Data List to Import Customers
A Datalist in the FirstHive (FH) platform is a named identity used to capture, store, and map customer data from multiple sources. You can ingest data using file uploads (XLS, CSV), pipelines from enterprise data warehouses, or automated sources like S3/FTP. Once imported, the data is structured and mapped to the FH schema, ensuring seamless integration across the platform.
Why Datalists Matter
Datalists are the foundation for how customer data is organized, segmented, and activated across FirstHive. They ensure that imported data is not just stored, but usable across every part of your marketing workflow.
- Campaign Targeting: Choose any Datalist while creating marketing campaigns or exporting data to partners.
- Segmentation: Use the FH segmentation tool to filter, group, and build audiences from your Datalist.
- Multiple Uploads: Upload new or updated data with the same tag, and FH will track and merge accordingly.
- Integration: Connect multiple systems into a single FH instance. You can also ingest historical data in phases.
Where You Can Import Data From
The Import Customers page in the FirstHive UI is your starting point for bringing external customer data into the platform. Whether you’re uploading from Excel files, connecting CRMs, or syncing from landing pages, this dashboard helps you streamline the entire import process.
FirstHive allows you to import customer data from a variety of sources including:
- File Uploads: Excel (XLS), CSV, and PSV formats
- Enterprise Pipelines: Data from warehouses or S3/FTP locations
- CRMs: Platforms like Zoho
- Marketing Tools: MailChimp, CleverTap, etc.
- eCommerce Systems: Such as Shopify
- Lead Capture Tools: Landing pages, web forms, and more
- Social Media Platforms: Facebook, Instagram, and others via automated batch processes
Each source supports different data formats and has specific upload and field-mapping requirements. Once the data is successfully imported, it appears under Manage Datalists for further use in segmentation, campaigns, or analytics.
You can find specific instructions for each data source on its respective page.
How FirstHive Handles Imported Data
When you import data into FirstHive, the platform automatically tags each record and maps it to the selected Datalist. These tags help with segmentation, filtering, and tracking upload history.
If you’re using automated pipelines — such as those from FTP/S3 locations or social media platforms — data flows in at regular intervals without manual intervention.
For example, when you connect a Facebook Business page, FirstHive pulls in post interactions like likes, shares, comments, along with sentiment data and metadata such as names or images. All of this is automatically tagged and mapped into the correct Datalist, ready for further segmentation or campaign use.
How FirstHive Maps and Stores Imported Data
When you import data into FirstHive—whether manually, through automated pipelines, or via social media connectors—it is automatically tagged and mapped to standard fields such as First Name, Last Name, Email, Phone Number, and Location.
To begin, you must create a Datalist from the Import Customers section. You can then upload data multiple times using the same or new datasets. FirstHive uses tags to track each upload, ensuring version history and easy change tracking.
Once imported, all data is organized into two structured tables:
- User Master Table: Stores core customer profile information.
- User Details Table: Captures additional attributes and interaction-level records.
Every transaction is linked to a specific user profile through master data mapping. FirstHive also maintains dedicated storage tables per client account, keeping master and transactional data clean, segregated, and optimized for segmentation, activation, and long-term management.
Key Identifiers in FH
| Identifier | Description |
|---|---|
| Channel ID | Unique to a user interaction on a specific channel. Prevents duplicates across sessions. |
| Enterprise ID | A unique identifier (128-bit UIB) that merges data from multiple channels to form a single unified profile. |
Example: If a user likes five posts across Facebook, FH identifies and maps them to a single Enterprise ID.
FAQs
Q1: What is a Datalist? A Datalist is a named data container in FH used to store and organize customer data from different sources.
Q2: Where is the ingested data stored? Data is stored in the User Master Table and the User Details Table, depending on the type of information.
Q3: How does FH identify unique users? FH uses Channel IDs for channel-specific interactions and Enterprise IDs to unify users across channels.