Retail
Scalable Ecommerce Platform for Retail Brands, USA
Increased conversion rate by 35%, reduced cart abandonment by 28%, and enabled the platform to handle 10× more concurrent users.
A South African retail chain with stores across multiple provinces wanted to reach customers on WhatsApp for order collection updates and promotions, integrated with their point-of-sale rather than run as a separate marketing tool. Connectivity and power interruptions made reliability the central design problem. PapaSiddhi built the integration and the messaging layer.
Delivered in approximately two months by a small dedicated team.
Project Highlights
Scalable Architecture
Built for growth — Fixed Price designed to scale
Secure & Compliant
Enterprise-grade security and data protection standards
Measurable ROI
Informal per-store WhatsApp with no records → Integrated messaging resilient to load shedding
South Africa Delivery
Delivered for a South Africa-based Retail client
Tech Stack
Last updated:
Industry
Retail
Sector
Regional Grocery & General Retail Chain
Region
South Africa
Project Type
Fixed Price
Kwa**** Stores is a regional grocery and general retail chain operating stores across multiple South African provinces. Its customers are value-conscious shoppers for whom mobile data costs matter, and who already used WhatsApp to message individual store numbers informally about orders and collections. Store teams were fielding these messages on their own devices or shared numbers, with no visibility for head office.
The chain wanted to turn that habit into a structured customer channel connected to its point-of-sale systems, covering both order collection updates and promotions. Doing so in South Africa meant designing around load shedding, varied connectivity and the direct marketing consent rules of the Protection of Personal Information Act (POPIA), all while keeping costs in ZAR proportionate for a regional retailer.
This project was delivered under a Non-Disclosure Agreement. The client operates in the Retail sector (Regional Grocery & General Retail Chain) and is based in South Africa.
Customer conversations on WhatsApp were happening store by store with no central record, no consistency and no link to order status. Formalising this was attractive, but the constraints were unusual. Scheduled load shedding regularly cut store power and connectivity, so any integration that assumed stores were always online would fail predictably and often.
Many customers were sensitive to data costs, which made image-heavy promotional broadcasts a poor fit. POPIA's direct marketing provisions require proper consent, and the chain had no reliable consent record for the customers already messaging it, so the consent base had to be rebuilt rather than inherited.
The point-of-sale software was an older on-premise product at each store, with a readable database but no usable API. A clean real-time integration was therefore impossible, and the design had to be defensive from the outset. Replacing the POS software across every store was not an option, so the integration had to read what existing systems could expose and tolerate their limitations.
Informal per-store WhatsApp with no records
Integrated messaging resilient to load shedding
PapaSiddhi built a Node.js messaging service on the WhatsApp Business API, with MongoDB storing conversation state and message history. A lightweight agent at each store reads order and collection status from the POS database and pushes events to the central service through a durable local queue. When power or connectivity drops, events accumulate locally and sync once the store is back online, so nothing relies on a store being reachable at any given moment.
Consent was rebuilt from scratch through an explicit, documented opt-in flow, with the record stored against each number and opt-outs honoured immediately and permanently — designed to support POPIA's direct marketing requirements. Templates are text-first and light on media to respect customer data budgets, while promotional sends are segmented and rate-limited. Order collection notifications go out as transactional messages the moment status changes arrive.
A React console lets staff read and reply to messages for their own store only. Delivered on a fixed-price basis, the build also included monitoring of the store agents, so head office can see which branches are offline and for how long instead of discovering sync gaps days later.
Delivered in approximately two months by a small dedicated team. Collection notifications now reach customers automatically as orders become ready, replacing informal per-store messaging with no record. The durable queue design has proven itself — stores routinely go offline during load shedding and no notification events have been lost, which was the specific failure the client feared most. A properly documented consent base was built from scratch, putting the chain in a defensible POPIA position for direct marketing where previously it had none. Message engagement is strong, consistent with WhatsApp's position in the South African market, and text-first templates kept payloads light enough to avoid customer data-cost concerns.
Transformation Summary
Informal per-store WhatsApp with no records → Integrated messaging resilient to load shedding
This project was delivered under a Non-Disclosure Agreement (NDA). Specific client details, business data, proprietary workflows, and project credentials remain confidential. Screenshots and live URLs are available upon mutual NDA execution.
Request an NDA to see full detailsIt would if it assumed stores were continuously reachable, which is why nothing in the design does. Each store runs a lightweight agent with a durable local queue, so a store losing power accumulates events and syncs when it returns rather than losing them — no notification events have been lost since go-live.
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Retail
Increased conversion rate by 35%, reduced cart abandonment by 28%, and enabled the platform to handle 10× more concurrent users.
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Live across all three campuses for the start of the academic year, delivered in approximately three months by a small dedicated team.
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