Data Collection Methods
Flow supports two main first-party data collection approaches:
Tag-Based Data Collection (Traffic Data)
PII (Personally Identifiable Information) -Based Audience Sharing
Tag-Based Data Collection (Traffic Data)
Flow provides a tracking tag that the publisher places on their website.
The tag is deployed through:
Google Tag Manager (recommended)
Directly in HTML or JavaScript
Flow captures website traffic data and segments users based on their page visits, interests, and behaviour.
These audience segments are then made available for ad targeting.
Meta and TikTok
A pixel is created, and audiences are segmented within the pixel. These segments can be shared individually. If no pixel exists, we can create one for you.
Google Ads
A full tag is created. Since Google Ads does not allow audience segmentation within a single pixel, Flow pre-segments the traffic before sharing.
PII-Based Audience Sharing
The publisher provides customer data (e.g., email, phone number) to Flow.
This data is uploaded to Meta and Google Ads to create custom audiences for targeted advertising.
Publishers own the audience but share access with Flow.
It is always advices to hash PII data using SHA-256 before uploading.
Customer e-mail address
Required
SHA-256
Phone
Number with country code (e.g. +27xxxxxxxxx)
Recommended
SHA-256
First name
Customer's first name
Recommended
SHA-256
Last name
Customer's last name
Recommended
SHA-256
City
City of residence
Optional
SHA-256
State/Province
State/Province
Optional
SHA-256
Country
Country (ISO 3166-1 alpha-2 format, e.g., US, ZA)
Required
Plain text
ZIP code
Postal/ZIP code
Optional
SHA-256
Date of birth
YYYYMMDD format (e.g., 19900315)
Optional
SHA-256
Gender
M (Male), F (Female), O (Other)
Optional
SHA-256
Below is an example of before and after data hashing:
-- Before Hashing
email,phone,first_name,last_name,city,state,country,zip,dob,gender
[email protected],+27123456789,John,Doe,Cape Town,Western Cape,ZA,8001,19900315,M
-- After Hashing
email,phone,first_name,last_name,city,state,country,zip,dob,gender
2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824,
7b8b965ad4bca0e41ab51de7b31363a1c873db5a27f259d146fdbc716f2fdf37,
3b5d5c3712955042212316173ccf37be800af5e01a82c4de90d75ff5f42b2fa2,
4e07408562bedb8b60ce05c1decfe3ad16b722309245f5caed37e38034f17772,
1c383cd30b7c298ab50293adfecb7b18,3f786850e387550fdab836ed7e6dc881,ZA,
b2e98ad6f6eb8508dd6a14cfa704bad7,69faab6268350295550de7d587bc323d,
e1671797c52e15f763380b45e841ec32
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