
Introduction
- With the fast development of China consumer market, a global fast-fashion brand plans to enter China market. And they have chosen Shanghai, the most fashion city in China, as their first entered city. At first stage, the company plans to open about 8~10 stores, based on their judgments of the market and company’s financial ability.
- The business problem is where are the best locations to open those stores. Without considering rent costs, the company should open a store in the most popular place, where bring stores high traffic and target customers. Therefore, we must know where the company’s target customer mostly like to visit. It can be breakdown to two questions. First, how to find the place our target customers like to visit. In this case, our customer is those 18~30 girls who like fashion clothes, shoes, and bags. Second, where is the most popular places among all the places they like.
- Another problem is to decide the store opening sequence and the possible shopping malls near those optimal locations to open those stores. Maybe we can rank those popular places according to their popularity and open store according to this rank. And we can find nearby shopping malls as a list to give the company’s mangers as a reference.
Report
Suggested new store locations using K-means and DBSCAN clustering with parsed geolocation data including public transport locations, E-commerce delivery addresses, competitors' store locations. More details in the pdf and slides.