-viewing leak is usually operational. Lead response research has replicated the same finding for years: contact within minutes converts at a multiple of contact hours later. That is a rota and CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.View full definition → automation fix, not an ad budget fix.
• A viewing-to-offer leak is usually price or fit. Prospects tour and walk away when the listing is mispriced against comparable stock, or when something photographs badly (layout, aspect, noise) and only reveals itself in person.
• An offer-to-close leak is usually friction: pre-approval that was never real, a valuation below the agreed price, a chain breaking three links away.

There is a second-order trap in the first one. Loosening qualification lifts inquiry-to-viewing beautifully and moves the leak downstream, where each unqualified viewing has now consumed an hour of an agent's diary. Completions stay flat, cost per completion rises, and the dashboard looks healthier. Judge any top-of-funnel intervention on completions per agent hour, not on the ratio it was aimed at. What these ratios do to media pricing, turning a cost per lead into a cost per closing, is the next lesson's arithmetic.

Benchmarking responsibly

Brokerages rarely publish granular funnel data, so treat every figure above as directional rather than audited.

1. Build your own baseline from 6 to 12 months of cohorted CRM data before comparing against anything external.
2. Segment each ratio by asset type and by lead source. A referral and a cold portal inquiry have structurally different viewing and completion rates, and blending them produces a number that describes no real lead.
3. Re-baseline seasonally. Resale viewing-to-offer tends to tighten in spring across much of the US and Europe and loosen in winter, a pattern rather than a law.

🎬 [VIDEO: "How to Build a Real Estate Sales Funnel" - youtube.com - search for recent brokerage or proptech channel walkthroughs of CRM-based lead-to-close tracking, useful for seeing funnel stages instrumented in real dashboards]

Key takeaways

• Each ratio accuses a different department: lead quality and speed, then price and fit, then execution. Price the repair of each in completions before choosing.
• Cohort by inquiry date. Dividing this month's completions by this month's inquiries manufactures a decline out of growth.
• Carry both lead-level and property-level offer-to-close, or competitive bidding will read as a closing failure.
• Never blend ratios across asset types or jurisdictions. New developments leak at inquiry-to-viewing and offer-to-close, resale at viewing-to-offer, rentals barely leak but run out of viewing capacity.
• Whichever stage books revenue gets the attention. Check that the stages after it are still being measured by someone.