What differs in data scale, place coverage and day‑to‑day workflow.
Huq 1T+ vs Geolytix 214M Mobile pings & Huq 50M+ vs Geolytix 50k Places.
Huq includes ~1 trillion mobile pings, 50M+ places and 5 years of history across the EU & ME. The larger data set supports finer‑grained catchments, more stable time‑series and better small‑area reads.
Huq lets you draw any boundary and compute metrics at ~50 m resolution, enabling site-specific analysis, while Geolytix focuses on area-level layers across standard boundaries. This means Huq supports more precise, micro-location decisions.
Huq offers ready-made workflows for retail, local government and public-sector tasks, including expansion, competitor, portfolio and regeneration tracking with first-party data. Geolytix emphasises whole-area views from aggregated third-party sources, making it more suited to broader averages than micro-location analysis.
Common questions about Huq Platform answered clearly.
Coverage and workflow differ. Huq provides larger movement and place datasets and a more advanced no‑code, intuitive interface. Many teams can cover the same decisions (site selection, catchments, benchmarking) with fewer specialist steps.
“Mobile pings” refers to aggregated, privacy‑first observations used for movement and footfall analysis. “Places” are deduplicated points of interest with metadata for retail and public‑realm assets. Counts reflect internal QA processes and may change as sources update.
With first‑party collection, Huq controls ingestion and QA end‑to‑end, which supports consistent measurement across time and geographies. Third‑party aggregation (per your input for Geolytix) can introduce variation between vendors. We recommend side‑by‑side trials against ground truth.
Huq computes metrics for custom shapes at ~50 m resolution. This is useful for micro‑locations (storefront clusters, station forecourts, plazas). Area‑level averages are still available when that view is appropriate.
Access provisioning, region setup, optional migration of saved areas as templates, and short role‑based training. All users are able to reproduce common analyses shortly after onboarding.
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