Address

77 King St W #3000, Toronto, ON M5K 1G8

©2019 by Deep Spatial.

PROBLEM

80% of business data has a location dimension (geospatial), however companies fail to utilize it effectively: 
GIS is complex and hard to use
It is Difficult to gain actionable business insights from geospatial data as it is limited to insights from maps: ex) tourism statistics/pedestrian data.

Some real worldproblems include:

• Stocking up the wrong inventory in stores
• Sub-optimal marketing communication
• Inefficient store performance owing to opening stores in the wrong location
• Inefficient utilization of available resources

Image by NESA by Makers
 

SOLUTIONS

Deep Spatial combines external consumer data with your sales data to help make profitable/optimal decisions
It offers insights based on demographics, map, affluence, population density/distribution etc
It is also flexible to work with unlimited datasets to get better results

A Platform that can enable business to,

INTEGRATE LOCATION DATA WITH YOUR BUSINESS DATA EASILY.

ENRICH YOUR EXISTING DATA WITH DEEP SPATIAL PRIVATE  DATASETS.

CREATE AND DEPLOY GEOSPATIAL ML MODELS EASILY.

GIVE PREDICTIVE BUSINESS INSIGHTS.

 

PRODUCT

Deep Spatial processes business data geospatially and creates knowledge and insights that help businesses know who their customers are (customer archetypes), predict what they need and supply it optimally. It brings geo-personalisation to any business as a service using AI. Companies like Uber and Airbnb have proved that the ability to utilize location data is very powerful. Deep Spatial can provide it’s AI platform to retail chains, logistics firms, manufacturing supply chain companies, banks and more. We can integrate your data with ours and create personalized insights.

Deep Spatial can help businesses:

• Expand physical locations with less risk by:

  1. Auto recommending cities and locations within the cities to open new stores

• Improve performance of existing stores by:

  1. Creating customer architypes

  2. Running customized promotions

  3. Optimizing in-store inventory based on customer archetypes

• Improving distribution through network analysis

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STITCH LOCATIONAL CONTEXT ON ANY MAP ENGINE.

ADD EXTERNAL PUBLIC, PROPRIETARY & DYNAMIC DATA.

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DEPLOY AI AT SCALE.

Deep Spatial AI can help retailers looking to expand locations determine why certain locations do better then others, then suggest future locations with a high chance of success.