Retail & E-commerce
Traditional recommendation engines use collaborative filtering — 'people who bought X also bought Y.' But they don't understand WHY. We diagnose what your engine is missing and, depending on the case, connect products, categories, attributes, seasons, and buying behavior to recommend on real customer intent.
— McKinsey & Company
The problems
Your recommendation engine doesn't understand product relationships.
Shallow recommendations
Collaborative filtering that doesn't understand semantic relationships between products.
Disconnected inventory
Stock, logistics, and pricing in separate systems.
Limited personalization
Generic experiences that don't reflect customer context.
Our solutions
Retail & E-commerce
Catalog graph
Products connected by attributes, compatibility, season, and usage context.
Contextual recommendations
AI that recommends based on real customer intent, not just history.
Unified inventory
Unified view of stock, pricing, and logistics in real time.
Related services
Frequently asked questions
What do you diagnose first in Retail & E-commerce?
We start with the operational pain, usually around Shallow recommendations: Collaborative filtering that doesn't understand semantic relationships between products. From there we decide whether the issue is process, data, systems, leadership, or a mix of them before proposing any implementation.
Do we need AI or a new platform to solve it?
Not by default. In Retail & E-commerce, the right answer can be a process change, integration, automation, dashboard, custom software, or no build at all. We only use AI or advanced data architecture when the diagnostic shows it will change the business result.
What could an initial project look like?
A first scope often targets Catalog graph: Products connected by attributes, compatibility, season, and usage context. We keep the scope tied to one measurable outcome, clear ownership, and the capacity your team actually has to operate the change.
How does fractional CAIO/CTO support work here?
We act as fractional technical leadership for Retail & E-commerce: prioritizing risks, turning Disconnected inventory into concrete operating decisions, selecting or coordinating vendors when needed, and supervising implementation until the change is working in the business.