TL / DR; Rubber Ducky Labs helps e-commerce companies avoid tone-deaf product recommendations — like featuring ski jackets in June. It works by combining machine learning with human expertise to produce the best product recommendations.

Introduction

Co-founders Alexandra and Georgia have over a decade of experience shipping products in fashion tech, B2B ML tooling, and high-scale data infrastructure, and are passionate about making the state of the art in machine learning effortless and easy to understand.

Alexandra’s career started with her dream job working on clothing recommender systems for fashion tech companies, and she and Georgia founded Rubber Ducky Labs to be the suite of dream tools that they wished were available for building recommender systems.

The Problem

You’re a PM at a fashion tech startup. Your app is recommending that you buy ski jackets. It’s June.

Looks like nobody told the algorithm that summer isn’t ski jacket season, and now it’s your job to figure out whether or not your algorithm will start driving away users. If your team’s metrics dashboards can’t answer the question, you’ll need to file a ticket for the data science team to run some analysis. Looks like it’s going to be at least a week before you have an answer.

The Solution

With Rubber Ducky Labs you’ll have an answer within minutes. Now, you’ll be able to understand whether you looked at a lot of ski jackets recently, so it’s just happening to you, or if your colleague recently flipped a switch to promote a brand that happens to carry a lot of ski jackets.

Our solution was developed from over a hundred conversations to answer the question of “what’s going on with my recommender system?” With Rubber Ducky Labs you can:

• Explore your data visually - with product images
• Drill down from aggregate metrics all of the way to individual item or user journeys
• Consolidate and debug your company’s business logic
• View annual and seasonal trends
• Facet, segment, and filter and your data
• View side-by-side comparisons of models or ranking changes

The Vision

The mission of Rubber Ducky Labs is to allow people with domain expertise — like product managers, merchandisers, marketers, growth hackers, and founders — to easily build intuition about and incorporate domain knowledge into their recommender systems.

Today’s launch is just the first step. We want to help you do everything from consolidating business logic to previewing side by side model comparison to launching production experiments, all within RDL’s tools.

If this sounds like something you’re interested in, we’d love to build together.

Technical Details

Setup took 90 minutes of time with our first user. Under the hood, Rubber Ducky Labs is a fully hosted web app that connects directly to your data warehouse on the backend to pull your custom metrics and data. No need to deploy any services or change any code, plus you get to bring your own model! Additionally, the web and API are authenticated with Auth0 to keep your data safe.

Our Ask

We’d love to learn more about your recommender system, and start identifying areas for improvement. Interested? Email alexandra@rubberduckylabs.io to get started.

Have a friend who works with recommender systems? We’d love to meet them! Email us at founders@rubberduckylabs.io.