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Location Analytics: A case study to identify specific customer segment in an area

Location Analytics: A case study to identify specific customer segment in an area


Pressto – Spain originated la tintorería & lavandería servicios (Dry cleaning & laundry) successfully marked its entry in India in 2008 and now servicing to more than 50,000 satisfied customers across Mumbai & Delhi. Pressto has an aggressive plan to increase penetration in the above two cities in coming months in addition to growing in newer cities in India. The client wants to assess the business potential for existing and potential stores to set an internal business target. Another objective is to identify a concentration of specific customer segment in an area to conduct focus marketing.


Quantta analyses customer segment and catchment area for each store. Socioeconomic profile of each segment is analysed on multiple dimensions like gender, age, income, etc. along with customer buying pattern. The customer profile for Pressto can be defined as all the households having the annual income of Rs 30 lacs and above per annum. There is no gender preference as the stores receive an equal number of garments from both the genders. It has been observed that people living within 1 km radius from the store are the most frequented customers. People living between 1 and 3 km visit the stores infrequently. Following steps are performed to determine business potential:

  • 3 km radius around a store is considered as a catchment area.
  • The entire area is divided into 1km × 1km grids to determine business potential at a micro level.
  • High-resolution satellite image processing technique is utilized to segment buildings into different categories like commercial vs residential, permanent vs non-permanent structures, open space vs inhabited area, etc.
  • Count total structures under each category
  • Estimated total number of household and total number of target household (profile similar to existing customer segment of Pressto) in each of this 1km × 1km grid
  • Validation of data using other external resources
  • Segment target household into multiple categories based on estimated business volume per customer
  • Business potential is further refined using a distance of household from the store.
  • Competition is mapped for each grid
  • Market share is projected using competition index


  • Determine business potential for each store, which is used to set business targets
  • Micro level analysis helps the client to determine market share at each grid (1km × 1km).
  • GIS heat map helps the client to visualize each grid based on business potential and existing market share. This helps the client to formulate detail marketing plan by micro area
  • Estimated benefit is 20% additional revenue and 10% reduction in marketing cost

Sample Report

The report shows heat map by grid in terms of attractiveness. Darker the colour is higher the attractiveness of the grid and vice versa. It helps the client to identify the attractive areas around the existing store. Mapping competitors and other important sales generators (establishments those help increasing sales directly / indirectly) provides additional information about important POIs (point of interest) for marketing campaigns in and around the area.

See Also

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  • In the realm of retail, marketing and digital commerce, analytics needs to factor-in the geographic / location aspect….the ‘where is’ question. To the best of my knowledge, Quantta Analytics is the first company in India to provide solutions that integrate GIS with analytics. As the above case study exemplifies, location helps customer profiling and mapping, make site selections, identify best performers, increase conversions with geo-targeting … the list is endless. The location analytics world market is predicted to reach $11.84 billions by 2019, although one is yet to see a report for India.

    • Hi Sangeeta, thank you very much for your comments. “Where” is a key question when we decide how to grow our business. This is the future!

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