iBeauty: Data-driven customer insights & predictive analytics

Databricks

iBeauty provides software, websites and webshops to beauty salons and hairdressers. Their goal is to help salon owners manage their schedules, inventory, and client relationships while boosting their online presence. With iBeauty, salon owners can focus on what they love—providing great services while the software handles the business side efficiently.

The challenge

As a digital partner for beauty salons, iBeauty processes vast amounts of operational data.

This data can offers several opportunities:

  • Unlock actionable insights from this data to improve salon services
  • Refine & extend iBeauty’s software offering
  • Potentially embed data-driven features as a differentiator in a competitive market

Our solution

Data science driven exploration based on a reduced, anonymized dataset.

The modular Databricks setup allowed agile iteration and robust data science workflows across exploration and modeling phases.

Applied different customer behavior analytics:

  • RFM segmentation to profile clients
  • Basket analysis to uncover service combinations
  • Predictive modeling to understand no-shows
  • Forecasting of customer treatments to improve staffing and inventory

The business value

Our exploratory work proved that iBeauty’s operational data holds untapped value that can directly enhance both salon performance and the iBeauty platform itself.

By applying advanced analytics, we:

  • Enabled customer segmentation, supporting more targeted marketing and service personalization.
  • Identified cross-selling opportunities through basket analysis of frequently combined treatments.
  • Built a predictive model for no-shows and treatments, improving efficiency and customer experience