Discussions

I wanted to share a small win and get some thoughts from other devs who’ve worked with the Rebuy API for product personalization. Recently, I was helping a client who runs a mid-size Shopify store, and they wanted to tweak their recommendation logic nothing too fancy, but enough to surface better add-on suggestions based on purchase history and cart behavior.

I started by exploring Rebuy’s API docs and was genuinely surprised at how flexible the endpoints were. Within a couple of hours, I had a proof of concept running that adjusted recommendations dynamically, depending on whether the user was returning or first-time. The caching logic took a bit of tuning, but once I aligned it with Shopify’s cart state, it ran smoothly.

What really stood out to me was how much customization Rebuy allows without breaking the native storefront flow. In past projects, I’ve had to rely on third-party scripts that bloated load times. With Rebuy, I managed to keep the requests lean, and even integrated a small internal dashboard to monitor recommendation performance (nothing fancy just a quick React setup).

This whole project reminded me that having access to reliable developer tools is kind of like having an affordable nursing coursework writing service it saves time, lets you focus on strategy, and gives peace of mind that the technical details won’t crumble later.

Curious if anyone here has tried connecting Rebuy recommendations with external data sources like Klaviyo or custom-built APIs? Thinking about testing that next to create more behavioral segments. Would love to hear what’s worked (or not) for others.