Verify what a dealer counter or market stall actually shows: the right brand signage in place, genuine parts sitting where the shelf plan calls for, prices held to the approved GHS list, and a photograph on file the moment something looks like it did not come through the authorised channel.
A signage and price brief goes out, a rep records what a counter or stall actually shows, and AI turns each photo into a pass, a flag, or a suspected-counterfeit review before the KAM ever makes a call.
Each dealer counter or stall receives the approved signage design, the shelf plan naming which parts sit where, and the current GHS price list. Reps carry it into the campaign module before a single visit starts.
The rep checks signage against the brief, confirms parts sit where the shelf plan says, reads every price tag against the approved GHS list, and photographs anything that looks like it did not enter through the authorised channel. A GPS landmark attaches to the visit automatically.
AI checks each photo for signage match, correct placement, price adherence, and markers associated with counterfeit or grey-market stock. Anything uncertain queues for a human reviewer before the counter's score updates.
Quick reads on shelf gaps, planogram AI, store visibility, and VisiMax for Ghanaian auto retail teams.
Built for a counter or stall trade, not a showroom floor. One workflow that briefs each site, checks what is actually on display, and scores it.
Each dealer counter or stall gets its own brief: the approved signage set, the shelf plan for genuine parts, and the current GHS price list. Nobody works the visit from memory.
A photo the AI is unsure about, whether it is a signage mismatch or a suspected counterfeit part, routes through a structured review before it lands on the record. Nothing is marked non-compliant on one uncertain image.
Signage status, shelf-plan compliance, GHS price adherence, and any open counterfeit flags roll into one score per counter, tracked across visits rather than a single snapshot, so a KAM can spot drift before it becomes a pattern.
AI checks packaging, branding, and batch markers against the approved SKU reference set. A part that does not match is flagged for a human reviewer, with the photo and GPS location attached to the outlet record.
Two 1Channel apps run the full field-to-channel workflow. Both sit on Google Play and the Apple App Store, sharing one cloud backend with the admin portal.
Counter and stall visits, signage checks, price verification, and AI photo review combine into one score per dealer for Ghana's auto-parts trade.
Explore Platform →Reference images and an outlet list define a display drive. Photo proof confirms it went up, and an exception alert fires if it comes down early.
Explore POSM →Structured review for anything flagged at the counter, from a signage mismatch to a suspected counterfeit photo, with a trail from first flag to close-out.
Explore Audits →Set up a signage or pricing drive with a budget, or run it ad hoc, then follow rollout counter by counter against the trade marketing plan.
Explore Campaigns →One record per dealer counter or stall, tagged by channel, category, and location, with onboarding and status tracking built for a fragmented parts trade.
Explore Outlets →Plan and measure seasonal parts and lubricant promotions, with ROI tracked by promotion, dealer, and SKU, and eligibility checked at the order stage.
Explore Trade Promo →The app reps carry to the counter: signage checks, price capture, photo evidence, and offline-first sync for stalls where the connection is unreliable.
Explore Mobile App →Counter and stall profiles sorted by trade type and category mix, each carrying its own signage, price, and audit history.
Explore Store Management →