> For the complete documentation index, see [llms.txt](https://docs.predicthq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicthq.com/getting-started/guides/industry-specific-event-filters.md).

# Industry recommendations

PredictHQ applies to any business whose demand is shaped by the real world. For a set of named industries, we have gone further and optimized the product directly: industry-specific impact patterns, thresholds, and catchment radii, tuned to how events affect that sector. Specifying a named industry gives you those optimizations out of the box - and either way, Beam personalizes results using your own demand data, which is more specific than any industry preset.

## Named industries

Use the Industry Value when specifying an industry in an API request. If your business doesn’t map exactly, use the Examples / Adjacent column to find the closest fit, or use `other` - an unlisted industry doesn't limit which events, features, or APIs you can use.

| Named Industry                         | Industry Value   | Examples / Adjacent Industries                                                       |
| -------------------------------------- | ---------------- | ------------------------------------------------------------------------------------ |
| Accommodation                          | `accommodation`  | Hotels, hostels, co-working spaces with short-term stays.                            |
| Consumer Packaged Goods (CPG)          | `cpg`            | Packaged food & beverages, household goods.                                          |
| Leisure, Travel & Tourism              | `tourism`        | Entertainment venues (cinemas, casinos, theme parks), attractions, DMOs, OTAs.       |
| Marketing and Advertising              | `marketing`      | Agencies, ad networks, campaign platforms.                                           |
| Parking                                | `parking`        | Car parks, garages.                                                                  |
| Food and Beverage (Restaurants & Bars) | `restaurants`    | Cafes, pubs, quick service restaurants, hospitality venues.                          |
| Retail                                 | `retail`         | Supermarkets, fashion, electronics, gyms/fitness centers (if sales-oriented).        |
| Transportation and Delivery            | `transportation` | Rail, buses, rideshare, delivery services.                                           |
| Other                                  | `other`          | If your business does not clearly fit into one of the above industries, use `other`. |

## Where industry matters

Industry is used across our systems to tune how events are interpreted and modeled for your business. This includes areas like impact patterns, thresholds, and catchment radius recommendations.

* **Predicted Impact Area API**\
  Area recommendations vary by industry, since the catchment area for demand differs across sectors.
* **Predicted Impact Patterns**\
  For each event, we calculate its leading and lagging impact per industry. These patterns are then used in the Features API to ensure event impacts reflect your sector.
* **Beam**\
  Beam builds on these industry-tuned patterns and thresholds, and further personalizes results with your own demand data.
* **Forecasts API**\
  Uses industry in the same way as Beam (industry is passed through to Beam behind the scenes).

## Beam Comes First

The most accurate way to identify which events impact your business is with [Beam](/getting-started/core-concepts/what-is-beam.md), 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
* Create a [Saved Location](/api/saved-locations/overview.md) for each of your business locations — this automatically generates a Predicted Impact Area that defines the geographic scope for event retrieval, so you don't need to manage the boundary manually

These are starting points only. Switch to Beam as soon as you can provide demand data.

## Recommended Feature Groups / Categories

<table><thead><tr><th width="236.2265625">Industry</th><th>Recommended Feature Groups / Categories</th></tr></thead><tbody><tr><td>Accommodation</td><td>academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports</td></tr><tr><td>Parking</td><td>concerts, expos, festivals, observances, performing-arts, public-holidays, school-holidays, sports</td></tr><tr><td>Restaurants</td><td>community, concerts, conferences, expos, festivals, performing-arts, public-holidays, school-holidays, sports</td></tr><tr><td>Retail, CPG</td><td>academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports</td></tr><tr><td>Transportation</td><td>academic, community, concerts, conferences, expos, festivals, observances, performing-arts, public-holidays, school-holidays, severe-weather, sports</td></tr><tr><td>Tourism, Marketing, and Others</td><td>concerts, expos, festivals, performing-arts, public-holidays, school-holidays, sports</td></tr></tbody></table>

{% hint style="info" %}
When requesting features from Features API with a Beam ID we automatically configure all the correct settings based on the Beam results. When not using Beam, we recommend using the `sum` stat for all relevant features (based on the industry to category mappings above) except for severe weather where we recommend using the `max` stat to avoid over representing the impact of severe weather events when multiple are overlapping.
{% endhint %}

## 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.

<table><thead><tr><th width="242.7578125">Industry</th><th>Minimum Local Rank</th></tr></thead><tbody><tr><td>Accommodation</td><td>50</td></tr><tr><td>Parking</td><td>50</td></tr><tr><td>Restaurants</td><td>50</td></tr><tr><td>Retail</td><td>35</td></tr><tr><td>Others</td><td>35</td></tr></tbody></table>


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