City Ranking, Trade Zone Analytics, Demographic Segmentation, Kiwi
Main Solutions ⇂
Trade Zone Analytics
Kiwi, a GIS platform
Background: Gap Inc., founded in 1969, is an American worldwide clothing and accessories retailer.
Gap is the largest specialty retailer in the United States, and is third in total international locations. Gap opened its 1,140 square meter flagship store in 2010 in Shanghai, China, and opened other stores in other region in a very short time.
Did not have a standard operation procedure of business expansion
Each department did not know when to start their jobs
Waste too much time on investigation
Nowadays, Gap has over 150 stores in China and continues expansion. But, Gap did not have a standard operation procedure of business expansion. Each department did not know when they need to start their works unless the previous department notify the next department. Therefore, they waste the majority of time for waiting others to inform each other. Moreover, Gap expanded their business slowly. If Gap wanted to open a new store, they needed to spend at least USD 1,000,000. Therefore, they need to evaluate every factors for decreasing the investment risk, but they spent a long time to do this thing. Gap wanted to shorten time for investigation but also wanted a precise analyzing report.
Main Solution Methods we used in this case:
Trade zone analytics
Kiwi, a location intelligence platform
For solving the first problem, we compiled all business process that each department needed to our Kiwi, a GIS platform, and all departments must follow the instructions step by step. They cannot pre doing the project, therefore, all departments can know the period that each department spent. From sells department to store design department, they can update the project immediately, and Gap can follow this data to adjust their schedule. Furthermore, we built-in formal version forms that China government needed. Employees of Gap can export the report and do not need to revise when they need to hand in legal documents.
For enhancing business expansion precisely, we used trade zone analytics, city ranking, and demographic segmentation to solve it. First, we estimated the total nationwide market potential segmented by region, city tier, and per brand, and we also insight into untapped cities for Gap. They could decrease risks and also have a first-mover advantage. Second, we distributed total population, working population, household number, as well as age, and model the distribution of wealth based on household income and expenditure and property pricing to apply on Kiwi. Then we customized market potential heat map for Gap, and added their key competitors at the same time. Final, drawing trade zones by data that we compiled and pointing out target locations.