Google Analytics for Physical Retail


COMPANY SIZE Less than 5

# OF ENGINEERS Less than 5


TAGS SaaS, Analytics, Retail Technology, Data Mining, YC Winter 2014


What do we do?

Next-gen retail analytics stack and data warehouse. We're currently working with large fashion retailers, and we're processing more than $1B worth of transactional data.

Technical challenges

- How to run complex queries over 50M+ rows under 1 second?
- How can we handle customer-specific features in a way that does not murder our codebase?
- How can we leverage machine learning or statistical analysis to make our integration process more automated?
- What can we do to improve our deployment infrastructure?
- How do we implement better dashboard insights that will demonstrate clear ROI?
- What can we bring from the online analytics world to brick-and-mortar retail?

Why join us?

0) Play with retail datasets that are otherwise incredibly hard to get.
1) Learn about the opaque world of retail infrastructure.
2) See a direct correlation between your work and the retailer's sales.
3) Collaborate with a team that has worked at fashion houses in Paris, shipped stuff for Colgate and Jack-In-The-Box, and has managed $100M of product for P&G.
4) Experience the thrill of launching a massive spark cluster.
5) Have tremendous impact over the technology and direction of the company
6) We have many interesting problems to solve, both on the product / analytics side and the infrastructure side.

Our tech stack

  • Node.js
  • Apache Spark
  • Docker
  • Python
  • Amazon Web Services
  • AngularJS