Tips for scaling analytics at startups

Tips for scaling analytics at startups

This week on The First Round Review, a veteran analytics leader unpacks what she’s learned from a decade of helming the data team at DoorDash — and shares her playbook for startups first standing up the function. Starting an Analytics Org From Scratch — Lessons From a Decade at DoorDash Early-stage

This week on The First Round Review, a veteran analytics leader unpacks what she’s learned from a decade of helming the data team at DoorDash — and shares her playbook for startups first standing up the function.

Starting an Analytics Org From Scratch — Lessons From a Decade at DoorDash

Early-stage startup builders likely aren’t spending much time poring over customer data. There probably isn’t much of it anyway — and you’re too busy building an MVP or practicing your fundraising pitch. At this phase, analytics can seem like the far-off domain of huge companies with legions of users.

But as the momentum of product-market fit picks up and more and more users leave measurable fingerprints across your product, you might begin to wonder how to start tracking everything. Is it time to build out an analytics team?

As both a seasoned analytics leader and a startup advisor, Jessica Lachs is a good person to ask. She joined DoorDash as its first General Manager back in 2014, helping the delivery service hit the ground in a couple US cities, and went on to found the analytics team and make the first few hires. Ten years, millions of users and an IPO later, Lachs has climbed the ranks to VP of Analytics, leading a global org of over 300 people — so she’s seen firsthand how the company’s data and resourcing needs have evolved at every stage of its life.

In today’s article, Lachs lays out a comprehensive guide for early-stage startups that are just starting to think about how to tackle analytics. Alongside plenty of examples of how she did things at DoorDash, she breaks down:

  • A birds-eye-view of an analytics org
  • The three C’s of data: creation, curation and consumption
  • Which metrics to track early on — and when to start experimenting
  • Hard and soft skills to vet analytics candidates for
  • The profiles of Lachs’ first hires
  • A checklist to gauge your startup’s readiness for an analytics org

Thanks, as always, for reading and sharing!

-The Review Editors


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