Competitive Intelligence Data for Manufacturing & Industrial Companies

#	relation_intensity	company_likeliest_relation	company_name	company_category	company_website_domain	company_linkedin_category	company_linkedin_subcategory	company_address	company_city	company_county	company_state	company_latitude	company_longitude	company_area_sqft	company_naics	company_naics_2d	company_naics_4d	company_naics_6d
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Avail. Formats

.json and .csv

File

Coverage

Countries

[Sample] PREDIK_DataDriven_competitive_intelligence_sample.csv

Attribute	Type	Example	Mapping
relation_intensity	Float	5.88070057
company_likeliest_relation	String	SUPPLIER
company_name	String	COUNTY MATERIALS CORPORATION	Company Name
company_category	String	CONCRETE PRODUCT SUPPLIER	Company Industry
company_website_domain	String	http://www.countymaterials.com	Company Website
company_linkedin_category	String	Construction	Company LinkedIn
company_linkedin_subcategory	String	Building Materials
company_address	String	702 N EDWIN ST	Company Address
company_city	String	Sadorus	City Name
company_county	String	Champaign County	County Name
company_state	String	Illinois	State Name
company_latitude	Float	40.12431153	Latitude
company_longitude	Float	-88.26708576	Longitude
company_area_sqft	Integer	4379
company_naics	Integer	327320	Company NAICS Code
company_naics_2d	String	MANUFACTURING	Company NAICS Name
company_naics_4d	String	CEMENT AND CONCRETE PRODUCT MANUFACTURING
company_naics_6d	String	READY-MIX CONCRETE MANUFACTURING

With a unique and novel approach that combines geolocation methodologies and alternative data, we have developed a Data Solution that helps companies understand competitors, suppliers, and customers in depth.

We help our clients to draw connections between companies and facilities, map markets and supply chains and uncover and visualize hidden relations between companies. Given a specific U.S. or Europe-based company, we draw a connections map, including all detected relationships between that company and other companies and facilities nationwide, statewide, and between countries. Markets we can address We can identify and detect connections between facilities and companies across the United States, and across countries and within them in Europe. What makes us different? We have developed a brand-new technology that combines the use of alternative data and machine learning methodologies, what allows us to perform competitive analysis in a non-traditional way, by studying a specific facility and detecting and drawing all the connections between the facility and other locations. We use publicly available information such as location data and building footprints to identify and geolocate company facilities. With a machine learning algorithm, we identify movement patterns between these locations. Already Validated Use Cases - Market Intelligence & Due Diligence Company: A large multinational company that provides specialized materials to different industries. Challenge: How to find a cost-effective way to analyze the competition and identify potential customers? Solution: Relationship data with a geolocation approach to unveil the DNA of a facility. Results: Identify competitors' clients and suppliers. - Risk Assessment Company: A leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services. Challenge: How to anticipate and prevent possible disruptions in all the tiers of the supply chain? Solution: Inter-company data with a geolocation approach to detect and measure relations between companies and facilities in the US. Using the movements of physical goods between different companies and locations, the supply chains can be inferred and analyzed. Results: Anticipate potential disruptions by understanding behavior in all the tiers of the supply chain. - Asset Protection & Loss Prevention Company: A large multinational corporation in the industrial and logistics sector. Challenge: How to optimize the asset recovery strategy in a network of more than 1 million locations nationwide? Solution: A machine learning model that combines client´s own data and a geolocation approach to track assets´ movements between facilities. Results: Improvement in the identification of facilities where the presence of assets to be recovered is higher. Other Use Cases - Monitor company supply chains (paired with import-export data if additive). - Provide a proxy for manufacturing/production (e.g., monitoring activity from factories to warehouses).

North America (2)

Mexico

United States of America

Free sample available

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Request detailed pricing

Methods

Frequency

Format

Competitor Analysis

Sales Intelligence

Competitive Intelligence

Supply Market Analysis

Supplier Data Enrichment

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What is Competitive Intelligence Data for Manufacturing & Industrial Companies?

What is Competitive Intelligence Data for Manufacturing & Industrial Companies used for?

This product has 5 key use cases. Predik Data-driven recommends using the data for Competitor Analysis, Sales Intelligence, Competitive Intelligence, Supply Market Analysis, and Supplier Data Enrichment. Global businesses and organizations buy ESG Data from Predik Data-driven to fuel their analytics and enrichment.

Who can use Competitive Intelligence Data for Manufacturing & Industrial Companies?

This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for ESG Data. Get in touch with Predik Data-driven to see what their data can do for your business and find out which integrations they provide.

Which countries does Competitive Intelligence Data for Manufacturing & Industrial Companies cover?

This product includes data covering 2 countries like USA and Mexico. Predik Data-driven is headquartered in United States of America.

How much does Competitive Intelligence Data for Manufacturing & Industrial Companies cost?

Pricing information for Competitive Intelligence Data for Manufacturing & Industrial Companies is available by getting in contact with Predik Data-driven. Connect with Predik Data-driven to get a quote and arrange custom pricing models based on your data requirements.

How can I get Competitive Intelligence Data for Manufacturing & Industrial Companies?

Businesses can buy ESG Data from Predik Data-driven and get the data via S3 Bucket and Feed API. Depending on your data requirements and subscription budget, Predik Data-driven can deliver this product in .json and .csv format.

What is the data quality of Competitive Intelligence Data for Manufacturing & Industrial Companies?

You can compare and assess the data quality of Predik Data-driven using Datarade’s data marketplace. Predik Data-driven has received 3 reviews from clients. Predik Data-driven appears on selected Datarade top lists ranking the best data providers, including Best +8 Airport APIs to use in 2023.

What are similar products to Competitive Intelligence Data for Manufacturing & Industrial Companies?

This Tabular Data has 3 related products. These alternatives include Competitive Intelligence Data for Food & Beverage Industry, HitHorizons Manufacturing Company Data API CSV JSON 4,289,762 Companies 50 European Countries Data Enrichment Monthly Updated, and Forager.ai - Startup Data Company Data Refreshed 2x/Mo Delivery Hourly via CSV/JSON/PostgreSQL DB Delivery. You can compare the best ESG Data providers and products via Datarade’s data marketplace and get the right data for your use case.

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Yearly License	Available
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Competitive Intelligence Data for Manufacturing & Industrial Companies

Data Dictionary

Description

Geography

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Predik Data-driven
Problem Solving with a Data-Driven Approach

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Competitive Intelligence Data for Manufacturing & Industrial Companies

Data Dictionary

Description

Geography

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Predik Data-driven Problem Solving with a Data-Driven Approach

Trusted by

Predik Data-driven
Problem Solving with a Data-Driven Approach