RetailNext vs Zivni vs Trax: Which Tool Is Best for In-Store Execution in FMCG?
Short answer: they solve different problems. RetailNext is built around in-store analytics and shopper traffic (originally for retailers, not brands running field reps). Trax is a computer-vision heavyweight for shelf image recognition at scale. Zivni is a field sales platform where AI shelf photo analysis is one feature inside a bigger toolkit — beat planning, GPS attendance, voice order entry, and ERP integration.
So the real question isn't "which is best." It's "best for what you're actually doing every day."
Let me break it down the way I'd explain it to a distribution owner who called me confused after a demo.
What each tool is actually built to do
Here's the thing — the name "in-store execution software" gets stretched to cover very different products. That's where buyers get burned.
RetailNext started as a retail analytics platform. Think traffic counters, dwell time, store heatmaps, conversion by zone. It's designed for the retailer who owns the four walls — the mall operator, the big-box chain — measuring how shoppers move. If you're an FMCG brand trying to manage reps visiting hundreds of outlets, that's not really its lane. It can tell you a lot about one store you control. It won't run your field team's day.
Trax is a serious computer-vision company. Their strength is shelf recognition — pointing a camera at a shelf and getting back share-of-shelf, planogram compliance, out-of-stock flags, and pricing. Big multinationals use it. It's powerful. It's also priced and structured for enterprise, and image recognition is the core of what you're buying.
Zivni is a field sales management platform. Reps use it all day — planning their beat, clocking in with GPS-tracked attendance, taking orders by voice, snapping shelf photos for AI analysis, and syncing everything into your ERP. The shelf photo piece matters, but it's part of a full workflow, not the whole product.
Quick comparison table
| Factor | RetailNext | Trax | Zivni |
|---|---|---|---|
| Primary purpose | In-store shopper analytics | Shelf image recognition at scale | Full field sales + retail execution |
| Best fit | Retailers measuring their own stores | Large FMCG brands, deep IR needs | FMCG/CPG distributors and brands running field reps |
| Field rep workflow | Not the focus | Add-on to the IR core | Built around it |
| Order taking | No | Limited | Yes (including voice) |
| GPS attendance | No | Varies | Yes |
| ERP integration | Varies | Enterprise-oriented | Yes |
| Entry pricing | Enterprise, quote-based | Enterprise, quote-based | From $5/user/month, modular |
| Regions we serve | Global | Global | UAE, KSA, Pakistan, Oman, Bahrain, Kuwait, UK, USA |
One note on pricing. RetailNext and Trax are typically quote-based enterprise deals, so I won't put fake numbers next to them — ask each vendor for a written quote tied to your outlet count and user count. Zivni starts at $5/user/month with modular add-ons, so you pay for what you turn on.
Which one fits your team?
Honestly, this comes down to three questions.
Do you own the store, or do you visit it? If you run the physical retail space and want to understand shopper behavior inside it, RetailNext is the closest fit. If you're a brand or distributor sending reps into someone else's store, RetailNext isn't built for that job.
Is image recognition the whole point, or one piece? If you're a large brand and your single biggest pain is shelf compliance across thousands of stores — and you have the budget and internal team to run an enterprise IR deployment — Trax deserves a serious look. That's what they do well.
Do your reps need to run their entire day in one app? This is where Zivni fits. Beat planning, outlet mapping, attendance, ordering, shelf photos, gamification — one tool the rep opens in the morning and closes at night. If your problem is "my field team is a mess of WhatsApp, Excel, and paper," a single field sales platform beats a specialist analytics tool.
Look — I'm the Zivni founder, so read that with the appropriate pinch of salt. But I'll be straight with you: if pure, deep shelf-image accuracy at massive scale is your one requirement and cost isn't a constraint, a specialist like Trax may serve you better on that narrow axis. We'd rather you buy the right tool than churn in three months.
What to actually ask each vendor before you sign
Don't judge from the demo reel. Demos are polished. Your stores aren't.
- Give them 20 of your real shelf photos — messy lighting, crowded shelves — and ask for the recognition output. Accuracy on their sample images means nothing.
- Ask what happens offline. Reps in traditional trade lose signal constantly. Does the app queue orders and sync later, or freeze?
- Ask for the total cost, written down, including setup, image-recognition processing fees, add-on modules, and support tiers. "Starts at" numbers hide a lot.
- Ask about ERP integration specifics — which systems, which fields sync, and who builds the connector.
- Ask about local support hours in your timezone. A UK ticket at 4pm GST is a different experience than a Karachi one.
- Ask how long onboarding takes for, say, 30 reps. Enterprise IR rollouts can run months. Get it in writing.
The common mistake I see distributors make
Buying an analytics tool when they needed a workflow tool. Or the reverse.
A merchandising manager gets excited about share-of-shelf dashboards, signs a heavy IR contract, and then realizes the reps still have no clean way to plan routes, log visits, or place orders. Now they're paying for two systems that don't talk to each other. That's the expensive version of this decision.
So map your actual daily workflow first. Write down what a rep does from 8am to 6pm. Then see which tool covers the most of that list without duct tape.
If your list is mostly "visit outlets, take orders, check the shelf, prove the rep was there" — that's a field sales platform, and you should shortlist Zivni against FieldAssist and BeatRoute too, not just RetailNext and Trax.
Want to test it against your own stores? Book a Zivni demo and bring your messiest shelf photos and your real outlet list — we'll show you the workflow end to end, no polished sample data.