A category manager heading into a line review at Walmart needs two things: store-level data she can put in front of a retail buyer, and a field execution program that actually keeps the shelf in shape between resets.
Trax was built to deliver the first, but it wasn’t built to deliver the second. If you need both, here are 5 platforms worth evaluating.
Trax is a shelf intelligence platform built around image recognition and analytics. Its core value proposition is visibility: take images in the store, run AI against them, and produce SKU-level compliance metrics, share of shelf data, and on-shelf availability scores. That data feeds category managers and commercial teams with a clearer picture of what is actually happening across their retail network.
At scale, with 30 of the world’s top 50 CPG companies in its client base and coverage across 80+ countries, it has delivered on that promise for a long time. The platform is designed to measure the shelf and surface what is wrong. That is what it was built to do, and it does it well.
Where teams outgrow it is the gap between seeing what is wrong and fixing it.
Trax identifies the problem, but what happens next — getting the information to the right person, in the right store, in time to change something before the rep leaves — is not part of its native design.
For teams that have moved past the measurement problem and now need to solve the correction problem, Trax is not the right tool for the next stage of their execution program. Those are the teams switching, and the reasons tend to fall into three categories.
The first is the correction gap. Trax tells you what is wrong on the shelf, but getting that information to a field rep in time for her to fix it during the same store visit requires execution workflow infrastructure that Trax does not natively provide. For teams where the problem is shelves not getting corrected fast enough — not just measured — that gap has a direct revenue cost.
The platform breadth question is the second. A category manager who needs compliance data to also feed back into assortment planning and planogram design needs more than a shelf camera. Trax covers the detection layer, but it doesn’t connect into the planning layer. Teams building an integrated execution stack need a platform that closes that loop.
Best overall — AI image recognition with same-visit correction and full platform connectivity.
Store360 is Vision Group’s shelf execution and compliance software.
Here’s how it works: a field rep takes a photo of the shelf, and within seconds the AI identifies every SKU, scores compliance against the planogram for that specific store, flags out-of-stocks, checks pricing accuracy, and returns a prioritised task list. The rep corrects the shelf before leaving the aisle. The fix is verified with a second photo. The correction loop closes in minutes.
What separates Store360 from every other platform on this list is the architecture after the image is processed. InfiViz, Vispera, ParallelDots, and Snap2Insights all produce compliance data that routes to a dashboard. Store360 routes it to the rep standing in front of the shelf with enough time to act on it.
An out-of-stock flagged after the rep has left the store gets corrected on the next visit, but an out-of-stock flagged while the rep is in the aisle gets corrected before she walks out the door.
Beyond execution, Store360 connects directly into Vision Group’s planogram tools (EZPOG, PicToPOG), assortment optimization engine, and demand intelligence layer. Compliance data from field visits feeds back into the next category planning cycle.
Clients include Coca-Cola, Nestlé, L’Oréal (a 30-year client relationship), Mars, Red Bull, Wegmans, Body Armor, Kenvue, Goya, Ferrero, and Henkel. The platform deploys in under 30 days on any mobile device a rep already carries.
✓ Best for: CPG brand teams where the primary problem is shelves not getting corrected fast enough — not just measured. Also the right fit if you need compliance data to connect into planogram and assortment planning.
✕ Not the right fit if: Your primary need is broad market measurement and competitive analytics — coverage without correction.
“The Store360 tool is so powerful. Photos plus reporting make it easy to get store managers to act. They even ask me directly what they should order.”
— Barbara, L’Oréal
“Rep Insights lets our people sell directly in store with data in under 60 seconds.”
— Michael, Nestlé
Strongest analytics depth for category and trade marketing teams.
InfiViz is Infilect’s shelf intelligence platform, deployed across 400,000+ stores in 18+ countries with a particularly strong presence in Asia-Pacific markets. The image recognition engine is trained across general trade and modern trade environments, including the high-density, high-SKU-count shelf conditions that are harder for models trained primarily on Western markets.
P&G, AB InBev, and ITC India are among its active clients.
The platform measures planogram compliance, out-of-stock detection, share of shelf, pricing compliance, and competitive shelf monitoring, and the analytics layer is built for category and trade marketing teams who need this data to support planning decisions. The drill-down from national to regional to store level is well developed, and the dashboards are designed for commercial users rather than technical ones.
InfiViz’s design priority is analytics output, not in-visit execution workflow.
Compliance data produced by InfiViz routes to a dashboard and reporting layer. The correction workflow — who gets the task, when, and how it is verified — is separate from the platform. For a category manager who needs shelf analytics to inform her category strategy, InfiViz delivers genuine depth. For a retail execution director who needs the rep to fix the shelf before leaving the store, the correction loop is not built in.
✓ Best for: FMCG category and trade marketing teams who need detailed shelf analytics for planning and retailer conversations, particularly in Asian and emerging markets where general trade coverage matters.
✕ Not the right fit if: Same-visit shelf correction is your core requirement. InfiViz is analytics-first. It surfaces what is wrong on the shelf; it does not close the loop between detection and correction in the visit.
Accessible AI image recognition entry point for CPG teams.
ShelfWatch is ParallelDots’ AI image recognition platform for CPG shelf execution. Its core capabilities cover planogram compliance, out-of-stock detection, share of shelf, pricing compliance, and POSM verification. The reported accuracy is 95%+ under field conditions, and the model trains on new SKUs within hours rather than days — a meaningful advantage for brands with frequent launches or packaging changes.
A global confectionery manufacturer used ShelfWatch across 200,000+ general trade outlets and recorded a 70% improvement in cooler purity compliance and 80% improvement in planogram compliance. Unilever Ghana expanded its deployment after scaling from 46% to 91% on-shelf availability in the first year. The platform integrates with standard SFA, CRM, and BI tools and operates offline with automatic sync.
ShelfWatch’s commercial positioning is clear: strong IR accuracy, accessible pricing relative to enterprise platforms, and fast SKU setup.
Where it sits closer to an analytics-and-reporting tool than an execution platform: the data outputs go to dashboards and alerts rather than to a rep’s device during the active visit with a same-visit task list. For teams on a constrained budget who need to move from manual audits to AI-powered shelf measurement, ShelfWatch is a starting point. For teams where same-visit correction is the commercial priority, the architecture limits what it can deliver.
✓ Best for: Mid-market CPG brands and teams moving from manual audits to AI-powered shelf measurement for the first time, or brands needing fast SKU training for frequent launches.
✕ Not the right fit if: Same-visit correction is the priority. ShelfWatch produces compliance data efficiently; it does not route that data back to the rep in the aisle during the active visit.
Strongest technical IR accuracy for European and international markets.
Vispera is a computer vision company based in Istanbul, with offices across Europe, India, and the US. Its image recognition platform offers two products: Storesense for mobile field visits and Shelfsight for fixed-camera continuous monitoring. The baseline recognition accuracy starts at 93% and reaches above 96% with accumulated training data. With its human-in-the-loop quality control process, Vispera commits to above 99% accuracy for accounts with sufficient training data — a technical performance bar that very few platforms publish explicitly.
Vispera measures planogram compliance, out-of-stocks, share of shelf, pricing, and competitive presence. Its panorama reconstruction algorithm handles narrow aisles and glass cooler reflections — conditions that challenge platforms trained primarily on clean shelf environments. The reporting layer feeds into Power BI dashboards and integrates with client CRM and analytics systems.
Vispera’s strength is technical precision and international coverage, particularly in European grocery retail where CPG execution standards are high and retailer data-sharing is more structured. The platform is analytics-oriented. Compliance data routes to dashboards and reports; same-visit corrective task routing to the field rep is not part of the core workflow. For CPG teams in European or Asian markets who need high-accuracy IR with strong integration into existing BI infrastructure, Vispera is worth evaluating to replace Tax.
✓ Best for: CPG and retail teams in European and international markets where IR accuracy, planogram compliance depth, and BI integration are the primary requirements.
✕ Not the right fit if: Same-visit correction in a CPG field execution workflow is the core need. Vispera is technically precise and analytically strong; it is not designed around in-visit task routing to field reps.
5. Snap2Insights
For CPG teams moving from manual audits at scale.
Snap2Insights is an AI image recognition platform built specifically for CPG in-store execution. Its most notable deployment is PepsiCo, which used the platform across 190,000 US retail locations — one of the largest retail IR deployments on record. The platform measures on-shelf availability, share of shelf, planogram compliance, and promotional execution, with an API-first architecture designed to integrate into existing SFA, CRM, and ERP workflows.
Snap2Insights’ positioning is rapid deployment and commercial ROI: the platform emphasises getting from image capture to actionable KPIs as quickly as possible, with configurable dashboards that align to client-defined execution metrics. Its edge-to-cloud capability means processing can happen on-device in low-connectivity environments before syncing to the cloud.
Like InfiViz, Vispera, and ParallelDots, Snap2Insights produces compliance data that routes to dashboards and reporting layers. The correction workflow is separate. Its strength is speed of deployment at scale and proven performance in large US retail networks.
For a CPG team with a large broker-managed field network that needs rapid AI IR deployment across a wide store footprint, Snap2Insights delivers that. For a team where same-visit correction is the defining requirement, the architecture is the same as the others — detection and reporting, not detection and correction.
✓ Best for: CPG teams with large field or broker networks that need rapid AI IR deployment at scale across wide US retail footprints.
✕ Not the right fit if: Same-visit correction is the priority, or you need compliance data to connect back into planogram and assortment planning. Snap2Insights is a strong measurement tool; the execution loop is not closed natively.
|
Platform |
IR accuracy |
Same-visit correction |
Primary strength |
|---|---|---|---|
|
Vision Group Store360 |
High (pre-trained, 1.3M+ SKUs via its digital product library) |
✓ Native — rep gets task in aisle |
Full execution loop: detect, correct, verify, plan |
|
InfiViz by Infilect |
High (95%+, GT + MT) |
Reports to dashboard |
Analytics depth for category & trade marketing |
|
ParallelDots ShelfWatch |
95%+ (fast SKU training) |
Alerts; dashboard-routed |
Accessible IR entry point, fast SKU setup |
|
Vispera |
93–99%+ (human-in-loop) |
Reports to BI/dashboard |
Technical precision, European market coverage |
|
Snap2Insights |
High (190K+ US stores) |
Dashboard and API outputs |
Rapid large-scale US deployment, API-first |
All four alternatives on this list do what Trax does: they read a shelf photo with AI and produce compliance metrics. The deployment credentials are genuine. If your team’s primary job is measuring shelf conditions and feeding that data into category dashboards, any of them is a credible replacement.
The gap that separates Store360 from the others is what happens in the fifteen minutes after the image is taken.
InfiViz, Vispera, ParallelDots, and Snap2Insights all produce a compliance score that routes to a report. A manager reviews it, a task gets created, and a follow-up visit is scheduled. If the shelf was wrong on Tuesday, it stays wrong until Thursday or next week. Every day between detection and correction is a day of lost sales on that SKU in that store.
Store360 routes the compliance score to the rep’s device while she is still standing in front of the shelf. The rep sees the gap, gets a task, fixes it, takes a verification photo, and moves on. The shelf is correct before she leaves the store. That is not a workflow improvement — it is a commercial event.
“What takes a couple of minutes now used to take 15 to 20 minutes. Rep Insights lets our people sell directly in store with data in under 60 seconds.”
— Michael, Nestlé
Beyond the correction loop, Store360 is the only platform on this list that connects execution data back into planogram design, assortment optimisation, and demand planning.
A compliance failure on a specific SKU in a specific store cluster is not just an operations signal — it is an input to the next category reset. The platforms built around detection alone generate reports. Store360 generates planning inputs.
For a category manager who needs the same platform to support her line review prep, her rep’s store visit, and her next assortment decision, no other platform on this list closes all three loops. Vision Group does.
“Vision Group has been a life changer here — a life changer. I would never even think of moving out of using them.”
— Eric, Goya
If your team is currently on Trax or evaluating alternatives in 2026, the fastest way to answer the question is a live walkthrough on your own category, your own store network, and the execution gaps your team is currently managing.
Book a 30-minute demo with the Vision Group team. No configuration required before the call.
For CPG brands that need same-visit correction — where the field rep fixes the compliance gap during the active store visit rather than in a follow-up — Vision Group Store360 is the strongest option. It combines AI image recognition with in-visit task routing, planogram connectivity, and a feedback loop back into category planning. For teams whose primary need is shelf analytics and compliance measurement at scale, InfiViz and Vispera are both strong depending on the market.
A field rep takes a shelf photo during a store visit. The AI compares every SKU in the image against the planogram on file for that specific store and flags deviations — missing facings, wrong positions, out-of-stocks, pricing errors — at the SKU level. The speed of that analysis determines what happens next: if the result reaches the rep during the visit, she corrects the shelf before leaving. If it reaches HQ in a post-visit report, the shelf stays wrong until the next scheduled visit. The difference between those two outcomes is typically two to five days of lost sales on the affected SKUs.
Three things matter most. First, whether the platform surfaces compliance data to the field rep during the active visit or only after it — that distinction determines whether you are solving the detection problem or the correction problem. Second, whether execution data connects back into planogram design and assortment planning, or sits in a standalone compliance dashboard. Third, how long deployment actually takes under real field conditions — not the best-case timeline from the vendor demo.
Both use AI image recognition to measure shelf compliance, out-of-stocks, share of shelf, and pricing. Trax routes that data to dashboards and compliance reports. Store360 routes it to the field rep’s device during the active store visit, enabling same-visit correction. Store360 also connects compliance data back into planogram building and assortment optimisation tools. Trax covers the detection layer. Store360 closes the full loop from detection through correction and back into planning.
It depends on the platform and the complexity of the deployment. Vision Group Store360 deploys in under 30 days including SKU library configuration, planogram integration, and field team onboarding. ParallelDots ShelfWatch can train new SKUs within hours. Vispera’s accuracy improves as training data accumulates, so time to peak performance depends on how much historical shelf data is available. Larger enterprise deployments with custom integrations take longer across all platforms. The more relevant question is time to first meaningful data — which for most of these platforms is days, not months.
Yes, and it does so in three specific ways. Accuracy improves from roughly 60–70% on position-level deviations with manual audits to 90–95%+ with AI image recognition. Speed improves from post-visit or same-day reports to seconds from photo capture. Coverage improves because every store visit generates structured compliance data rather than subjective rep notes. The operational change is that the rep’s job shifts from documenting what she sees to acting on what the AI surfaces — which is a better use of her time in the store.
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