Visitor analytics for museums & cultural venues

Museum visitor analytics from Bumbee Labs shows cultural venues when visitors come, how long they stay in each exhibition and how many reach the shop and café. Wi-Fi across the galleries counts them, with 3D sensors at entrances for precise counts. Bumbee Labs is the company behind the only footfall method in Europe approved by a data protection authority.

The short version

• Visit counts and dwell time for every gallery, exhibition and exhibit, with a temporary show measured as its own space.
• The museum shop and café are zones too, so you see how many visitors reach them and how long they stay.
• Wi-Fi covers the galleries and halls, and 3D sensors add precise counts at entrances and in rooms where Wi-Fi coverage is uneven.
• Exportable, board-ready reports for funders come from the same anonymous data, with API access.
• Below: seven questions museums ask, from which exhibitions earn their space to which figure goes to the funder, and ten shorter ones.

What do museums and cultural venues ask visitor analytics to answer?

Which exhibitions earn their floor space?

A museum sees which exhibitions earn their floor space by giving each gallery, hall and exhibit its own visit count and dwell time, next to the total for the building. You see which exhibits people linger at and which they pass, and where the hot and cold zones are when you place exhibits.

Because dwell is measured per gallery, curators can also see whether a re-hang or new interpretation changed how long people stay, and the mix and placement of exhibits and events can follow the same figures. The insight on museum dwell time covers what galleries learn from it.

What did the temporary exhibition give the museum?

A museum measures a temporary exhibition as a zone of its own, so the show gets its own visit count and dwell time, plus the attendance lift it created for the whole venue. That puts it directly beside the permanent collection, or the same season last year, the way benchmarking footfall compares like with like.

When the show is promoted, campaign and event impact is overlaid on the venue total, so the campaign’s effect on attendance is read against the same figures. The page on how to measure event impact covers the method.

How many of our visitors get to the shop and the café?

The museum shop and the restaurant or café are measured as zones, like any gallery. For each one you see the number of visits, the share of the museum’s visitors who reach it and how long they stay, counted across the building with Wi-Fi people counting.

Paths between zones show which galleries visitors pass through on the way there, and peaks per zone show when the shop and café are busiest, which helps when planning staffing and opening hours.

Are visitors missing the east wing?

Flow data shows how visitors move between the galleries and halls of a museum, including any wing they reliably miss. Signage and routing can be adjusted, and the effect measured by comparing flows and dwell before and after the change, with hot and cold zones on a gallery heatmap.

Changes made for visitor flow, comfort or safety can be checked with the same comparison.

Which visitor figure do we send to our funder, and will it hold up?

The figure to send is one whose counting the museum can explain. Automated counting produces the auditable visitor numbers funders already require, calibrated against manual control counts, and splits them by exhibition, by season and by programme type. Visitor figures for funders covers the reporting side.

Bumbee Labs delivers these as exportable dashboards and board-ready reports showing real visitor numbers per gallery or hall, in a format funders and grant bodies accept, so annual funder reporting rests on measured evidence. Footfall data lists the full metric catalogue.

As a publicly funded institution, a museum often shares its funders and its privacy requirements with libraries and cities & municipalities.

Do café and shop guests count as museum visitors?

Whether they count depends on the definition a funder uses, and a museum can report both. Zone-based counting keeps the building total apart from the visits to each exhibition, with the café and the shop as zones of their own, so the visitor count can be given in either form.

How do we staff gallery hosts and volunteers around the visitor peaks?

Visitor peaks by hour, day and season, and per zone, show when a museum needs hosts and volunteers on the floor and when the galleries are quiet, so opening hours and staffing follow real demand. The counts reach your planning tools through the analytics platform & API.

Staff planning with footfall data shows how a roster is built from the hourly pattern.

Which other visitor questions do museums ask?

• How do we fill in the national museum statistics? The same measurement can answer each framework’s definition, such as visits to the building or to an exhibition; see Museum attendance in numbers for how the definitions differ.
• Do we measure up against other museums? Compare visits per open hour, dwell time and season with your own history; Museum attendance benchmarks explains how to compare like with like.
• What numbers go in the press release and to the sponsor? Visits, dwell time and the attendance lift per exhibition, read against the same figures as the campaign; see promotional figures for exhibitions.
• Does a school class count as one visit or thirty, and when does it arrive? Frameworks count school groups differently, and counting every entrance and open hour shows a school visit as a peak by hour.
• Free entry means no tickets and no figure. Automated counting at every entrance gives a free-entry museum a visitor figure without tickets, and it replaces manual counts and estimates with auditable numbers.
• Does staying open in the evening pay off? Peaks and trends across the day and the season let opening hours follow demand, and a before and after comparison shows what the later hours added.
• A queue builds around one popular work. If the queue backs up into neighbouring galleries, moving the work or changing the flow around it can redistribute visitors before congestion drags down the rest of the visit, and the same comparison shows whether it worked; see queues, crowding and capacity.
• Is it the same audience coming back? Repeat visits (with visitor opt-in) show whether attendance is driven by new or returning visitors.
• Do rainy summer days fill the museum? Weather and school holidays move attendance, so a fair comparison sets the same weeks against each other.
• Is our audience local or from out of town? That is a catchment question, and the insight on where visitors come from shows how a venue reads its catchment from mobile network data.

Is a people counter enough for a museum, or do you need visitor analytics?

A people counter is enough when the only question is how many people came in. For a museum that has counted by hand, that is real progress: a continuous total in place of clickers and estimates, and a headline figure that meets a funder’s reporting requirement. Museum visitor analytics answers the questions that follow: which exhibitions earned their space, how long visitors stayed in each gallery, which rooms they walked past, how many went on to the shop or café, and whether attendance is driven by new or returning visitors (with visitor opt-in). Flow and dwell data tell a curator which galleries pull their weight and where the visit stalls.

Those questions shape next season’s programme and the next funding round. A single count at the door cannot answer them; that takes zone-level measurement of dwell, flows and repeat visits (with visitor opt-in). With zone-based measurement both come from the same anonymous data: the total for the annual report, and the gallery-by-gallery detail behind programming, layout and staffing decisions. People counter vs analytics sets out when a simple counter is enough and when analytics pays off.

Should a museum count visitors with Wi-Fi or with 3D sensors?

Bumbee Labs combines the two. Wi-Fi people counting reads aggregate movement across the galleries and halls and turns it into statistics about how each space performs: the flows between galleries, dwell time per exhibition, and where queues and crowding form. 3D sensor counting adds precise counts at entrances and in specific rooms where Wi-Fi coverage is uneven. Both methods count anonymously and no one is identified. Wi-Fi counting captures no images, and where a 3D sensor counts, video is processed for analytics only and no personal images are stored. With peaks and trends visible across the day and the season, opening hours and staffing can follow real demand. How to count visitors compares the methods.

What should a museum look for in a visitor analytics platform?

Six criteria separate a museum analytics platform that a publicly funded body can defend from one it cannot:

1. Anonymity with regulatory approval. Many vendors say “GDPR-compliant”; approval by a data protection authority is a stronger assurance, and the one a publicly funded body can point to.
2. Zone resolution down to gallery, hall and exhibit. An entrance total cannot compare exhibitions; zone-level counting shows visits and dwell per space.
3. Funder-ready reporting. Exportable, board-ready reports built on measured, auditable numbers.
4. API access, so attendance data reaches the institution’s own reporting and planning tools.
5. A mix of methods. Wi-Fi covers whole galleries and halls, and camera or sensor counting adds precision at entrances and in specific rooms where coverage is uneven.
6. Calibration against manual control counts. Figures reported to funders have to hold up to scrutiny, so the platform should validate its counts and say how.

Can museum visitor analytics handle a school visit or a blockbuster opening?

Yes. The approach is proven at scale at Hovet Arena in Stockholm, where the same zone-based measurement handles intense break-time surges. In a museum the surge is a school visit or a blockbuster opening, and the KPI is engagement; at an arena it is concession sales. In both, what is measured is anonymous flows between zones.