Analyzing sales reports made easy
Being the world’s leading high-end fashion retailer, one can only imagine the level of efficiency and efforts expected from the business, sales and store management teams to keep sales high and customers satisfied across the world.
From the single store in heart of USA, our client has diversified in recent decades to meet-up with the growing up-scale clothing demand from asian and oceanic countries. In one of the most challenging and fast-paced markets in the world the store-to-sales ratio is a key performance indicator on deciding the:
· Store level changes required.
· Customer buying trend and customer satisfaction index.
· Upcoming fashion trends.
What were the challenges client was facing?
Our client was facing issues with their existing data analytics tools and they were way too slow to keep up with the market conditions. Given the data complexity the current tool took more than 15 days to load-analyze-report the data into a business readable/understandable format.
How to reduce hassles of analyzing complex retail store sales data?
To help our client receive reports much faster and with up-to-date precise data, we first created an original data source(ODS) repository and then used various transformation on the data to streamline it and make it more meaningful. This transformed data was stored in Microsoft Azure Data Warehouse (DWH).
The operational data from this DWH systems is forwarded to Power BI. In Power BI, we shaped this data into useful information in different reports and dashboard board format that we refreshed daily and the business or store staff can use daily.
Power BI transforms the DWH’s crude information into client preferred
A. Informative Power BI services report or
B. Daily/Monthly paginated reports (auto-scheduled run)
These reports show different statuses and statistics of the store sales or customer relations. Then, store staffs like managers, customer care agents, stock controllers, etc. use this information to properly operate and manage their sales including outlet sales.
Using Explora’s expertise in data management along with using Power BI for advanced analytics, our client has opened new possibilities for the better store sales analytics experience and helping them shape a future they deserve in much faster and effective way.
Using Power BI, the company gains the benefit as it opened new revenue streams, new business opportunities, and improved customer relations experience giving better results. The integration of Power BI for advanced analytics becomes more cost-effective and affordable for end-users.
Besides, in terms of the report performance wise, from the 15 days of data refresh now reduced to 2 hours data refresh every day and this is a significant improvement we bring to client. With this, most of the reports can now generate in real-time manner daily.