Recommended Event Categories and Local Rank Thresholds
Industry-level defaults for event relevancy when Beam can’t be used.
Beam Comes First
The most accurate way to identify which events impact your business is with Beam, PredictHQ’s relevancy engine. Beam analyzes your demand data to surface which event categories matter most at each of your locations, so you don’t need to guess.
Without Beam, you’re guessing which events matter. With Beam, your own demand data tells you - so you cut noise, focus on impact, and avoid costly mistakes.
If you have demand data, always run Beam first.
When You Can’t Use Beam
If demand data isn’t available, we’ve done research to provide industry-level defaults. These include:
Recommended Feature Groups (categories) per industry
Minimum Local Rank thresholds to filter out events too small to matter
As always, use Suggested Radius to work out a suitable area
These are starting points only. Switch to Beam as soon as you can provide demand data.
Recommended Feature Groups / Categories
Accommodation
academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports
Parking
concerts, expos, festivals, observances, performing-arts, public-holidays, school-holidays, sports
Restaurants
community, concerts, conferences, expos, festivals, performing-arts, public-holidays, school-holidays, sports
Retail, CPG
academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports
Transportation
academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports
Tourism, Marketing, and Others
concerts, expos, festivals, performing-arts, public-holidays, school-holidays, sports
Minimum Local Rank Thresholds
Local Rank is a location-sensitive scale (0-100, logarithmic) that predicts how much impact an event will have in its immediate vicinity - factoring in population density and local characteristics such as how built-up or accessible an area is. For example, a 1,000-person conference may register a Local Rank of 43 in densely populated Hong Kong and 65 in less crowded Dublin - despite having the same PHQ Rank.
Beam automatically applies Local Rank filtering when identifying impactful event types for your demand modeling. However, if you’re setting up filters or queries manually, these thresholds offer a smart default to focus your analysis where it matters until you can rely solely on Beam.
Accommodation
50
Parking
60
Restaurants
65
Retail
35
Others
35
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