Daasity's Data Model

Daasitys Data Model header

This article is specific to the Growth Data Model and is applicable for Growth customers.

The Daasity Data Model is actually a compilation of several data models that are grouped in logical subject areas for D2C brands. 

Each subject area of data has a model. For example, Order Information is contained in the Orders model. The model is comprised of several tables of information that has either been extracted from a data source (I.e. Shopify, Facebook) or has been transformed with SQL to produce a new result.

The data & information you see as an end user are the result of raw extracted data being organized, aggregated, and transformed through our Transform process.


At the highest level, your data goes through the following simplified process:

Daasitys Data Model - process

Several calculations and transformations happen in the Load & Transform section. Data is combined, calculations are performed, algorithms are run, and finally several new data tables are created. Those transformations result in 7 mini data models that reside within your data warehouse.

Daasitys Data Model - Data Models

Some examples of the calculations and transformations that happen in Daasity's data model are:

  1. Householding: We look for additional signals beyond just email address to identify if two customers might be the same person. The Daasity householding algorithm is a drastic improvement over other systems that only use email address, resulting in more accurate repurchase rates and LTV.

  2. Order Unification: We combine Shopify, POS, Amazon and other orders into one master table. This allows you to see a holistic business view without going to multiple systems. And of course, data is filterable down to just 1 sales source system giving you the flexibility to view your order and revenue data in aggregate or boiled down to an individual source.

  3. Customer Data Calculations: In addition to householding, customer data is further transformed to place customers in various RFM cohorts, calculate LTV and more. This helps you identify who your best (and worst) customers are.

  4. Marketing Channel Attribution: Daasity allows customers to do channel mapping that enhances the accuracy of traditional GA last click channel attribution. Read more about Daasity Attribution here.

  5. Calculations: We've pre-programmed hundreds of calculations that D2C brands typically are looking for to save you time and effort.

Each individual data model can be accessed through Explores. Explores are views into areas of the data model that are used to created queries that produce results - or answers to questions. 

Learn more about choosing the right explore