Looking for a Placer.ai Alternative? Compare Vemcount

Placer.ai and Vemcount produce their numbers in different ways. Placer.ai states that its panel is made up of tens of millions of mobile devices, that the data comes from mobile application providers, and that it is aggregated and extrapolated with proprietary algorithms and machine learning to provide estimates of visits. Its Trust Center compares the method to a pollster who uses a sample to generate insights about a much larger population. Vemcount from Vemco Group does not sample. A sensor above the entrance counts each person who walks in or out, the count is produced on the sensor, and no images or video are stored. A sample can describe places where you have no equipment, including your competitors. A count describes your own building, person by person. Neither replaces the other.

Vemcount accuracy is a contractual minimum of 96 percent, typically 98 to 99 percent, verified against manual counts at the customer's own entrances. Placer.ai describes its accuracy in a different way. It says it uses a panel of tens of millions of devices and statistical analysis, and that it continuously validates its modeled foot traffic data against ground truth data. An accuracy percentage per location is not published on the pages we read, so ask Placer.ai how accuracy is stated for your sites and whether it is part of the agreement. This matters when a number carries money: turnover rent, a marketing fee per visitor, a staffing budget or a bonus. For those decisions, ask every supplier for the figure they will sign, and check it against a manual count at your own door.

Vemcount measures per entrance, per zone and per hour, for as many doors as the building has. You see which entrance carries the traffic, which zones people visit and how long they stay. Placer.ai's feed documentation lists data for venues, complexes, chains and billboards, with visits by hour of day and by length of stay. Data per entrance or per zone inside a building is not published on the pages we read. Placer.ai also states that it only shows data for locations with more than 50 unique devices. If you run small units or stores inside a mall, ask any supplier how your own locations are covered. Placer.ai describes its coverage as locations in the U.S. Vemcount is used in 98+ countries.

Vemcount shows counts live on the dashboard, within seconds of a person passing the sensor. That is what occupancy limits, queue alerts and staff calls need. Alerts go by SMS, WhatsApp, webhook or MQTT, so a full zone can trigger a message, a screen or a building system while the visitor is still there. Placer.ai states that its data refreshes daily and describes its trends as near real-time, and its feed documentation gives a default 2-day lag for daily deliveries. Daily data is well suited to trends, benchmarks and market reports. If your case needs an action within seconds, such as opening a checkout or holding an occupancy limit, ask each supplier how fast the data arrives. Vemco Group also monitors sensor health: gaps are flagged, and estimated data is marked as estimated until real values replace it.

You need measured counts when a number has to hold for one building, one entrance and one hour. Vemcount from Vemco Group is built for these cases:

• Sales conversion: visitors per store and per hour, matched with POS transactions.
• Staffing: the rota follows the real traffic per hour.
• Occupancy and safety limits: a live count of the people inside.
• Leases and tenant reports: footfall per entrance or per tenant as a figure that landlord and tenant both accept.
• Marketing: the effect of a campaign at your own doors, day by day.
• Small and indoor units: a kiosk, a store inside a mall, a floor in an office.

Vemcount accuracy for these counts is a contractual minimum of 96 percent, typically 98 to 99 percent, verified against manual counts. Estimates from a device panel answer other questions, covered in the next tab.

Location analytics is the right tool when the question is about places you do not operate. Placer.ai describes these uses itself: a True Trade Area that shows the geographic area visitors come from, comparison of trade areas and foot traffic with competitors, rankings of locations within a chain, site selection, and a Void Analysis report that lists prospective tenants for a shopping center. A sensor cannot do this, because a sensor only counts where it is installed. Vemcount does not estimate visits to locations where no sensor is installed. The two fit together. Use location analytics to choose a site, understand the catchment and benchmark the market. Use Vemcount to measure what happens at the entrance and inside once the doors are open. Both offer an API, so the two data sets can meet in your own BI tool.

Measured counts become more useful when they are joined with other data from the same building. On Vemcount the sales module connects POS data, with 19 POS integrations (any other POS can push sales data through the REST API), and calculates conversion per store and per hour. VemTrack adds heatmaps, paths, zones and dwell time. VemTenant collects tenant sales for shopping centres, VemLease manages leases, VemSpace covers occupancy and indoor climate, and VemFusion handles integrations, with an open API included in the licence. Our own development team builds the platform, so when you need something adapted, we can do it. Placer.ai's scope is different. It offers a platform, an API and data feeds with visit, audience and market data, a marketplace with integrations such as Snowflake and ArcGIS, and a Retail Sales Report with sales estimates at store and chain level. Connecting a customer's own POS, tenant sales collection and indoor climate are not published on the pages we read.