Headquartered in San Fransisco, this energy recovery device manufacturer aims to solve the complex challenges of refrigeration systems in commercial and industrial space. They manufacture Co2 refrigeration systems that can be used instead of super-polluting hydrofluorocarbons (HFCs) refrigeration systems to store dairy products, frozen food, meat, or other food products.
Their highly -efficient devices reduce the energy consumption and operating costs of CO2 refrigeration systems and increase their efficiency, particularly in higher ambient temperatures. Their target audience for this type of refrigeration system is grocery stores, supermarkets, and retail brands that use refrigeration systems in their warehouse to store food products.
The company wanted the POI data of these target audiences from the US location to pitch their highly reliable and sustainable energy recovery devices.
Traditionally, Co2 refrigeration systems are costly and require high energy and operating costs. Therefore, it is challenging for high-end retail brands to switch from polluting systems to this environment-friendly and sustainable Co2 systems
Therefore, the company wanted to identify the more prominent brands primarily from the retail industry and supermarkets & grocery, restaurants, etc. who use large refrigeration systems in their datawarehouse. Upon identifying these brands, the company can perform their market analysis, consumer behavior, the durability of products from such systems, carbon footprint release, and many more.
The company wanted POI data from 38 different sub-categories from the retail industry as mentioned below in 3-4 weeks.
|Catagories||# of domains||Catagories||# of domains|
|Arts and crafts||6||Housewares||2|
|Charging stations||3||Music, Video and DVD||3|
|Computer and Electronics||12||Paint||5|
|Convenience store||271||Pawn shops||2|
|Departmenta store||61||Pawn shops||3|
|Florists||2||Photos and frames||2|
|Food and Beverage||14||Shoes||44|
|Fuel stations||110||Sporting good||38|
|Furniture and decor||41||Super market and groceries||392|
|Gift and Novelty||9||Telecom||9|
|Health and died foods||9||Video games||1|
|Home centers||17||Warehouses and wholesale stores||4|
|Home improvement||1||Watches and Jewellery||27|
|Total # of Domains||1372|
Xtract.io started by identifying the major brands to inculcate the usage of Co2 systems. Upon identifying, our GIS experts started collecting the following details of the specific brand, store, or retail-related POI.
|Domain ID||Location Name|
|Street Address||Address Extended|
|Website||Hours of Operations|
|Telephone||Latitude & Longitude|
The data collected was 95% accurate, validated in-depth, and was delivered in 8-10 business days ensuring global coverage as requested by the client. Through our POI datasets, the data analysis process for our customer become easier and faster as the extracted location points was accurately created and cleansed thoroughly. Xtract.io POIdata was “analytics-ready” right from the word go
A total of 1M+ POI data for 38 sub-categories, across 1372 brands were collected, crafted manually, and delivered to the client successfully.