About The Client
The client is a highly successful coffee brand in South Korea, with a large network of nearly 1,400 local stores. The company has the second-largest market share in the country, second only to Starbucks. In 2010, they made the decision to expand into the Chinese market and currently operates two direct-sale stores in the country.
The client is known for its high-quality coffee and welcoming atmosphere, and has developed a loyal customer base in South Korea. The company's expansion into China represents a major opportunity for growth and the chance to introduce its brand and products to a new market.
Key Challenges:
Identify sales primetime of each store.
Organize targeted promotional activities via consumer insights.
Achieve standardized one-stop operations system.
Implemented Solution
The client had a number of pain points that needed to be addressed in order to improve their store operations and increase sales. These pain points included the need to identify the sales primetime for each store, organize targeted promotional activities based on consumer insights, and achieve a standardized one-stop operations system.
To address these issues, the solution provided was data integration, which included the integration of consumer traffic, sales, and staff shift data. By collecting and analyzing this data, the client was able to gain valuable insights into customer behavior and preferences, identify the most effective times for sales and promotions, and streamline their operations to better meet the needs of their customers.
Key Results
The implementation of this solution has had a significant impact on the client's store performance and customer experience. By collecting and analyzing data on consumer traffic, sales, and staff shift patterns, the client has been able to identify the most effective times for sales and promotions and streamline their operations to better meet the needs of their customers.
One key finding was that the store saw its highest traffic of the day at 12:00, with nearly 400 customers. While the conversion rate at this time was 35%, which may be considered a data depression, the entering rate at 12:00 was at a normal level of 25%. The vacancy on the third floor was disregarded. These results suggest that the solution has been successful in improving the store's performance and customer experience, and has helped the client to identify opportunities for further optimization and improvement.
One key finding was that the store saw its highest traffic of the day at 12:00, with nearly 400 customers. While the conversion rate at this time was 35%, which may be considered a data depression, the entering rate at 12:00 was at a normal level of 25%. The vacancy on the third floor was disregarded. These results suggest that the solution has been successful in improving the store's performance and customer experience, and has helped the client to identify opportunities for further optimization and improvement.
