Modeling Transactional E-Commerce Data Header
What's inside:
Done Icon

Overview

Understanding analytical databases

Defining your enterprise metrics

Asserting your metrics

Navigating corner cases and ensuring accuracy

Asserting your enterprise dimensions

Takeaways & next steps

9 MIN

How to Transform Your E-commerce Data into Business Metrics

If you’re a DTC founder selling goods through an e-commerce store, there’s a pretty good chance you’re using a platform like Shopify, BigCommerce, or Woocommerce, and one of the dozens of analytics extensions like RetentionX, Sensai metrics, or Profitwell that provide off-the-shelf reporting.

At a high level, these tools are excellent for helping you understand “what” is happening in your business, but you’ll inevitably find yourself asking deeper questions that your off-the-shelf extensions can’t answer. You might also be frustrated to learn that the revenue reported by these off-the-shelf dashboards is inconsistent with the revenue that your finance team reports.

When you find that these problems are impeding your ability to make important decisions, it’s time to start thinking about building a data warehouse.

We created this guide for founding teams in M13’s portfolio companies who need a data warehouse but aren’t seasoned data pros. We’ll walk you through the fundamentals of modeling transactional sales data.

In this guide, we’ll cover:

1

Understanding analytical databases

2

Defining your enterprise metrics

3

Asserting your metrics

4

Navigating corner cases and ensuring accuracy

5

Asserting your enterprise dimensions

6

Takeaways & next steps



Here’s what else you’ll need to get started:

A database like Snowflake, BigQuery, or DigitalOcean receiving raw data from your e-commerce platform

A SQL developer



This guide also includes sections that may be valuable to the SQL developer building the database, including:

A Retail Modeling Checklist: Questions to ask yourself and your team before you start modeling your data

SQL templates: Standardized SQL templates that your SQL developer can apply to your own raw data for a head start

If you’re a founder at an M13 portfolio company who needs references for a contract or full-time SQL developer, please reach out to us on Slack or at propulsion@m13.co.

9 MIN

How to Transform Your E-commerce Data into Business Metrics

Modeling Transactional E-Commerce Data Header

M13

What's inside:
Done Icon

Overview

Understanding analytical databases

Defining your enterprise metrics

Asserting your metrics

Navigating corner cases and ensuring accuracy

Asserting your enterprise dimensions

Takeaways & next steps

If you’re a DTC founder selling goods through an e-commerce store, there’s a pretty good chance you’re using a platform like Shopify, BigCommerce, or Woocommerce, and one of the dozens of analytics extensions like RetentionX, Sensai metrics, or Profitwell that provide off-the-shelf reporting.

At a high level, these tools are excellent for helping you understand “what” is happening in your business, but you’ll inevitably find yourself asking deeper questions that your off-the-shelf extensions can’t answer. You might also be frustrated to learn that the revenue reported by these off-the-shelf dashboards is inconsistent with the revenue that your finance team reports.

When you find that these problems are impeding your ability to make important decisions, it’s time to start thinking about building a data warehouse.

We created this guide for founding teams in M13’s portfolio companies who need a data warehouse but aren’t seasoned data pros. We’ll walk you through the fundamentals of modeling transactional sales data.

In this guide, we’ll cover:

1

Understanding analytical databases

2

Defining your enterprise metrics

3

Asserting your metrics

4

Navigating corner cases and ensuring accuracy

5

Asserting your enterprise dimensions

6

Takeaways & next steps



Here’s what else you’ll need to get started:

A database like Snowflake, BigQuery, or DigitalOcean receiving raw data from your e-commerce platform

A SQL developer



This guide also includes sections that may be valuable to the SQL developer building the database, including:

A Retail Modeling Checklist: Questions to ask yourself and your team before you start modeling your data

SQL templates: Standardized SQL templates that your SQL developer can apply to your own raw data for a head start

If you’re a founder at an M13 portfolio company who needs references for a contract or full-time SQL developer, please reach out to us on Slack or at propulsion@m13.co.

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