The SaaS Data Pipeline (SDP)

The bridge linking your product + marketing teams.

How does the EDP work ?

This BigQuery data pipeline transforms your product + marketing data into immediately-usable reporting.

01

Raw data

Roll up data from Google Analytics, your marketing platforms, and your product

03

Data viz

We build reports in your preferred data viz platform - Data Studio, Looker or Tableau

02

Data models

We write a set of SQL transformations, which churn your raw data into rich insights

  • 01

    Raw data

    Roll up data from Google Analytics, your marketing platforms, and your product

  • 02

    Data models

    We write a set of SQL transformations, which churn your raw data into rich insights

  • 03

    Data viz

    We build reports in your preferred data viz platform - Data Studio, Looker or Tableau

SaaS-specific “Recipes”

Each "Recipe" (aka workflow) within your pipeline answers a specific set of questions. Most SaaS data pipelines start with classics like:

SaaS

Trial -> Paid Rate Analysis

  • Are trials converting into paid users?
  • Are marketing campaigns driving signups that don’t convert?
  • Do we have product <> market <> messaging fit?

SaaS

Churn / Retention Analysis

  • Are users sticking around, or bouncing?
  • What features are churned users *not* using?

SaaS

CAC + LTV Cohort Analysis

  • How much can we afford to spend on acquiring each new user? much can we afford to spend on acquiring new users?
  • Is our marketing spend acquiring truly new users, or just preaching to the choir?
  • How has this changed over time, or by marketing channel?

Why use the SDP?

This data pipeline is NOT for you if...

  • You love manually + tediously wrangling your data in spreadsheets
  • You love not knowing who your best users are, and how they found you
  • You love making product + marketing decisions by the seat of your pants