A multi-finance company with over 200 branches in Indonesia, operating for 14 years. The company offers various products including leasing, factoring, and consumer financings such as new and used motorcycle financing, investments, working capital, and multipurpose financing.


Challenges
The multi-finance company uses spatial analysis to:
Identify potential locations suitable for the company’s target market.
Identify the performance of the existing store network.
Result
The multi-finance company collaborated with a professional team from Bhumi Varta Technology to develop a solution to address the above challenges.
The company can determine the best location to add a new network using vehicle data, especially two-wheeled vehicles, commodity data, and people density data (information about crowds in specific areas).
By using commodity data and human movement data in specific areas, the company can determine the economic cycle in a particular area and the sales performance, allowing them to create accurate and highly targeted marketing strategies.
Through this collaboration, the multi-finance company can identify existing stores to obtain parameters that affect the performance of each store and use them as a basis for opening or closing new networks.
Combining the parameters that affect the branch or network’s performance and sales history data, the business can predict sales for each store they have.