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Join Apify TikTok Profile Scraper with Socialgist Reviews
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Apify TikTok Profile Scraper
Get profile details via Apify's TikTok Profile Scraper. To use this Actor, fill in the profile names you want to gather information about.
For each TikTok profile, you will extract:
Basic profile details: name, nickname, bio, ID, and profile URL.
Account status: whether the account is verified or not, and if it's a business and seller account.
Follower and engagement metrics: number of followers and accounts followed.
Profile avatar: avatar URLs.
Content information: number of videos, fans, hearts, friends, and likes.
About Socialgist Reviews
Covering over 50 Chinese review platforms and over 250 English review platforms, this dataset offers insights into customer satisfaction, product feedback, and consumer trends. Whether it’s understanding how products are received, tracking competitor performance, or identifying areas for improvement, Socialgist Reviews dataset provides the real-world voice of the customer, crucial for market analysis, product development, and brand management.
Quickly connect Apify TikTok Profile Scraper and Socialgist Reviews with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Apify TikTok Profile Scraper
For robust enterprise data integration, web data acts as a foundational source. It can be drawn from a variety of channels—including third-party partners, internal applications, and public web repositories.
Step 2
Add Socialgist Reviews with Unify or another transformer to combine schemas
To accelerate using your web data, you can apply any number of operations to the data. Enrich, augment, join, structure, filter, storage, search, or more! Datastreamer has hundreds of plug-and-play operations that you can apply.
Step 3
That's it! You have just connected Apify TikTok Profile Scraper and Socialgist Reviews
With Datastreamer it’s never been easier to use web data. You can dynamically expand your Pipelines with more capabilities, and you’ve now been able to solve your operational bottlenecks in working with web data.