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DISCLAIMER

This is MOCK customer data that was swapped in for the sake of the demo. No real or sensitive information is used.


TL;DR

This is a custom data dashboard I built from scratch in React as a Product Manager, using disparate sources of data, to make the right product decisions.

This resulted in migrating customers 2x faster.

Demo here

The Problem

When I joined Nylas as a Product Manager, I was tasked with re-imagining, and in turn re-engineering, the Nylas Scheduler.

The biggest hurdle? The data pipelines for v2 had been shut off 1 year prior, leaving no relevant data left for me to pull.

This left me blind as a PM, with no insights on feature usage, customer use-cases, or revenue impact.

It's tough to build for the future when you don't know about the present.

The Solution

I got creative with the data sources I could pull from. This included:

  • database dumps (15gb of plaintext)
  • excel sheets about customers
  • exported Jira and Vitally data

Duck-taping all these disparate data sources together through org IDs and very sketchy Python code, I managed to get useful data.

Next came the frontend. The mission was to create the views I needed as a PM to make smart decisions about which features were needed, which could be discarded, and in what order to prioritize each feature.

The Outcome

Thanks to the cohort views (and the most-used feature view which unfortunately didn't make the demo ^), I was able to break-up the road to GA into 5 releases.

Each release unblocked a subset of customers, which allowed us to incrementally get users on Beta, while preventing a massive waterfall of features for the GA release.

Customer support teams managed to transition customers from v2 to v3 2x faster than the waterfall appraoch with the cohorts layed out.

Running it

  • pull it
  • npm install
  • npm start

About

A data dashboard used to make data-informed decisions for Nylas' Scheduler (redacted data for demo purposes)

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