RetailNext alternatives: 5 options compared for European retail and shopping centres

What RetailNext does well

RetailNext is a mature analytics platform built only for physical retail: founded in 2007, headquartered in Campbell, California, and used by more than 600 retailers in over 100 countries, according to its own website.

Its platform rests on the Aurora sensor, a single ceiling-mounted device designed and manufactured by RetailNext that combines people counting, behavioural analytics and high-resolution video. RetailNext states 95-99% counting accuracy and says every installation is audited manually. On top of the sensor it offers Traffic Analytics, Insights (test-and-learn for layouts and displays), Asset Protection (loss prevention with POS exception reporting) and Pulse AI, a conversational layer for asking questions about store data in plain language.

It also has real weight in Europe. RetailNext acquired the Retail Performance division of Ipsos, which it describes as the UK's leading people counting specialist, and it lists an office in Milton Keynes. Its Benchmarks Hub covers traffic data across North America, EMEA and APAC. Aurora is described as SOC 2 Type II compliant, with GDPR-compliant configurations and no personally identifiable data stored.

Sectors on its site include apparel and footwear, department stores, jewellery, convenience stores, restaurants, retail banking, facilities and shopping malls. For a large retail chain that wants one vendor for counting, journeys and loss prevention, it is a serious option.

Why buyers look for RetailNext alternatives

Buyers usually look at RetailNext alternatives for structural reasons rather than a single missing feature: the hardware model, existing cameras, where the vendor operates, the privacy architecture and the sectors it covers.

• Dedicated sensor or existing cameras. RetailNext is explicit that its counting runs on its own device, quoted below. If your stores already have suitable IP cameras, a platform that reuses them changes the hardware budget and the rollout plan.
• Presence in your markets. For a multi-country European rollout, local support, partners and language matter as much as the product.
• Privacy architecture. Every vendor here describes anonymous counting, but some offer optional gender and age estimation. Your DPIA needs to know exactly what is processed and where.
• Sector breadth. RetailNext is retail-first. Shopping centre landlords, cultural venues, banks and transport hubs may want one platform across very different spaces.
• Integrations and total cost. POS, workforce management, BI and single sign-on, plus hardware, installation, licences and support over three years.

“Aurora® is a complete, self-contained sensor that consolidates traffic counting, video, and analytics into one ceiling-mounted device, so it doesn't depend on your existing cameras”

RetailNext, Aurora sensor FAQ, consulted 14 October 2026

The same FAQ adds that existing analogue or IP cameras are supported through RetailNext Asset Protection's video management. In other words, the cameras you own can feed video workflows, while counting relies on Aurora.

Comparison table

The table compares RetailNext and five alternatives on the criteria buyers use in RFPs, with facts taken from each vendor's own website on 14 October 2026. It describes published capabilities, not tests we ran. For a broader ranking of the market, see our people counting software comparison.

A blank or "not specified" cell means the vendor's public pages did not state it on the date checked. It is a question for your RFP, not a verdict.

The alternatives

Each alternative is described with the same three points: what it is, where it fits best and what to check in your evaluation.

Flame Analytics

Flame Analytics turns the IP cameras a site already has into counting and behaviour sensors. Hypersensor connects over RTSP, works with major camera brands, and Flame states over 99% people counting accuracy. It reconnects detections across cameras without biometrics, personal identifiers or image storage, supports single sign-on, and also ingests data from existing counters, WiFi and POS. For a single site with suitable cameras, Flame says live counting typically starts within 5-7 business days.

Its customers span very different spaces: the CaixaForum network of cultural centres, with more than 250 sensors, the shopping centres of Merlin Properties, and IKEA stores in Mexico.

Best fit: European retailers and shopping centre operators with existing CCTV, multi-sector portfolios, and strict GDPR requirements. Check: cameras need at least 720p and a top-down or angled position, and accuracy depends on camera quality, placement and calibration, so audit your cameras first.

“Data helps us adapt, make better decisions and stand out in an increasingly competitive environment.”

Digital Transformation Director for Shopping Centers, Merlin Properties, case study on flameanalytics.com

V-Count

V-Count designs its own 3D active stereo vision sensors, which process data on the device and send only anonymous counts to its BoostBI cloud platform. It states up to 99% accuracy for entrance counting, staff exclusion and counting in complete darkness, and reports more than 600 customers, including 11 Fortune 500 companies, in 130+ countries through 150+ partners. BoostBI connects to sales data through connectors and a REST API, and V-Count publishes its pricing on its website.

Best fit: retailers without suitable cameras who want a dedicated sensor and published pricing. Check: one sensor per entrance to install, and whether optional gender and age analytics will be enabled, which your DPIA must cover.

FootfallCam

FootfallCam has made people counters since 2002 and states that its systems are designed and manufactured in the UK. Its in-store analytics run on the Pro3 sensor, which combines stereo vision and AI video. Its privacy-first AI page describes masking at chip level, processing on the device and an on-premise deployment option. For supermarkets it also offers a package that reuses existing CCTV to measure queues, loss risk and aisle performance.

Best fit: UK and European operators that want one vendor for hardware and software, or need on-premise hosting. Check: which use cases need FootfallCam hardware and which can run on your cameras.

ShopperTrak (Sensormatic Solutions)

ShopperTrak Analytics powers Sensormatic's people counting for retail spaces ranging from small temporary kiosks to large malls and concert venues. It uses overhead counting devices, an Employee Exclusion solution to remove staff from counts, real-time occupancy, and Brand Vitality Meter, built with HappyOrNot. Sensormatic states that 70% of the top 100 retailers worldwide rely on it, and it runs local sites for several European countries.

Best fit: large chains already using Sensormatic for loss prevention or RFID that want traffic data in the same ecosystem. Check: privacy architecture and data location, which the pages we consulted did not detail.

Xovis

Xovis builds Swiss-made 3D sensors with embedded processing, states counting accuracy of up to 99%, and says data leaves the sensor as metadata such as coordinates "without any type of biometric or personal information". Sensors can work together to track paths across large areas, and AI extensions add attributes such as gender and apparent age. Its range also includes sensors for passenger counting on buses and trains, and its retail offer is delivered together with partners.

Best fit: large, complex spaces where precise flow tracking matters. Check: which partner provides the analytics software and support in your country.

How to run a fair evaluation (RFP checklist)

A fair people counting evaluation tests every shortlisted vendor in your own stores, against the same manual count, under the same privacy and cost rules. Use these eight steps:

1. Pilot in two or three stores with different entrance types (mall unit, high street, wide entrance) for at least four weeks.
2. Measure accuracy against a manual count at busy and quiet times. RetailNext says it audits every installation manually, and V-Count advises buyers to "check any people counter against a manual count at busy and quiet times before you rely on the data".
3. Compare claims on equal terms. RetailNext's solution comparison puts repurposed security cameras at 75-85% accuracy; Flame Analytics states over 99% for Hypersensor. Only a pilot in your stores settles it.
4. Complete a DPIA under Article 35 of the GDPR: what is processed, whether any demographic or biometric feature is enabled, where data is stored and which subprocessors are used.
5. Audit your infrastructure: camera resolution and angle, network capacity, and where new sensors would need cabling.
6. List the integrations you need: POS, workforce management, BI and single sign-on.
7. Get the deployment plan in writing, with dates per store and who installs and calibrates.
8. Calculate a three-year total cost: hardware, installation, licences, support and replacements, and ask for references in your country and sector.

Frequently asked questions

Sources

All vendor facts were checked on each vendor's own website on 14 October 2026. Flame Analytics figures come from flameanalytics.com. If a vendor updates its site, the facts above may change: tell us and we will update this comparison.