Find profitable locations for new stores
We help business development teams identify profitable locations and reduce scouting time for new stores using our hyperlocal data-driven insights on customer demographics, footfall, and competitor activity.
Our offering
Get in depth knowledge about any location and make site decisions with confidence
What is the competitor activity in the location?
Where are the popular locations with high footfall?
Will the new location cannibalize my existing stores?
Where are my look-alike customers?
Where are the whitespaces in my store network?
We Curate movement data, places data, demographics and consumer spend data form data providers, open source, and web scraping
We use geospatial analytics and AI on movement data to identify customer home/office locations, places visited and store footfall
We then generate hyperlocal insights and visualize the insights on an interactive map using AI/ML
How it works
Our AI powered location tech help you narrow down from 100s of locations to the highest ROI locations
AI-based Location attributes
We score each locality, pincode, mall, street on 100s of parameters such as:
- Population
- Affluence
- Retail index
- Vibrancy index
- Fashion index
- Luxury seekers
- Rent
- and many more
Shortlist locations with high potential
Narrow down from 100s of potential locations using our location attributes to top locations suitable for your business. We also consider whitespaces in your network to suggest top location for new store
Predict revenue potential/ ROI
Predict the revenue potential and ROI of each location using ML that considers 100s of attributes of the catchment area including
- Your 1st party data
- Customer demographics
- Competitor business activity
- Footfall
Find available properties for your requirement
Use our Verified listings of available properties in each shortlisted locality, mall etc to find the most suitable property for your requirement
Why use location insights for site selection
.svg)
.svg){kind=icon}
High opportunity cost
Opening a new store is a growth-oriented strategic decision requiring capital investment
Bad decisions have a very high cost, poor ROI, lost opportunity costs, and eventually lower annual brand P&L at market level
.svg){kind=icon}
Underperforming stores
Many retailers have been struggling with underperforming stores and they routinely shut down 6-10% of stores every year
The problem is aggravated by online retailers, who are able to use web-analytics to target their customer more effectively
.svg)
.svg){kind=icon}
Everchanging retail landscape
Consumer buying power, interests, behaviors, demographics, and local travel patterns change over time
So does the competition at local level
.svg)
.svg){kind=icon}
No reliable sources of data
Information presented by real estate consultants is static and does not consider local competition, visitation and travel patterns
Public sources of data are outdated
Why Spatic
We offer end to end solution customized to your needs. What makes us unique is our ability to identify and use hyperlocal nuances in all insights, analytics, projections and recommendations.
Highly Experienced Team
Our team has decades of experience in building complex AI/ML-driven solutions for location analytics, pricing, promotion, assortment, and demand forecasting in the retail and restaurants industry
Core team of a real estate startup
Our founders have been instrumental in building a $300M real estate startup and scaling the business to ~10M users in India using technology. We understand challenges in finding a good real state property and how location data can solve those challenges.
Leading global apparel retailers
Developed a next-generation assortment optimization system to select the right mix of merchandise at each store. The system optimizes several business KPIs using AI/ML models that predict sales from the descriptions of the clothing. A limited pilot during COVID improved in-store sales by 7%.
Our Partners
Book a Demo
Share your contact details with us to setup a product demo. We will connect with you in a day.
We promise not to spam you.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.