Xpand is a location intelligence tool for retail expansion.

1. XPAND - LOCATION INTELLIGENCE
FOR RETAIL EXPANSION
WHERE SHOULD YOU OPEN YOUR NEXT STORES?
TM

2. Let's give your location decisions
the data science edge!

3. URBAN LOCATIONS

4. URBAN LOCATION SELECTION: A THREE STAGE APPROACH
CITY MODULE LOCALITY MODULE BUILDING BLOCK MODULE
(to select cities
within a state)
(to select localities
within a city)
(to select building blocks
within localities)

5. From population & asset ownership data,
calculate wealth index of each city.
Divide by number of competitor stores to
arrive at retail potential of each city.
Health
Demographic &
community distribution
Visualise data on other decision variables. Choose high opportunity cities.
URBAN LOCATIONS: CITY MODULE
Infrastructure
Literacy & education Financial access
Note: This module works best for Tier 2 and Tier 3 cities (Tier 1 cities are obvious choices).

6. URBAN LOCATIONS: LOCALITY MODULE
Cluster residential & commercial
Points of Interest (POIs).
Residential localities
Commercial localities
&
From population & asset
ownership data, calculate
wealth index of each city ward.
These clusters are the
potential localities to
choose from.
5 KM
Define store catchment
area radius.
From overlaps with city wards,
calculate wealth index of each
catchment area.
Divide by number of competitor
stores to arrive at retail potential
of each locality.
Rank all the localities
& choose the top N.

7. URBAN LOCATIONS: BUILDING BLOCK MODULE
Explore each locality in detail (zoomed in):
Drop pins on potential building blocks, and see:
1. Traffic patterns
2. Property rental rates
of surrounding area.
HIGHER TRAFFIC = HIGHER VISIBILITY
LOWER PROPERTY RENTAL RATES = LOWER COST
Within each locality, select
building block with high
visibility & low rental rate.

8. RURAL LOCATIONS

9. RURAL LOCATION SELECTION: A TWO STAGE APPROACH
DISTRICT MODULE VILLAGE / SMALL TOWN MODULE
(to select districts
within a state)
(to select villages / small
towns within districts)

10. From population & asset ownership data,
calculate wealth index of each district.
Divide by number of competitor stores to
arrive at retail potential of each district.
Health
Demographic &
community distribution
Visualise data on other decision variables. Choose high opportunity districts.
RURAL LOCATIONS: DISTRICT MODULE
Infrastructure
Literacy & education Financial access

11. RURAL LOCATIONS: VILLAGE / SMALL TOWN MODULE
From population & asset ownership
data, calculate wealth index of
each subdistrict.
These nodes are the potential
villages / small towns to
choose from.
25 KM
Define store catchment
area radius.
From overlaps with subdistricts,
calculate wealth index of each
catchment area.
Divide by number of competitor stores
to arrive at retail potential of each
village / small town.
Rank all the villages /
small towns & choose
the top N.
From village / small town location, population &
road network data, perform network analysis to
identify the nodes (weekly migration hubs).

12. AN END-TO-END SOLUTION

13. A UNIFIED DATA SCIENCE DRIVEN WEB APP WITH FIVE MODULES
Urban Locations
City Module - to select cities within a state
Locality Module - to select localities within a city
Building Block Module - to select building blocks within localities
Rural Locations
District Module - to select districts within a state
Village / Small Town Module - to select villages / small towns within districts

14. ADDITIONAL VISUALISATION TOOLS
Heat map of retail penetration to identify
'colder' regions (with lesser penetration).
Voronoi polygons to visualise area
'dominated' by own & competitor stores.

15. WANT TO KNOW MORE?
CONTACT US!
PARTHA BISWAS
CHIEF BUSINESS OFFICER
+91 97481 23311
PARTHA@XELPMOC.IN
Xelpmoc
Bengaluru | Kolkata | Mumbai | Gurugram | London
xelpmoc.in