Nano Prime Heatmap &
Zone Analytics

Nano Prime is V-Count's indoor wide-area sensor. It supports zone measurement, heatmaps, dwell and visitor flow, with the appropriate coverage, configuration and licence. This guide focuses on the practical side: how to plan coverage, set up zones and grids, check data quality, and turn the output into tested decisions.

What Nano Prime measures, in plain words

Nano Prime looks down on an area of floor from the ceiling. It tracks where visitors are over time and processes this on the device. The platform then shows four things:

1. Zone visitor counts: how many visits each department or area got.
2. Zone dwell time: how long visitors stayed in each area.
3. Heatmap: as the page above explains, a projection of total dwell time onto your store layout.
4. Visitor flow: the most and least popular paths between zones.

Measured movement shows where visitors travelled or stayed. It does not reveal intent, and it does not prove why someone left an area.

Planning coverage

The page above states that a single Nano Prime can cover 120 square metres from a height of 4.5 metres. Treat this as a planning reference, not a promise for every room. Real coverage depends on ceiling height, the shape of the space and what might block the view.

Use these steps to plan:

1. Mark the areas that matter. Start with the zones linked to decisions, not the whole building.
2. Measure ceiling heights. Heights can vary across a store, especially near mezzanines or bulkheads.
3. Map obstructions. Note tall fixtures, hanging signs, lights and beams.
4. Check power and network access at each candidate mounting point.
5. Send us your floor plan and photos. A simple drawing and a few photos from your store manager are enough. We’ll recommend the final sensor count and positions within 24 hours.

Fewer, well-placed sensors are better than many sensors placed without a plan.

Working with the grid system

The page above describes a high base resolution and a grid system. This lets you zoom into small sections and compare attraction levels grid by grid. Nano Prime can even record attraction duration for a specific product or item.

Grid detail is powerful, but it needs discipline:

• Use fine grids for specific questions, such as a single fixture or a feature table.
• Use larger zones for regular reporting. They are easier for store teams to read.
• Do not compare a fine grid in one period with a large zone in another.
• Keep a dated record of every grid and zone layout.

Nano Prime and entrance counting

Nano Prime answers "what happened inside?". An entrance counter such as Nano AI answers "how many came in?". Most stores need both.

With both in place, you can relate zone visits to total store visits. For example, zone share of store visits = zone visits ÷ eligible store visits × 100, over the same period. Store conversion still uses the standard formula: eligible purchase transactions ÷ eligible store visits × 100.

Setup checklist

• Agree the business questions and the owner of each zone.
• Send your floor plan and a few store photos covering height, field of view, obstructions, power and network. You’ll get the placement plan back within 24 hours.
• Confirm the licence. Heatmaps are a separately selectable sublicence.
• Draw zones along real fixtures and aisles.
• Walk each boundary and check that positions land in the right zone.
• Choose a staff exclusion method: lanyard, shoulder tag or mobile app. Test staff movement separately.
• Agree acceptance criteria for zone counts and dwell before go-live.
• Record the start date, zone plan and rules.

Data quality checks in the first weeks

• Coverage gaps: an area that always shows zero may be outside the view.
• Edge effects: visits that jump between two zones may point to a boundary drawn through a busy aisle.
• Staff patterns: long dwell before opening or after closing suggests staff are not excluded.
• Time gaps: missing hours can come from power or network breaks.
• Sense check: service points and tills are usually busy. If they look quiet, check the setup.
• Layout changes: a new fixture can block part of the view. Re-check coverage after every refit.
• Reference check: observe a zone for a short period at a busy time and compare with the report.

Where Nano Prime is useful

Wide-area measurement helps most where a door count cannot tell the full story:

• Large open-plan stores: compare departments and find areas visitors skip.
• Showrooms: see which displays draw visitors and how long they stay.
• Lobbies and halls: understand how people move through a shared space.
• Waiting areas: see when an area fills up and how long people stay.
• Department stores and malls: compare activity across floors and sections.

If you need live occupancy for a whole area, remember the limits. Occupancy reporting needs coverage of all relevant entrances and exits, an agreed baseline and checks for drift or missing data. Counting does not replace venue safety procedures or set a safe capacity.

Thinking of zones like web pages

The page above compares a store to a website, with each zone as a page. This is a helpful way to frame your reports:

• Store visits are like site visits.
• Zone visits are like page views.
• Dwell is like time on page.
• Visitor flow is like the path from page to page.

The comparison has limits. A website knows which page led to a sale. A store sensor does not link a purchase to a path. So use sales by category and zone data side by side, and test your ideas.

Testing product placement with Nano Prime

The page above mentions A/B tests for product placement. Here is a simple way to run one at fixture level:

1. Pick one product or fixture. Set a fine grid or small zone around it.
2. Record a baseline. Measure visits and attraction duration for full weeks of normal trading.
3. Move one thing. Change the position, height or neighbour of the product. Change nothing else if you can.
4. Measure an equivalent period. Match weekdays, opening hours and season.
5. Check sales for the item or category over both periods.
6. Log outside factors. Note promotions, stock gaps, weather and staffing.
7. Decide. Keep, reverse or refine the change, and record why.

If you run the same test in two similar stores, you can compare them. One store changes. The other stays the same as a control. This makes the result easier to trust. Even so, a before-and-after change is not proof of cause.

Reading dwell time well

Average dwell can hide what is really going on. Look at the spread as well:

• Many short stays: visitors pass through. The area may work as a corridor.
• A mix of short and long stays: some visitors engage, others move on.
• Many long stays: strong engagement, or a queue, or a slow service point.

Agree the cut-off times for short, medium and long before you report. Keep them the same over time.

Linking Nano Prime data to sales

BoostBI can bring zone data and sales data together. It has native Shopify and Nebim connectors and working integrations for VendPOS, Nayax, ImagineX and QuickBooks. Manual sales import and a scoped REST API are also available.

Map each zone to the product categories it holds. Then compare category sales with zone visits and dwell over the same closed period. POS import timing is separate from traffic refresh, so check that both data sets are complete.

Using zone data for pricing and marketing reviews

The page above also mentions price and marketing decisions. Zone data can support these reviews, with care:

• Price changes: watch visits and attraction duration at the fixture, next to item sales. Movement alone cannot tell you whether a price is right.
• Campaign displays: check whether the display zone gets a larger share of store visits during the campaign than before.
• Seasonal areas: set a temporary zone, measure it for the season, then remove it and note the dates.
• Signage: test new signs one at a time, and measure flow into the target zone.

In each case, compare equivalent periods and log outside factors. Treat results as evidence for the next decision, not as final proof.

Rolling out across several stores

1. Finish the pilot and write down what worked: sensor positions, zone types and rules.
2. Build a standard zone template for each store format.
3. Send a floor plan and photos for each new store. Ceilings and fixtures often differ, even within one format.
4. Validate zones in each store before adding it to chain reports.
5. Compare stores on shares and trends, not on raw zone totals, unless the zones match.
6. Review the template once a year, or when you change store layouts.

The AI Sales Coach in BoostBI can add targeted weekly suggestions from each store's data. Managers review, act and compare the KPI later. It is AI-generated guidance, not a guaranteed uplift.

Reports for different roles

• Store managers: busy zones by hour, to place staff where visitors are.
• Merchandisers: zone share and dwell by category, to review space and placement.
• Marketing teams: visits and dwell at campaign displays during the campaign.
• Property teams: movement across floors, corridors and common areas.

Visits per labour hour can show workload in a zone. It does not describe how well an individual works.

Common mistakes to avoid

• Applying the coverage reference to every ceiling without checking the floor plan and photos.
• Drawing zone lines through the middle of busy aisles or fixtures.
• Changing grids or zones during a test.
• Reading long dwell as proof of interest.
• Leaving staff in the data.
• Comparing stores with different zone plans as if they were the same.
• Expecting zone data to explain why a visitor did or did not buy.
• Forgetting that POS import timing is separate from traffic refresh.
• Reporting fine grid results to teams who need simple zone summaries.

Keeping the setup accurate over time

Stores change. Fixtures move, ranges change and seasonal displays come and go. After each refit, check coverage and zone boundaries again. Take a short reference observation in the busiest zones. Log the date of every change, so later comparisons use the right zone plan.

Privacy and data handling

Compatible sensors process measurements on the device and send analytics outputs to the platform. Technical features alone do not establish regulatory compliance. Review data flows, access, retention and connected systems before rollout.

Frequently asked questions

Short answers on planning and using Nano Prime.

How many Nano Prime sensors will I need?

It depends on the floor area, ceiling heights and obstructions. Use the coverage reference above for a first estimate. Send your floor plan and a few photos, and we’ll confirm the final number and positions within 24 hours.

Can Nano Prime count store entrances too?

Nano Prime is built for zones, heatmaps, dwell and flow. For store visit totals, count every relevant entrance with an entrance counter such as Nano AI.

Which licence do I need for heatmaps?

Heatmaps are a separately selectable sublicence. Pricing is per sensor. Check the full quote, including hardware, software, installation, integration and support.

How fresh is the data?

BoostBI typically refreshes reports every 10 minutes. Enabled real-time configurations can refresh as often as every minute.

Can I export zone data?

Yes. A scoped REST API is available, and V-Count provides the documentation. Confirm fields, timing and access before you build reports.

Can I change zones after go-live?

Yes. Zones are set in configuration, so you can adjust them as questions change. Record the date of every change. Compare periods only when they use the same zone plan.

Does Nano Prime work in large halls?

It is designed for wide indoor areas. Coverage depends on ceiling height and obstructions, so we plan the layout for each hall from your floor plan and photos.

How do I get started?

Choose one area and one question. Plan coverage, validate zones and run a clear test. Read more about heatmap and zone analytics, or request a demo to review your floor plan.