Conference Destinations by Season

Methodology, and what these numbers cannot tell you

Venue supply, rating and category depth

Every count on this page is read from our own directory database on 2026-09-19. A metro's venue count is the number of listings with an active status in that city. The average rating is the mean Google rating across the listings in that city that carry a rating; listings without one are excluded from the average rather than counted as zero, which is why the rated-listing count differs from the venue count. Category columns count listings filed under conference centers, convention centers and hotels and resorts. The 60 metros shown are the largest by listing count, not by population, meeting space, or hotel inventory. A city with a huge convention center can sit below a city with a long tail of small rooms, because this measures how many bookable places we list, not how much square footage they add up to.

Seasonality

Seasonal figures come from DataForSEO Labs, which returns twelve months of Google search volume for each keyword. For each metro we pulled the keyword cluster around "{city} conference venues" for the United States, then summed the monthly volume of every keyword in that cluster that carried a full twelve-month history. The window is 2025-09 to 2026-08. A metro's best season is the one holding the largest share of that total, and the index on the national chart sets the average month at 100. The pull cost $0.73 across 60 API calls.

This measures when people search, not when they book. A September spike means September is when planners type the query, and the events they are sourcing usually land months later. It says nothing about room rates, availability, or how hard a venue will negotiate. Nobody should read a quiet search month as a cheap month.

Cluster depth matters and is printed next to every season. A metro whose cluster held one keyword with history can show a season at 100 percent, which means one keyword happened to draw all its volume in those three months, not that nobody searched the rest of the year. Treat a one-keyword or two-keyword row as a hint and a twelve-keyword row as a signal.

27 of the 60 metros returned a usable twelve-month history. The other 33 returned none, usually because the keyword cluster for that city is too thin for Google to report month-level volume. Those rows read "No seasonal data" and their beacons are grey. We did not substitute a national curve, a neighboring city, or a model. Among the metros that did report, 12 peak in spring, which is the most common pattern here.

The map

Beacons are plotted from each city's stored latitude and longitude through an Albers equal area conic projection with standard parallels at 29.5N and 45.5N, computed at build time. The coastline is a deliberately coarse silhouette, accurate enough to place a dot in the right state and no more. Alaska and Hawaii are not drawn, and no metro in either state ranks in the top 60 by listing count.

Where two beacons would overlap, they are nudged apart until they do not, and any beacon pushed past the coast is walked back until it is on land. Four New York-area metros sit close enough that three of them were hidden under the fourth, so the map moved them; the largest correction is 16.8 units on a 856-unit canvas, under two percent of the width. Read a beacon as "this city, roughly here", and read the table for the exact city.

Refresh

The page is static. Counts move when we import venues and the site rebuilds; the search window moves when we re-run the seasonality pull. Both steps live in one script, PIPELINE/build_conference_destinations.py, which caches what it has already paid for so a rebuild never buys the same month twice.