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Armoire Style is a clothing rental membership that helps ambitious women love what they’re wearing. Founded in 2016 and headquartered in Seattle, WA, Armoire Style serves as a trusted advisor to help women build an elevated wardrobe that inspires confidence. With smart data and stylist picks, Armoire Style provides members with curated and personalized recommendations that make getting dressed all that much easier.
Before:
Platform Challenges, Data Inaccuracies, and Complex Processes Bring Uncertainty
Armoire had a mountain of data on customer behavior across subscriptions, rental history, preferences, and purchases that could be invaluable in satisfying and delighting their shoppers. But bringing all of that data together and harnessing it to feed predictive models was a significant challenge.
The problem Armoire Style faced was their business intelligence platform wasn’t flexible enough to empower forward-facing analytics in a governed way.
Trying to understand customer tenure across subscriptions, upgrades, and plans can make for some complex SQL queries. With a goal of bringing the same data to all tables within the business, they understood the value of data’s true potential.
Armoire Style needed a more effective way to use that data and serve up the perfect look for its customers to fuel their activity and their fashion inspiration.
Solution:
A Data Migration Providing a Single-Source-of-Truth
After collaborating with the Armoire Style team, we recommended the capabilities of Looker. We migrated away from inflexible and complex SQL queries to clearly defined Explores in Looker. Because Armoire Style had data, dashboards, and a lean analytics team, the migration consolidated everything into one system, creating one-source-of-truth. With a centralized system, the entire business gained access to valuable insights and can be utilized by stakeholders in all departments across the business.
As summed up by their CTO, Tristan Rees, “We wanted to invest in a tool which would allow us to extract tables and enable business users to explore data even without dashboards or SQL knowledge”.
After:
Data Accuracy and Accessibility Drive Operational Efficiency
The Armoire Style team now has optimal data models with real-time visibility into item performance. Because of the newly enhanced capabilities of data, performance can be measured to assist in driving profitability and adapting to obstacles that may hurt the bottom line.
Some other key results of the solution include:
- Valuable, useful data models fed by trusted data.
- Real-time visibility into customer behavior and item performance.
- Ability to predict customer style tastes, patterns, and return highly curated suggestions.
- Increase data team productivity.
- Democratized data and analytics accessible to stakeholders across the business, without the need for complex coding.
Rees mentions, “We now have people in our warehouse, merchandising, and operations teams, some who have never touched data, where our conversations are less of ‘hey can you build me this report’ to ‘hey, I’m running this report and it’s not performing. Can you help me?”
