Envestnet | Yodlee's De-Identified Retail Transaction Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

#	unique_mem_id	unique_bank_account_id	unique_bank_transaction_id	amount	currency	description	transaction_date	post_date	transaction_base_type	transaction_category_name	primary_merchant_name	secondary_merchant_name	city	state	zip_code	transaction_origin	factual_category	factual_id	file_created_date	optimized_transaction_date	yodlee_transaction_status	mcc_raw	mcc_inferred	swipe_date	panel_file_created_date	update_type	is_outlier	change_source	account_type	account_source_type	account_score	user_score	lag	is_duplicate
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx
2	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx
3	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx	Xxxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxx	xxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxx	xxxxxxxxxx
4	xxxxxxxxx	xxxxx	xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxx	Xxxxxxxx	Xxxxxxx	xxxxx	xxxxxxxx	xxxxxxxxxx	Xxxxxx	xxxxxxxxx	Xxxxx	xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxx	xxxxxxxxx	xxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxxx	xxxxxxxx	Xxxxxxxx
5	Xxxxxxxx	xxxxxxxx	xxxxxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	Xxxxx	Xxxxxx	Xxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxx	Xxxxxxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxx	Xxxxxxx	xxxxxxxxx	Xxxxx	xxxxx	Xxxxxx	xxxxxxxxx	xxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxx
6	Xxxxx	Xxxxxxxxx	xxxxxxxxxx	xxxxxx	xxxxxxxxx	xxxxxxx	Xxxxxxx	Xxxxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxxx	xxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxxxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxxx	Xxxxxxxx	xxxxx	Xxxxxx	xxxxxx	xxxxxxxx	xxxxxxx	Xxxxx	Xxxxxxxxx	Xxxxx	Xxxxxxx	Xxxxxxxx	xxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxxxxxx	Xxxxxxx
7	xxxxxxxxx	xxxxxxx	xxxxxxxxxx	xxxxxx	xxxxx	Xxxxxxxxxx	Xxxxxxxxx	xxxxxxx	Xxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxx	xxxxxxxx	Xxxxxx	xxxxxxxxxx	xxxxxxxxx	xxxxx	Xxxxx	xxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxxxx	Xxxxxxxx	xxxxx	xxxxx	Xxxxxxxxxx	Xxxxxxx	Xxxxxxxx	Xxxxxxx	xxxxx	xxxxxxx	Xxxxx	xxxxxxxxxx
8	Xxxxxxxxxx	xxxxxxx	Xxxxx	xxxxxxxxx	xxxxxxxx	Xxxxxxxx	xxxxxxxx	Xxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxx	Xxxxxxxxxx	Xxxxxxx	Xxxxxx	Xxxxxxxxxx	xxxxxxxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	Xxxxx	Xxxxx	Xxxxxxx	xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxxx	xxxxxx	xxxxxxxxxx	xxxxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxx	xxxxxxx	Xxxxxx
9	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxxxx	Xxxxxxx	Xxxxxxx	xxxxxxxx	xxxxx	Xxxxx	Xxxxxxxx	xxxxxxxx	Xxxxxxxxx	xxxxxxxxxx	xxxxxxxxxx	xxxxxxxxx	xxxxxxxxx	Xxxxxxx	Xxxxxxx	Xxxxxxx	Xxxxxxx	xxxxxxx	Xxxxxxxxxx	xxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxxx
10	xxxxxx	xxxxxxxx	Xxxxxxxx	xxxxxx	xxxxxxxx	xxxxxx	Xxxxxxxx	xxxxxxxxx	xxxxx	Xxxxxxxxxx	Xxxxxxxxx	Xxxxxxx	xxxxxxxx	Xxxxxxx	Xxxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx	xxxxxxx	Xxxxxxxxx	xxxxxxxxx	xxxxxxxx	xxxxxxxxx	xxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxx	Xxxxxxxxxx	Xxxxxxxxx	Xxxxxx	xxxxxxxx
...	xxxxxxxxxx	xxxxxxxx	Xxxxx	xxxxxxxx	xxxxxxxxxx	xxxxxxxx	Xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxx	xxxxxxxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxx	Xxxxx	Xxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxx	Xxxxx	Xxxxxxxxxx	Xxxxxxx	Xxxxxxxxxx	Xxxxxxxx	xxxxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxx

#	ticker	brand	quarter	start date	end date	users	txns	spends
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx
2	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx
3	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx
4	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx
5	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx
6	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx
7	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx
8	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx
9	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx
10	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx
...	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx

Volume

+ merchants

Data Quality

99%

% high precision tagging, 600 tickers

Avail. Formats

.sql and .txt

File

Coverage

Country

History

years

[Sample] Sample Consumer Transactions.csv

Attribute	Type	Example
unique_mem_id	Integer	794996014209149592499260
unique_bank_account_id	Integer	206568081043093301913884
unique_bank_transaction_id	Integer	13261778880509950775504945222
amount	Float	6.82
currency	String	USD
description	String	HOBBYLOBBY 4141 MARTIN WAOLYMPIA WA~~XXXXX~~XXXXXX**...
transaction_date	String	10/2/2019
post_date	String	10/2/2019
transaction_base_type	String	debit
transaction_category_name	String	Entertainment/Recreation
primary_merchant_name	String	Hobby Lobby
secondary_merchant_name
city
state
zip_code
transaction_origin	String	Physical
factual_category	String	Businesses and Services,Home Improvement,Interior Design
factual_id
file_created_date	String	10/3/2019
optimized_transaction_date	String	10/2/2019
yodlee_transaction_status	Boolean	f
mcc_raw	Integer	59450
mcc_inferred	Integer	5945
swipe_date
panel_file_created_date	String	12/15/2019
update_type
is_outlier
change_source
account_type	Integer	1
account_source_type	Integer	1
account_score	Float	651.650587
user_score	Float	46.270715
lag	Integer	1
is_duplicate	Integer	0

[Sample] Agg Product Sample.csv

Attribute	Type	Example
ticker	String	DIS
brand	String	The Walt Disney Company
quarter	String	2023 Q1
start date	String	10/1/2022
end date	String	12/31/2022
users	String	25,388
txns	String	62,403
spends	String	4,666,652

Product Attributes

Attribute	Type	Example	Mapping
Ticker		APL
Brand		Apple
Quarter		2023 Q1
Start Date		10/1/22
End Date		12/31/2022
users		22,230
txns		62,413
Spends		4,66,523

Envestnet®| Yodlee®'s Retail Transaction Panels (Aggregate/Row) consist of de-identified U.S. consumer credit/debit/ACH transaction level data, offering a wide view of the U.S. consumer ecosystem in near real-time (T+1).

Envestnet®| Yodlee®'s Retail Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform. Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production. We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data. Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing? Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics. Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking 2. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC) 3. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence 4. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

North America (1)

United States of America

9 years of historical data

9	+ Years history
3,000	+ merchants
600	+ tickers
23	+ million users
48	+ million + accounts

Free sample available

Envestnet | Yodlee has not published pricing information for this product yet. You can request detailed pricing information below.

Request detailed pricing

Self-reported by the provider

99%

% high precision tagging, 600 tickers

Methods

Frequency

Format

Alpha Generation

Credit Card Analytics

Consumer Trend Analysis

Consumer Profiling Revenue Forecasting

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What is Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts?

Envestnet® Yodlee®’s Retail Transaction Panels (Aggregate/Row) consist of de-identified U.S. consumer credit/debit/ACH transaction level data, offering a wide view of the U.S. consumer ecosystem in near real-time (T+1).

What is Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts used for?

This product has 5 key use cases. Envestnet Yodlee recommends using the data for Alpha Generation, Credit Card Analytics, Consumer Trend Analysis, Consumer Profiling, and Revenue Forecasting. Global businesses and organizations buy Consumer Behavior Data from Envestnet Yodlee to fuel their analytics and enrichment.

Who can use Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts?

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

How far back does the data in Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts go?

This product has 9 years of historical coverage. It can be delivered on a daily, weekly, and monthly basis.

Which countries does Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts cover?

This product includes data covering 1 country like USA. Envestnet Yodlee is headquartered in United States of America.

How much does Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts cost?

Pricing information for Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts is available by getting in contact with Envestnet Yodlee. Connect with Envestnet Yodlee to get a quote and arrange custom pricing models based on your data requirements.

How can I get Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts?

Businesses can buy Consumer Behavior Data from Envestnet Yodlee and get the data via S3 Bucket. Depending on your data requirements and subscription budget, Envestnet Yodlee can deliver this product in .sql and .txt format.

What is the data quality of Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts?

Envestnet Yodlee has reported that this product has the following quality and accuracy assurances: 99% % high precision tagging, 600 tickers. You can compare and assess the data quality of Envestnet Yodlee using Datarade’s data marketplace. Envestnet Yodlee appears on selected Datarade top lists ranking the best data providers, including Best Credit & Debit Card Transaction Data Providers: Q1 2023.

What are similar products to Envestnet Yodlee’s De-Identified Retail Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts?

This product has 3 related products. These alternatives include Envestnet Yodlee’s De-Identified Travel Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations 90M+ Accounts, Consumer Edge Vision Retention Data CPG, Grocery, Food Delivery Psychographic US Transaction 100M+ Cards, 12K+ Merchants, Retail & Ecommerce, and GapMaps Consumer Behaviour Data by AGS USA 1800 indexes. You can compare the best Consumer Behavior Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Envestnet | Yodlee's De-Identified Retail Transaction Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Quality

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Envestnet | Yodlee
Empowering the Intelligent Financial Life™

Envestnet | Yodlee's De-Identified Retail Transaction Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Quality

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Envestnet | Yodlee Empowering the Intelligent Financial Life™

Envestnet | Yodlee
Empowering the Intelligent Financial Life™