A structured review of the RetailNext in-store analytics and asset protection platform for retail analytics, store operations and loss prevention teams: what it does well, where the constraints sit and who should look elsewhere. Every score traces to something RetailNext publishes.
RetailNext is two products under one subscription, and the analytics half is the deep one: traffic, shopper behaviour and merchandising insight with Benchmarks market data, anchored to Aurora, a ceiling-mounted sensor RetailNext designs and manufactures with the analysis running onboard. The asset protection half reads the cameras a store already has, stating compatibility with existing analog and IP camera infrastructure with no forced hardware replacement. Its estimator returns a cost per store per month and per year in under 60 seconds, scaling by store count, entrances per store, store type, global region and current technology setup. It scores lower on retention, because the published figure is up to 30 days of high-resolution color video, and lowest on what happens at the moment of an incident, because the documented response is an alert and a searchable case file. Choose RetailNext when the primary question is shopper behaviour and merchandising. Look elsewhere when the same cameras have to cover safety and operations too.
Five criteria, each scored from RetailNext's own current documentation as of August 24, 2026. Spot AI competes with RetailNext, so no score here rests on an anonymous source, an aggregated user rating or a private benchmark: each one sits next to the documented fact behind it. Anything RetailNext does not document is recorded as not publicly specified rather than assumed. Facts here come from RetailNext's own product, platform, pricing and partner pages. Where RetailNext publishes nothing, this review records the absence rather than filling it from a reseller listing. This is not a paid placement, and RetailNext had no input into it.
One half is an entrance sensor RetailNext builds. The other reads the cameras a store already has. Analytics depth is published in detail; retention and on-site response are where the constraints sit.
RetailNext is two products under one subscription and the split is worth understanding before anything else. On one side sits the analytics platform, anchored to Aurora, a ceiling-mounted PoE sensor that RetailNext designs and manufactures with the analysis running onboard the sensor, feeding traffic counting, shopper behaviour and merchandising insight plus Benchmarks market data. On the other sits Asset Protection, which reads the cameras a store already has. The design target is a chain whose first question is what shoppers do in the store rather than what happens to it after closing.
The analytics half is where the product has depth. RetailNext publishes named retail formats it serves, from apparel and footwear to jewelry, department stores, convenience stores, restaurants, retail banking and shopping malls, and its technology partner programme names Zipline, Brandtrack, Rallyware, Storeforce Solutions and Zebra as partners that extend the platform, connecting traffic and behavioural data to POS systems, workforce management tools and CRM platforms through data sharing and API integrations.
The asset protection half is the one that touches existing hardware. RetailNext states that it is compatible with existing analog and IP camera infrastructure with no forced hardware replacement, and the module blends video with POS exceptions, EAS alarms, door alarms, safe openings, keypad activity and panic buttons into searchable case files, with real-time alerts and investigation stated as up to 75% faster. Video sits in the RetailNext cloud, with up to 30 days of high-resolution color video published as the retention figure.
RetailNext is strongest when the question is what shoppers do in the store, and thinnest when the same cameras are asked about safety, operations or what happens after closing.
Both columns are documented. Nothing here comes from an anonymous review.
Both columns describe documented behavior. RetailNext's column was checked against its own documentation on August 24, 2026.
Swipe the table sideways to see every column.
RetailNext data comes from RetailNext's own public documentation as checked on August 24, 2026. Gaps are marked as not publicly specified.
The honest split, stated the way a shortlist call would state it.
If traffic, conversion, dwell and merchandising are what the business is trying to measure, RetailNext was built for exactly that and the Aurora sensor gives it an accurate front door regardless of what is on the walls. Benchmarks market data then lets the chain read its own numbers against the market rather than only against last year.
If EHS wants spills and blocked exits, operations wants opening routines and stockroom dwell, or the loss team needs something to happen on site while the store is closed, none of that appears in the published scope and the usual result is a second video vendor on the same cameras. Chains whose cases outlive a 30-day retention window are the other case to check early.
Spot AI ships 15+ pre-trained Video AI Agents spanning vehicle break-in, fire, intrusion, personal protective equipment, forklift near-miss, falls and hazard-zone crowding, so a mixed estate gets shipped coverage on both sides. Iris builds anything else in natural conversation in about eight minutes, full-resolution video stays on the Intelligent Video Recorder in the building and the platform is SOC 2 Type II, NDAA-compliant and HIPAA-aligned.
These two platforms have different centres of gravity and the comparison gets clearer once that is said plainly. RetailNext is built around the entrance sensor and the shopper, with asset protection alongside it and the video in its cloud. Spot AI is built around the cameras already in the store, with 15+ pre-trained Video AI Agents spanning security, safety and operations, deterrence through standard speakers and full-resolution video staying on the Intelligent Video Recorder on site.
For a lot of chains the honest answer is both, split cleanly. Aurora keeps counting at the entrance because that is a different job, and the video and asset protection side moves onto a platform that also carries the safety and operations questions. Run one store on both for a fortnight before deciding, and include the stockroom and the back door, because those are the areas an entrance-anchored platform was never pointed at.
Quote both against the identical store list and state plainly whether the traffic and merchandising programme continues. A bundled analytics subscription and a per-camera video subscription are not the same purchase and should not be compared on one line.
See what the AI catches on your live feeds before any platform decision.
Customer-reported outcomes from named Spot AI customers.
Cambridge City cut footage search from two hours to 30 seconds after consolidating seven municipal locations on one platform.
Silver Bay Seafoods replaced fragmented legacy camera systems across 22 locations, including remote Alaska facilities, and lifted operational efficiency 15%.
Unique Industries covers more than a million square feet with a three-person safety team, catching near misses and falls on the cameras already installed.
"Having cameras that talk back to you changes everything. Spot AI has become a real part of our safety team."
Yes, for the right question. It scores 2.9 out of 5 here, carried by deep retail analytics with Benchmarks market data across seven named retail formats, and by an asset protection module compatible with existing analog and IP cameras. It fits a chain whose first question is shopper behaviour and merchandising. Teams whose main problem is what happens after closing should read the retention and response answers first.
For asset protection, yes. RetailNext states that the module is compatible with existing analog and IP camera infrastructure with no forced hardware replacement, so the cameras already in store carry it. The analytics half is different: Aurora is a ceiling-mounted PoE sensor RetailNext designs and manufactures, the analysis runs onboard the sensor and it is stated not to depend on existing cameras. A camera protocol or conformance profile is not publicly specified for either half.
Up to 30 days of high-resolution color video is the figure RetailNext publishes, held in its cloud platform. That is worth checking against how long your own cases stay open, because organised retail crime cases, insurance claims and civil recovery frequently run longer, and footage attached to an open case has to be exported before the window closes rather than after.
Aurora hardware sensors, full platform access on desktop and mobile, all software licensing and updates, an unlimited Aurora hardware warranty covering replacements and technician visits, and Benchmarks market data. The estimator returns a cost per store per month and per year in under 60 seconds, moving on store count, entrances per store, store type, global region and current technology setup. Additional services vary by site requirements, ceiling height, electrical needs and network infrastructure, so installation and integration work sit outside that figure.
It depends which half you are replacing. If entrance counting and merchandising insight are the reason you bought, RetailNext is strong and worth keeping. If the video side has to cover safety and operations as well as asset protection, or full-resolution video needs to stay in the store, a camera-agnostic platform such as Spot AI fits, because 15+ pre-trained Video AI Agents run on the cameras already installed and video stays on the Intelligent Video Recorder. The alternatives roundup compares five platforms side by side.