PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market

#	geohash7	latitude	longitude	cve_ent (entity code)	nom_ent (entity name)	cve_mun (municipality code)	nom_mun (municipality name)	dwell_unique_dev	traffic_unique_dev	unique_dwell_g9	unique_traffic_g9	count_d_devices	dwell_total	traffic_total	observations	men_enoe	women_enoe	avg_age_possible_enoe	avg_education_level_enoe	cannot_read_enoe	can_read_enoe	avg_n_children_enoe	married_enoe	single_enoe	weekend_visits	workday_visits	work_hours_visits	nighttime_visits	avg_hour_visits	avg_day_of_week_visits	avg_distance_work_visits	manufacturing_industry_locations_denue	wholesale_groceries_food_locations_denue	educational_visit_osm	hospital_visit_osm	mall_visit_osm	monthly_income_est_census	total_monthly_income_est_census	expense_v3_census	houses_one_room_census	houses_two_rooms_census	houses_three_rooms_or_more_census	population_c_census	population_d_census	health_expense_census	corporate_visits_denue	hotels_motels_visits_denue	for_sale_properties_pc	for_rent_properties_pc
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Request Data Sample

Volume

rows

Data Quality

95%

quality rate

Avail. Formats

.bin, .json, and .xml

File

Coverage

Country

History

years

Product Attributes

Attribute	Type	Example
geohash7	String	9g6hhzb
latitude	Float	19.0276337
longitude	Float	-98.22807312
cve_ent (entity code)	String	21
nom_ent (entity name)	Text	PUEBLA
cve_mun (municipality code)	String	119
nom_mun (municipality name)	Text	SAN ANDRES CHOLULA
dwell_unique_dev	Integer	249
traffic_unique_dev	Integer	265
unique_dwell_g9	Integer	408
unique_traffic_g9	Integer	295
count_d_devices	Integer	703
dwell_total	Integer	2151
traffic_total	Integer	579
observations	Integer	2730
men_enoe	Float	0.66666667
women_enoe	Float	0.33333333
avg_age_possible_enoe	Integer	47.66666667
avg_education_level_enoe	Integer	99
cannot_read_enoe	Float	0.041322314
can_read_enoe	Float	0.958677686
avg_n_children_enoe	Float	2
married_enoe	Float	0.5
single_enoe	Float	0.5
weekend_visits	Float	0.27006905
workday_visits	Float	0.72993095
work_hours_visits	Float	0.47446575
nighttime_visits	Float	0.52553425
avg_hour_visits	Float	13.9988131
avg_day_of_week_visits	Float	3.97556107
avg_distance_work_visits	Float	27.2500084
manufacturing_industry_locations_denue	Float	0.03030303
wholesale_groceries_food_locations_denue	Float	0.333333333
educational_visit_osm	Float	0.320130358
hospital_visit_osm	Float	0.204813236
mall_visit_osm	Float	0.07871647
monthly_income_est_census	Float	115000
total_monthly_income_est_census	Float	1955000
expense_v3_census	Float	0
houses_one_room_census	Float	0
houses_two_rooms_census	Float	0
houses_three_rooms_or_more_census	Float	0
population_c_census	Float	1
population_d_census	Float	0
health_expense_census	Float	11945.5
corporate_visits_denue	Float	0.0000397938199104442
hotels_motels_visits_denue	Float	0.003784458
for_sale_properties_pc	Integer	11
for_rent_properties_pc	Integer	2

Our dataset provides detailed and precise insights into the business, commercial, and industrial aspects of any given area in Mexico (Including Point of Interest (POI) Data and Foot Traffic. The dataset is divided into 150x150 sqm areas (geohash 7) and has over 50 variables.

- Use it for different applications: Our combined dataset, which includes POI and foot traffic data, can be employed for various purposes. Different data teams use it to guide retailers and FMCG brands in site selection, fuel marketing intelligence, analyze trade areas, and assess company risk. Our dataset has also proven to be useful to explore the Mexican real estate market. - Get reliable data: Our datasets have been processed, enriched, and tested so your data team can use them more quickly and accurately. - Ideal for trainning ML models. The high quality of our geographic information layers results from more than seven years of work dedicated to the deep understanding and modeling of geospatial Big Data. Among the features that distinguished this dataset is the use of anonymized and user-compliant mobile device GPS location, enriched with other alternative and public data. - Easy to use: Our dataset is user-friendly and can be easily integrated to your current models. Also, we can deliver your data in different formats, like .csv, according to your analysis requirements. - Get personalized guidance: In addition to providing reliable datasets, we advise your analysts on their correct implementation. Our data scientists can guide your internal team on the optimal algorithms and models to get the most out of the information we provide (without compromising the security of your internal data). Answer questions like: - What places does my target user visit in a particular area? Which are the best areas to place a new POS? - What are the expending habits of users in a particular area? - What socioeconomic characteristics do the people who travel in a particular area have? - What is the volume of traffic surrounding my current POS? - What is the influx of visits that my competition receives? This dataset is useful for getting insights from industries like: - Retail & FMCG - Banking, Finance, and Investment - Car Dealerships - Real Estate - Convenience Stores - Pharma and medical laboratories - Restaurant chains and franchises - Clothing chains and franchises Our dataset includes more than 200 variables, such as: - Number of users that stays in a specific quadrant. - Resident population. - Food spending. - Spending on arts and recreation. It also includes data from the "ENOE" (National Occupation and Employment Survey) and the "DENUE" (National Statistical Directory of Economic Units), such as: - Percentage of married users - Average scholar grade - Percentage of locations related to agriculture/ manufacturing/ financial services/ wholesale trade of groceries and food (Among others). - Percentage of users within a specific socio-economic segment. - Population segmented by age gap (Example, users from 15 to 29 years old). How efficient is a Geohash? Geohash is a faster, cost-effective geofencing option that reduces input data load and provides actionable information. Its benefits include faster querying, reduced cost, minimal configuration, and ease of use. Geohash ranges from 1 to 12 characters. The dataset can be split into variable-size geohashes, with the default being geohash7 (150m x 150m). Why should you trust PREDIK Data-Driven as your data provider? In 2023, we were listed as Datarade's top providers. Why? Our solutions adapt according to the specific needs of companies. Also, PREDIK methodology focuses on the client and the necessary elements for the success of their projects.

North America (1)

Mexico

1 years of historical data

1 million

rows

License	Starts at
One-off purchase	Not available
Monthly License	Available
Yearly License	Available
Usage-based	Not available

Request detailed pricing

Self-reported by the provider

95%

quality rate

Methods

Frequency

Format

Location Intelligence Site Visitation Retail Site Selection Point of Interest (POI) Mapping

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52 countries covered

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420M MAU

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248 countries covered

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What is PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market?

What is PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market used for?

This product has 5 key use cases. Predik Data-driven recommends using the data for Location Intelligence, Site Visitation, Retail Site Selection, Point of Interest (POI) Mapping, and POI Enrichment. Global businesses and organizations buy Location Data from Predik Data-driven to fuel their analytics and enrichment.

Who can use PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market?

This product is best suited if you’re a Medium-sized Business or Enterprise looking for Location 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.

How far back does the data in PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market go?

This Tabular Data has 1 years of historical coverage. It can be delivered on a weekly, monthly, quarterly, yearly, and on-demand basis.

Which countries does PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market cover?

This product includes data covering 1 country like Mexico. Predik Data-driven is headquartered in United States of America.

How much does PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market cost?

Pricing information for PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market 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 PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market?

Businesses can buy Location Data from Predik Data-driven and get the data via S3 Bucket, SFTP, Email, UI Export, and REST API. Depending on your data requirements and subscription budget, Predik Data-driven can deliver this product in .bin, .json, .xml, .csv, .xls, .sql, and .txt format.

What is the data quality of PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market?

Predik Data-driven has reported that this product has the following quality and accuracy assurances: 95% quality rate. 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 PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market?

This Tabular Data has 3 related products. These alternatives include PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +60 Data Variables for the LATAM Market, The Data Appeal Global Point-of-Interest (POI) Data API, Dataset 251 Millions+ POI Data Mapped Footfall and Sentiment Insights, and Xtract.io - Points of Interest (POI data) Location data Fast-food restaurant company All Subway Brand locations in US and Canada. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.

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License	Starts at
One-off purchase	Not available
Monthly License	Available
Yearly License	Available
Usage-based	Not available

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PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market

Data Dictionary

Description

Geography

History

Volume

Pricing

Suitable Company Sizes

Quality

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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PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +200 Data Variables for the Mexican Market

Data Dictionary

Description

Geography

History

Volume

Pricing

Suitable Company Sizes

Quality

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