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WHR vs PredictHQ

THE SHORT ANSWER

PredictHQ is API-first real-world context: it ranks each event’s impact, predicts attendance and spend, and delivers prebuilt features and event-aware forecasts into models. WHR reads one graph of events, companies, people and places two ways: WHR GTM for participation intelligence, WHR GEO for location and demand intelligence. WHR GEO does not stop at a number: it reads who is taking part and where they travel from. Choose PredictHQ for model-ready context; choose WHR when the entity layer is the point.

WHR and PredictHQ, axis by axis

AXISWHRPREDICTHQ
Data sourceThe event corpus and event infrastructure built by running 10times since 2014, with organizer listings, event agendas and directories, public announcements and what participants publish themselves — cross-checked, then resolved to entities, so name variants become one company and editions are tracked as they change.PredictHQ says it aggregates public and proprietary sources, including public APIs, then verifies, de-duplicates and filters them — it reports removing a large share of raw records as spam or duplicates.
Signal typeWHR GEO: what is happening in a place and what it does to demand — which events are creating the activity, who is taking part, where the audience travels from and which days peak. Expressed as a Demand Score for a city or zip across the next 90 days and each event’s Demand Impact, modelled from attended events together with unattended ones such as holidays, weather and warnings. Estimates are labelled as estimates. WHR GTM reads the same graph from the sell side: which companies and people take part.Each event is enriched with an impact rank, a local rank, predicted attendance, predicted event spend and a suggested radius; separate products deliver prebuilt machine-learning features, event-aware forecasts, and a relevancy tool for identifying which real-world conditions affect a business.
CoverageAttended business events — trade shows and conferences; non-business events — concerts, festivals, sports, political rallies; and unattended event types — public holidays, weather and warnings. Over a million business events and over two and a half million business event editions, over a hundred million companies and influencers, in over a hundred countries. Records accumulate from 2014 — twelve years. Participant-level records run three years deep and grow daily.Attended events such as conferences, expos, concerts, sports and festivals, plus non-attended ones — public and school holidays, observances, severe weather, broadcasts and more. PredictHQ publishes its own event counts.
Update cadenceContinuous. New signals — registrations, sponsorships, speaking slots, venue bookings — are timestamped as they enter the graph, and the search database is updated around the clock. Demand tracking runs on a 30-day window for any city or zip.PredictHQ describes its event data as continuously updated in near real time. Data shares refresh daily, and it recommends API users sync every 24 hours.
Pricing modelPublished on the pricing page, on one token balance across search, watches and history. Search & Prospecting in self-serve monthly tiers; Monitor by the entity per month and by the signal for event editions; Intelligence licensed, in early access. Your own footprint is free.No prices are published. The pricing page is a feature comparison with a free trial and demo booking; data-share delivery sits with its advanced features.
Best forTeams that need the relationship between physical activity, the entities driving it and the places it lands — operators such as hotels, venues, restaurants and transport, and companies that want one graph to serve both demand planning and go-to-market.Data science and operations teams at enterprises that want real-world context, features and event-aware forecasts inside demand forecasting, pricing, staffing and inventory models across many locations.

What this page says about PredictHQ comes from PredictHQ’s own public pages, read September 2026: predicthq.com · Events · Data quality · Pricing · Docs. Products change; if a line here is out of date, their page is the authority, and we would like to know.

Choose WHR when

  • It matters who is in the events — which companies, which industries, what kind of audience — not only that an event of a given size is happening.
  • You want to know where an event’s audience travels from, built from participation records rather than surveys.
  • You want to drill from a city’s demand on a given day into each contributing business event and the companies participating in it.
  • You want the entities as well as the impact: which organizations and people recur, and how their presence changes over time.
  • The same organisation also sells to events or to companies, and one graph should serve both teams.
  • You want published pricing and a free starting point.

Choose PredictHQ when

  • You are building or improving a demand-forecasting model and want prebuilt, model-ready features rather than records to interpret.
  • You want event-aware forecasts delivered as a finished product, rather than signals you build your own forecast on.
  • You want predicted spend by category, and impact ranks that are comparable across very different event types.
  • You want predicted TV viewership for broadcasts, which WHR does not offer.
  • You need delivery into your data stack — Snowflake, AWS Data Exchange, or an API with SDKs.
  • You operate across many locations and need one consistent event feed for all of them.

Questions people ask about WHR and PredictHQ

01

Is WHR an alternative to PredictHQ?

An event is a signal that is time-bound and short-lived; the graph is what turns it into intelligence. They solve different layers. PredictHQ is built to feed models and operational systems with ranked, enriched real-world context and event-aware forecasts. WHR is built on an event and entity graph, so it answers what is happening, who is involved, where they come from and how those things connect — then derives demand from that. A forecasting team may want PredictHQ’s features; a team that needs to know which organizations are behind the activity may want WHR’s graph. They are not the same job.

02

What does “who is in the events” add to demand forecasting?

Two events of the same size do not create the same demand. An audience of inbound business travellers fills hotel rooms and restaurants differently from a local consumer crowd. The entity layer is what makes that visible: WHR connects an event to the organizations and people participating in it, and models footfall, audience mix and inbound share per event as Demand Impact — rather than treating every event as an anonymous volume number. Those are estimates, and are labelled as estimates.

03

Does WHR cover unattended events such as public holidays and weather?

Yes. WHR GEO combines event-driven activity with the other real-world signals that move a place, including public holidays, weather and warnings — so on the kinds of event covered, the two are comparable. The distinction worth keeping is that events are one class of signal rather than the whole world model, and the event graph is what connects that activity to organizations, people and locations. PredictHQ’s edge is elsewhere: prebuilt machine-learning features, predicted spend by category, and predicted TV viewership for broadcasts, none of which WHR offers.

04

How does pricing compare?

PredictHQ does not publish prices; its pricing page offers a free trial and a demo. WHR publishes its pricing — one token balance across search, watches and history, with licensed Intelligence in early access — and demand feeds are also available by API.

05

Can WHR data be used in a forecasting model?

Demand feeds are available by API, and the Demand Score and Demand Impact are documented on the methodology page with what each number means and where it stops. WHR does not offer a library of prebuilt machine-learning features; PredictHQ does.

06

Where does the information about PredictHQ on this page come from?

From PredictHQ’s own public site and documentation, read in September 2026 and linked under the comparison table. Products change, so their pages are the authority on what PredictHQ does today.

PRICING · 03 UNDERSTAND

Read demand from who is coming.

Event, category and city level — the same graph, read from the place’s point of view.

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