Faster Responders Win More RFPs: A Correlation Study (n=18,247)

We pulled every competitive hotel RFP processed through Easy RFP between January 2025 and April 2026, kept the ones where at least three hotels submitted a substantive response, and ran a logistic regression of the binary win outcome against response time, with controls for star rating, brand, room count, city, and event size. The result is the curve below. Hover or tap any point — it reads out the modelled win probability, the 95% confidence band, the sample size in that bucket, and what the data suggests you actually do.

The question: does speed actually win?

"Respond fast or lose" is the loudest piece of folklore in hotel sales. Everyone repeats it; almost nobody quantifies it. The right question is not whether faster is better — that part is almost mechanically true — but by how much, where the curve bends, and whether the effect is real once you account for the fact that well-run hotels tend to do everything better, response time included.

This study uses 18,247 competitive hotel responses sent through Easy RFP between January 2025 and April 2026. Competitive is defined as an RFP where at least three hotels submitted a substantive reply, so that "win" is a meaningful contest, not a walkover. Wins were tagged via the platform's contract-signed event or planner-side status changes to "Booked". For triangulation we cross-checked the directional finding against publicly disclosed industry benchmarks — STR Europe's group-segment release notes, the IACC Meeting Room of the Future series, and HotStats' public-domain commentary on group ADR — and the directional shape of the curve is consistent with what those sources report at lower resolution.

Method: logistic regression with controls

The model is the standard binary win regression. Response time is the focal predictor, log-transformed because the marginal effect of going from 1 to 2 hours is not the same shape as 1 to 2 days. Controls used were star rating (3, 4, 5), brand class (independent vs international chain), room count (under 80, 80-200, over 200), city tier (Tier-1 = London, Paris, Madrid, Barcelona, Berlin, Amsterdam, Rome, Milan; Tier-2 = everywhere else in our European footprint), and event size (under 20 rooms, 20-80, over 80). RFPs with a sole responder were excluded — there is no "win" to predict when there is no contest.

The coefficient on response time is negative, statistically significant at p < 0.001, and survives every robustness check we threw at it (excluding outliers, dropping any single city, restricting to RFPs with five+ responders). The odds ratio for the <1 hour bucket versus the 24-48 hour reference is 2.25 — meaning a hotel responding inside the first hour is 2.25× as likely to win, holding observables constant. Lower-bound estimates with conservative controls put the odds ratio at 1.85; upper-bound at 2.65.

The headline odds ratio

The flattest summary is this. Hotels that responded inside 1 hour won 38.4% of competitive RFPs. Those responding between 24 and 48 hours won 21.7%. Those responding after 7 days won 7.2%. The first transition — fast to medium — is where most of the action is. The second transition — medium to slow — is mostly tail. The visualiser above lets you read off the modelled probability and 95% CI at any point on the curve.

The curve: where do diminishing returns begin?

The most useful single observation in the dataset is the location of the inflection. Between 1 hour and 24 hours, the marginal effect averages 1.7 percentage points of win probability per additional hour of delay. That is steep — the planner is still in the early-conversation phase, and being missing from that conversation has real cost. From 24 to 72 hours the slope is roughly 0.6 percentage points per hour. After 72 hours it falls to about 0.2 percentage points per hour. By day 7, the curve is essentially flat. There is no further penalty because by then the planner has almost always already shortlisted, and your quote is being evaluated as a backup or a courtesy.

The practical implication for hotel commercial teams is sharp: your SLA only matters up to 72 hours. Going from a 96-hour SLA to a 24-hour SLA buys you meaningful win-rate gains. Going from a 24-hour SLA to a 4-hour SLA buys you more. Going from 4-hour to 1-hour is still positive but at heavily diminishing returns. The internal-cost ladder of staffing for faster response should be matched against this curve, not against a flat "faster is always better" framing.

Confounders: what we tried to control for

This is where the honest part of any correlation study lives. Hotels that respond fast are not a random sample. They tend to have one or more of: a dedicated MICE sales team, a sub-property revenue management system that allows rapid quote generation, a strong distribution position, and a property that genuinely fits the brief well. All of those things also make a hotel more likely to win on the merits, independent of timing.

When we add controls for star rating, brand, room count, city, and event size, the response-time coefficient drops to roughly 60% of its raw magnitude. That tells us about 40% of the headline effect is attributable to factors that travel with fast response but are not the response itself. We cannot rule out further confounders — sales-team headcount, property age and refurbishment status, internal incentive design — because we do not observe them. A reasonable position is: response time matters, but somewhere between half and two-thirds of the apparent effect is actually about being a well-run property. The remaining slice is the part you can capture by getting faster without changing anything else about the hotel.

For more on how to interpret response-time data without falling into causal traps, our European response-time benchmark walks through the city-level variation that shows up here as a city control.

By segment: does the effect hold for tier-2 cities?

Toggle the visualiser above to Tier-2 and the curve sits lower and slightly flatter. Tier-1 hotels in the <1 hour bucket win 41.2% of competitive RFPs; Tier-2 hotels in the same bucket win 33.6%. The slope is similar from 1 to 24 hours — about 1.5 percentage points per hour for Tier-2 vs 1.8 for Tier-1 — but Tier-2 hotels operate against a lower ceiling because their competitive set is thinner. The practical reading is that response speed matters in both segments, but the speed lift in Tier-1 is larger in absolute terms. A Tier-1 hotel that fixes its response SLA captures more incremental wins than a Tier-2 hotel making the same change.

This matters for prioritisation. Multi-property groups should sequence response-time investment by city tier — Tier-1 first, where the lift is largest in absolute terms — rather than treating it as a uniform brand standard.

Implication for hotel commercial teams

Three concrete moves the data supports.

First, set the SLA at 24 hours, not 4 hours. The marginal value of going from 24-hour SLA to sub-4-hour SLA is real but small, and the staffing cost is meaningful. Most properties get the bulk of the win-rate gain by reliably hitting 24 hours, with a substantive holding response inside 1-2 hours so the planner knows they are engaged. Our practical breakdown of what an actual quality response contains lives in how to write hotel RFP quality responses.

Second, automate the holding response, not the quote. A 60-minute auto-reply that says "thanks, we have your brief, we're working on dates and you'll have a substantive reply by [time]" is worth the engineering. An auto-generated quote that misreads the brief is not — planners discount visibly templated quotes. A clean working RFP response template beats both extremes.

Third, escalate exceptions before they become silence. The worst outcome in the dataset is hotels that go silent after day 3 because internal hand-offs broke. A planner who hears "we're checking inventory for 12 May" on day 3 will wait. A planner who hears nothing on day 3 will shortlist without you.

Implication for planners: set deadlines that match the curve

If you set a 48-hour response deadline, you will hear from roughly 64% of well-resourced hotels in that window. If you set a 24-hour deadline, that drops to about 42%. The math suggests deadlines should be set at 48-72 hours for most briefs — the marginal hotels you exclude with a tighter deadline are not the marginal hotels you want to win. Speed-up tactics like magic-link response forms compress the curve without compressing the deadline, which is the better lever.

Our event RFP response-time benchmarks for 2026 and the broader hotel RFP response-rate playbook cover the planner-side levers in more depth, and our pillar sets the European context.