Data Challenges before Daasity

Before working with Daasity, MANSCAPED^® did all ELT in-house via internally built Python extractors and custom transformations. However, maintaining this architecture became unmanageable as the business grew and developed significant analytics and data reporting needs.

• 60% of the workweek was spent maintaining the ELT pipeline, preventing useful analytics work.
• The data team could not easily manage specific reporting requests, change transformation code, or run deeper analyses without making major time trade-offs.

Data Solutions with Daasity

MANSCAPED started using Daasity’s purpose-built commerce extractors for major data sources, which Daasity maintains and updates as API changes roll out. Over time, the team has expanded its use of Daasity into being the brain and hub of a sophisticated data pipeline, analytics, and reporting solution.

• MANSCAPED has connected over 140 data sources to Daasity.

MANSCAPED’s data team has leveraged Daasity’s customizable transformation code functionality. This enables them to modify and extend Daasity’s robust prebuilt code as they see fit, without needing to monitor dozens of potential downstream analytics and reporting consequences.

The Results 

By having a single platform for ELT and being able to modify Daasity’s transformation code, the team can more easily manage their data needs. 

In their case, this means getting back to providing insights that optimize spend across the org, doing Marketing Mix Modeling, and keeping millions of customers well-groomed.