Peavey Chick Days Promotion
Overview
A one-off client engagement at Bright Village for Peavey Mart, a Canadian farm and ranch supply retailer. The work: stand up a seasonal Shopify promotion to sell live baby chicks, and wire it into Peavey Mart’s legacy back-office systems so that orders, inventory, and fulfilment all lined up with reality.
It sounds small until you look at what selling live animals actually involves.
Why live animals make this interesting
Selling chicks is not like selling a product off a shelf. Everything is time sensitive, and most of the complication lives in the coordination layer rather than in the software itself:
- Hatcheries work on fixed schedules. Chicks are only available in specific weeks, and once they are ordered they have to move fast.
- Pickup windows at each store are narrow. A chick is not going to sit in a stockroom for a week waiting for a customer.
- Inventory shifts by the day. What is listed for sale has to reflect what the hatchery can actually deliver on a given date, at a given location.
- Customer expectations are hard. If a promised chick does not show up at the right store on the right day, the problem is immediate and very public.
None of that maps cleanly onto a stock Shopify product listing, so most of the work was making the shop behave like a logistics pipeline instead of a regular catalogue.
Architecture
The integration sat between Shopify and Peavey Mart’s legacy systems. The initial build used Python-based Azure Functions for compute and Azure Service Bus for job orchestration.
- Shopify as the customer-facing storefront, product catalogue, and order intake.
- Azure Functions (Python) as the integration layer. Functions received webhooks from Shopify, translated them into calls against Peavey Mart’s legacy APIs, and pushed inventory and order-status updates back into Shopify when things changed on the back-office side.
- Azure Service Bus as the orchestration spine. Rather than doing everything inline in a webhook handler, work was queued as messages and picked up by worker functions. That kept the integration responsive and resilient when either side was slow or unavailable.
- Peavey Mart’s legacy systems as the source of truth for what could actually be fulfilled, store by store.
Highlights
- Delivered a seasonal promotion end to end under real-world deadlines set by hatchery availability.
- Event-driven architecture using Azure Service Bus so retries and transient failures did not take the storefront down with them.
- Careful webhook idempotency handling so a redelivered Shopify event never accidentally doubled an order for a perishable product.
- Python Azure Functions kept iteration fast during a project where requirements shifted as the business learned what the promotion actually needed.
- Monitoring set up from day one so a promotion with fast-moving inventory stayed observable in real time.
Stack
Shopify, Python, Azure Functions, Azure Service Bus, Peavey Mart legacy systems