How Lounge Underwear Built Data Infrastructure for 9 Shopify Stores

By Melanie Rankin | 3 min read

Lounge Underwear, recently named as the UK’s Fastest Growing Fashion Brand, is an online retailer whose mission focuses on comfort, female empowerment, and sustainability. From their ground-breaking Breast Cancer Awareness campaign, continued passion for diversity, sustainable collections, and carbon offsetting projects, Lounge is dedicated to being the company that cares - about Mother Nature and breaking down traditional beauty standards.

Lounge was originally founded in 2015 but experienced its highest growth during the
pandemic, exceeding all expectations. Due to the enormous growth, it became apparent that their existing Data Analytics systems were not serving their needs to understand their customers and make more informed decisions. That’s when the decision was made to focus on building a data infrastructure to help drive their already-astronomical growth to new heights.

The Challenge: 9 Countries, 9 Stores, Overwhelming Data Sets

Though sales data from Shopify stores represented the bulk of their data, Lounge was also working with a plethora of Social media, Marketing, Financial, and Customer behavior data to be put to use from different platforms. The best way to make effective use of this data was by blending all entities together and making them easier to digest for every end-user of the reports.

When a dedicated Business Analytics manager was brought onto the Lounge team, they knew that building an efficient data pipeline without a fast and reliable data integration platform wouldn’t be possible. They chose Dataddo as a fast and efficient integration tool with a wide variety of data sources, ease of use, and much-needed flexibility in data operations that were sure to change and develop over the course of the next several months.

The Solution: A Source for Every Data Point

After getting their cloud services and their data warehouse all set up, the task fell to integrating data from a pool of sources which extended beyond Shopify including Facebook, Instagram, LinkedIn, Zendesk, Rebound Returns, Xero, and more.

But Shopify proved to be an unexpectedly difficult task all by itself, due in part to API limitations and the size of the data. - not only were the data divided into separate stores, but each store was also divided by each data type, all of which had to be extracted individually.

Though the task was painstaking, Lounge’s team had Dataddo’s full support and consultation throughout the entire process, eventually assisting them to get all of their sources up and running.

Jenny MalaiThe communication is brilliant - it’s one of the key reasons we are working together. Anytime we needed support it has always been there.

-Jenny Malai, Business Analytics Manager at Lounge Underwear

Dataddo collects Lounge’s data from each source before sending it across to their data warehouse overnight. This data is then integrated from the data warehouse to their PowerBI data visualization platform. The end result: stable pipelines, safe storage, and the visualizations they need to make data-driven decisions.

The Result: Transparent Analyses, Informed Workflows 

The dashboards currently in use at Lounge have proven extremely versatile and time-saving across different departments at the company. Departments that might not usually incorporate data into their everyday work lives have more insights than ever into their operations. With data now available in categories like ticket performance, refunds, and product feedback, they have a clear view of what is and isn’t working and can make informed adjustments in their day-to-day workflows.

Marketing now has a complete view of Lounge’s worldwide presence to judge campaign and social media effectiveness, where Management has access to overall sales, product performance and customer growth across all stores.

Moving Forward With Dataddo 

As their data systems continue to grow, the next step for Lounge is to continue diving as deeply as possible into their customer insights to understand better how they can improve their customer experience. For the near future, they are looking into the possibility of adding a data science tool to the pipeline between their data warehouse and data visualization tool for faster, more efficient data blending and analysis.

Dataddo will continue running automatically in the background, delivering information to Lounge’s data warehouse so they can keep “Making Comfort Sexy” - but now, with data.

 

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Category: Case Studies

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