Opah Labs Consumer Behavior Data | B2B2C | 800K Total Records w/ Weekly Updates |
# | id |
second_name |
deleted |
created_by_user_id |
updated_by_user_id |
created_at |
updated_at |
password_hash |
password_salt |
village |
voter_id |
avatar_file_name |
avatar_content_type |
avatar_file_size |
avatar_updated_at |
country_id |
role_id |
company_id |
account_id |
district |
income_source |
gender |
shopkeeper |
newpin |
subdistrict |
registar |
loan |
reg_status |
reg_by |
reg_agent_id |
sc |
status |
location |
constituency |
birth_year |
account_type |
name |
balance |
debit |
credit |
transaction_type |
user_id |
counter_user_id |
counter_phone_number |
counter_account_id |
gid |
|||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx |
2 | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | 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 |
3 | 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 | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx |
4 | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | 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 |
5 | 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 | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx |
6 | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | 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 |
7 | 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 |
8 | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx |
9 | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx |
10 | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx |
... | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
id
|
Integer | 900000001 | |
String | Email Address | ||
String | Contact Last Name | ||
String | Contact First Name | ||
second_name
|
String | REDACTED | |
String | English | Language Name | |
deleted
|
Integer | 1 | |
created_by_user_id
|
Integer | 900000001 | |
updated_by_user_id
|
Integer | 980190962 | |
created_at
|
DateTime | 2012-05-06T12:49:42+00:00 | |
updated_at
|
DateTime | 2013-03-04T16:54:00+00:00 | |
password_hash
|
String | REDACTED | |
password_salt
|
String | $2a$10$KWWg6WqcLRS/MZFj9GD0mO | |
village
|
String | REDACTED | |
voter_id
|
String | demo | |
avatar_file_name
|
String | missing.png.gif | |
avatar_content_type
|
String | image/gif | |
avatar_file_size
|
Integer | 390 | |
avatar_updated_at
|
DateTime | 2013-03-04T16:53:59+00:00 | |
country_id
|
Integer | 1 | |
role_id
|
Integer | 1 | |
company_id
|
Integer | 1 | |
account_id
|
Integer | 7000001 | |
district
|
String | REDACTED | |
income_source
|
String | demo | |
gender
|
String | ||
shopkeeper
|
Boolean | t | |
newpin
|
Integer | 1 | |
subdistrict
|
String | REDACTED | |
registar
|
Integer | 1 | |
loan
|
Integer | 0 | |
reg_status
|
|||
reg_by
|
String | SMTZ00000096 | |
reg_agent_id
|
String | SMUG00000005 | |
sc
|
Integer | 1 | |
status
|
Integer | 1 | |
location
|
String | REDACTED | |
constituency
|
String | CTR | |
birth_year
|
String | REDACTED | |
account_type
|
String | SM ACCOUNT | |
name
|
String | REDACTED | |
balance
|
Integer | 1051070 | |
debit
|
Integer | 0 | |
credit
|
Integer | 160000 | |
transaction_type
|
String | cashin-credit | |
user_id
|
Integer | 980191075 | |
String | Phone Number | ||
counter_user_id
|
Integer | 980190962 | |
counter_phone_number
|
String | REDACTED | |
counter_account_id
|
Integer | 8000612 | |
gid
|
Integer | 890000000 |
Description
Country Coverage
History
Volume
884,000 | Records |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License | Not available |
Yearly License | Available |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates ?
The dataset provides secure, user-centric consumer behavior data for finance, insurance, and real estate. It offers insights into transaction history and personal preferences, ensuring global coverage, high consistency, and reliable quality for informed decision-making.
What is Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates used for?
This product has 5 key use cases. Opah Labs recommends using the data for Financial Services, Insurance, Global, Digital Payment, and B2B2C. Global businesses and organizations buy Consumer Behavior Data from Opah Labs to fuel their analytics and enrichment.
Who can use Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates ?
This product is best suited if you’re a Medium-sized Business looking for Consumer Behavior Data. Get in touch with Opah Labs to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates go?
This product has 10 years of historical coverage. It can be delivered on a weekly and monthly basis.
Which countries does Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates cover?
This product includes data covering 2 countries like Tanzania and Uganda. Opah Labs is headquartered in United States of America.
How much does Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates cost?
Pricing information for Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates is available by getting in contact with Opah Labs. Connect with Opah Labs to get a quote and arrange custom pricing models based on your data requirements.
How can I get Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates ?
Businesses can buy Consumer Behavior Data from Opah Labs and get the data via S3 Bucket. Depending on your data requirements and subscription budget, Opah Labs can deliver this product in .json, .csv, and .xls format.
What is the data quality of Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates ?
Opah Labs has reported that this product has the following quality and accuracy assurances: 100% Match Rate. You can compare and assess the data quality of Opah Labs using Datarade’s data marketplace.
What are similar products to Opah Labs Consumer Behavior Data B2B2C 800K Total Records w/ Weekly Updates ?
This product has 3 related products. These alternatives include Opah Labs B2C Contact Data 800K Total Records w/ Weekly Updates, Accurate Append Verified US Fundraising & Donor Data Consumer Donation History High Match Rate Batch & API Delivery, and WiserBrand Consumer Review Data Consumer Behavior Reasons of the calls from consumers to companies. 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.