V-Count vs RetailNext:Choose the Right Fit for Your Stores
Choose V-Count Nano AI and BoostBI for entrance measurement, conversion analysis and weekly store-manager guidance. Evaluate RetailNext when your brief also calls for integrated video and asset protection. Compare the installed configuration, data connections and complete price before deciding.
See V-Count in a Live Demo →V-Count Editorial · Reviewed 19 September 2026
A V-Count-authored comparison using linked primary vendor sources.
Two Platforms, Different Buying Priorities
Both vendors supply their own hardware and analytics. Start with the decisions your store teams need to make and the functions your quote must include.

*Nano AI specifications refer to people counting. Validate coverage, lighting and traffic at the intended mounting position; optional demographics and staff-exclusion functions can have different operating requirements. Source ↗ · Source ↗.
Compare the Configuration You Will Actually Use
A published feature is not automatically enabled in every package. Ask both suppliers to confirm the quoted model, software functions and acceptance test.
| Buyer requirement | V-Count: Nano AI + BoostBI | RetailNext: Aurora + platform |
|---|---|---|
| Hardware | Nano AI: dedicated 3D people counting with onboard processing. Source ↗ | Aurora: stereo analytics, edge processing and video capabilities. Source ↗ |
| Counting accuracy | Up to 99%; validate your entrance and counting rules. Source ↗ | Published range of 95–99%, with installation audits. Source ↗ |
| Mounting and coverage | 2.2–7 m for Nano AI people counting. Confirm width, lens coverage and optional-feature limits. Source ↗ | Confirm height, lens and coverage for the quoted Aurora model; the reviewed brief does not give a maximum. Source ↗ |
| Counting in darkness | 0 lux using built-in infrared LEDs. Source ↗ | Minimum lux is not specified in the reviewed brief; ask for the proposed low-light configuration. Source ↗ |
| Staff exclusion | Three methods; select the compatible method and BoostBI sublicence. Source ↗ | Staff exclusion is available; the Aurora brief describes UWB. Source ↗ |
| Gender and age | Gender and age estimation in the same Nano AI sensor, with the appropriate configuration and licence. Source ↗ | Gender demographics documented; age estimation not confirmed in the reviewed sources. Source ↗ |
| Manager guidance | AI Sales Coach: weekly store-specific guidance in BoostBI. Source ↗ | Pulse AI conversational analytics and staffing predictions are documented. Source ↗ |
| Privacy and data flow | On-device processing with non-identifiable analytics outputs. Review integration data, retention and access. Source ↗ | Configurable privacy controls and video functionality. Review the configuration and retention. Source ↗ |
| Commercial model | Hardware purchase + BoostBI per-sensor subscription, including selected sublicences. Source ↗ | Subscription includes Aurora hardware; site-specific services can add cost. Source ↗ |
| Integrations | Native Shopify and Nebim; other working integrations and scoped REST API connections. Source ↗ | POS integrations and API access documented; confirm specific systems. Source ↗ |
Unspecified means the reviewed source does not establish the detail, not that a vendor lacks the capability. Counting accuracy is separate from demographic or staff-exclusion accuracy.
Turn Better Visitor Data Into Store Decisions
V-Count brings entrance measurement and an actionable reporting workflow together. These are three benefits to demonstrate with your own retail team.

Keep Staff Movements Out of Customer Counts
Where staff repeatedly cross the entrance, V-Count’s three exclusion methods give you options for protecting the visitor denominator. Choose the method that fits your team and validate it separately from total crossing counts.

Measure Entrances With Changing Light
Nano AI’s built-in infrared LEDs support people counting at 0 lux. Include your darkest trading conditions in the test and confirm coverage at the proposed height, especially where a high ceiling or wide doorway affects placement.

Give Managers a Weekly Next Step
BoostBI’s AI Sales Coach uses available store data to provide weekly guidance. Managers can choose a staffing or conversion action, review the result and keep improving the operating routine.
Connect Footfall With the Systems You Already Use
For conversion reporting, V-Count supplies the visitor measurement and connects it with compatible sales data in BoostBI. Native Shopify and Nebim connectors are available; VendPOS, Nayax, ImagineX and QuickBooks are working integrations. Manual sales import and scoped REST API connections provide further routes. Review BoostBI integration options.
RetailNext also documents POS integration and API access. Confirm the supported system and fields rather than treating “has an API” as proof that a particular loyalty, inventory or ERP workflow is ready. Footfall is anonymous visit data; matching it to named loyalty customers would be a separate project with its own data requirements.

Agree the reporting rules before comparing results
Purchase conversion = eligible purchase transactions ÷ eligible store visits × 100. Match store IDs, time zones and complete reporting periods. Define returns, cancellations, repeat entries, staff exclusion and group counting consistently. Visit counts do not automatically represent unique shoppers.
BoostBI typically refreshes every 10 minutes; enabled real-time configurations can refresh as frequently as every minute. POS arrival time is separate. Confirm data-gap handling, historical imports, export formats and who supports each connection before the rollout.
Compare the Same Entrances Over the Same Term
V-Count’s public ranges are $299–$799 per sensor, one-time, and $9–$49 per sensor per month for BoostBI. The quoted BoostBI rate includes the selected sublicences; API access, staff exclusion, demographics, queues and heatmaps are not all enabled at every price point. Check current V-Count pricing and request a configuration-specific quote.
RetailNext’s current estimator calculates a subscription from store locations, entrances, industry, region and existing technology. Aurora hardware is included. Its pricing page identifies installation, custom mounting, cabling and custom integrations as possible additional costs. Use the RetailNext pricing source for current inclusions.
Comparable project cost = hardware not included in the subscription + installation and site work + subscription over the agreed term + integration and support charges + applicable delivery and taxes.
Ask for these assumptions in writing
- Coverage: stores, entrances, width, mounting height, sensor quantity and any separate zone or queue coverage.
- Power and network: Nano AI’s 5V supply and external PoE option, mounting accessories, cabling and site readiness.
- Reporting: enabled analytics, API rights, POS connector, historical data, exports and refresh frequency.
- Commercial terms: currency, billing period, minimum term, renewal, hardware ownership, warranty and any installation or integration charges.
- Support: remote and onsite responsibilities, response targets, regional coverage and handover training.
Use the people-counting provider buyer guide for a broader shortlist and a consistent requirements checklist. V-Count can turn that checklist into a Nano AI and BoostBI proposal for your stores.
Prove the Fit at a Representative Entrance
- Agree the objective. Choose traffic reporting, staffing, conversion or another defined decision. Select the V-Count hardware and BoostBI functions needed to support it.
- Check the site. Record height, width, lighting, obstacles, power and connectivity. Confirm mounting and coverage before installation.
- Validate the counts. Compare entry and exit events against the same independently observed reference, including peak traffic, groups and staff crossings. Record missed and extra counts separately.
- Reconcile the reports. Test POS mappings, time periods and exclusions. Agree acceptable data completeness and who fixes missing information.
- Plan the handover. Confirm historical-data export rights, the existing contract, support contacts and manager training before expanding to more stores.
A pilot determines your installed performance. Neither a product headline nor a customer story establishes a guaranteed conversion uplift for a new retailer.
V-Count vs RetailNext: Buyer Questions
Which shopper analytics solution fits a mid-sized retailer?
Which RetailNext-style analytics features should a small retailer prioritise?
How do V-Count and RetailNext integrate with POS, loyalty and inventory systems?
How do ShopperTrak, RetailNext and V-Count compare for retail analytics?
How should I compare FootfallCam with V-Count and RetailNext?
How should I compare V-Count and RetailNext pricing?
Can I move from RetailNext to V-Count?
Primary Sources Behind This Comparison
Reviewed 19 September 2026 by V-Count Editorial. Pricing and product scope may change. Confirm the named model and selected functions in a current proposal.
- V-Count Nano AI product information
- BoostBI capabilities and integrations
- V-Count pricing
- People-counting provider buyer guide
- RetailNext Aurora sensor
- Aurora technical product brief
- RetailNext pricing and inclusions
- RetailNext Traffic Analytics
- RetailNext demographic feature summary
- RetailNext platform and AI comparison
- FootfallCam V9 integrations
- Sensormatic ShopperTrak Traffic Insights
See V-Count on Your Own Store Requirements
Bring your entrance dimensions, reporting goals and POS system. We’ll show you how Nano AI and BoostBI can support your next store decision.