Agro-Dealer Retail Merchandising Software for Ghana

Each outlet class carries its own checklist. A roadside agro-dealer shop is judged against a different must-stock list and display brief than a fertiliser depot, and a cooperative input store's shelf-talkers are not the same as a feed wholesaler's counter set-up. The platform tags every outlet by class, serves the matching checklist automatically, and rolls scores up by class so a brand team can see precisely which outlet type is falling behind.

A field officer photographs the counter or shelf, and the photo carries a GPS stamp and a timestamp automatically. The cloud model recognises pack shapes for seed, fertiliser and crop-protection lines, counts facings against the must-stock list, flags a rival product placed alongside, and raises a planogram gap or an out-of-stock line the moment it appears. Manual counting is no longer needed, and an agro-dealer counter audit takes a fraction of the time it used to.

L1 is completed by the field officer or extension agent during the visit itself, as a self-check against the brief. L2 is a supervisor review, triggered either by a low score or by a routine sampling quota. L3 is a spot-check run by the brand on a chosen sample of outlets, for governance. A failed check at any level escalates to the outlet owner with a corrective-action deadline attached.

A brand team briefs POSM by outlet class and links it to a season window, whether that is a start-of-season planting push or a mid-season top-up campaign. Each agro-dealer counter's allocation is generated from that brief automatically, and the field officer captures a before-and-after photo pair with GPS attached at install. An ROI dashboard flags any campaign under-delivering while the season is still open, so a brand can still correct course.

Yes. The app works offline by design. On a rural beat, at a village input shop or a fertiliser depot on an agricultural route where coverage is thin, an officer still completes the checklist, takes the required photos and logs POSM verification without a connection. The record syncs to the cloud automatically once signal returns, so nothing captured in the field is lost.

The checklist captures a competitor's branding, demonstration stock, POSM, pricing and any new product on the shelf. The same AI model that reads your own facings flags a rival pack sitting alongside yours without any extra step from the officer. That picture of the counter feeds directly into planning conversations with the agro-dealer and shapes territory priorities ahead of the next planting window.

An audit captures the batch number on the SKUs that matter and checks it against the batch master automatically. Stock nearing expiry is flagged the moment it is scanned, giving a brand team the chance to arrange a clearance offer or move stock to a faster-moving depot before it has to be written off. Crop-protection and biological lines are prioritised in this check because they carry the shortest shelf life on the counter.

A territory view shows compliance across a defined area, from a dense southern belt down to a single rural beat. A class view separates agro-dealer shops, fertiliser depots, seed dealers and feed wholesalers so each is measured against its own brief. A SKU view shows facings for seed, fertiliser, crop-protection and feed lines individually. Every figure drills down, all the way to the single photo behind it.

Yes, both run on the same cloud backend. Every audit attaches to the field officer's visit record, so a brand team can trace a single line from visit to audit to sell-through without switching systems. A gap between a high visit count and a low audit count surfaces automatically for supervisor review, and 1Voice AI can answer a plain-language question about any of it on demand.

A brand manager sees POSM compliance, SKU facing trends, planogram gaps, competitor adjacency and a near-expiry heatmap. A merchandising lead tracks campaign ROI, install pace and budget burn. Sales leadership gets territory roll-ups summarising all of it. 1Voice AI handles one-off questions as they come up, in plain language.