TikTok Influencer Ranking Analytics API

Retrieve ranked lists of TikTok influencers sorted by metrics such as follower count, GMV, and engagement rate, computed from large-scale analytics data.

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GET/v1/tiktok/influencer/ranking/analytics

datestringrequired

The format is yyyy-MM-dd. The rankings are divided into three categories: daily, weekly, and monthly. Weekly rankings are held every Monday, and monthly rankings are held on the first day of each month.

regionstringrequired

Region code, region, such as US

influencer_category_namestringoptional

Category filter

product_category_idstringoptional

product_category_list

rank_typeintegerrequired

1=day 2=week 3=month

influencer_rank_fieldintegerrequired

List sorting type 1=total_followers_cnt 2=total_sale_cnt

page_numintegerrequired

Page numbers start from 1 and go up to a maximum of 100,000.

page_sizeintegerrequired

The maximum number of pages is 10.

TikTok API Use Cases

Influencer Vetting

Verify creator data before signing deals. Pull live stats instead of relying on self-reported media kits.

Audience Intelligence

Understand a creator's audience demographics and engagement patterns for campaign targeting.

Competitor Monitoring

Track competitor brands or creators over time by polling this endpoint periodically.

Frequently Asked Questions

Is the TikTok API official?

No, KeyAPI provides an unofficial TikTok API that lets you access TikTok data through our platform. We handle the complexities of data collection so you can focus on building your application.

How current is the data?

We provide real-time data from TikTok. When you make a request, we fetch the latest information available.

How do credits work?

Each API endpoint consumes credits. Most endpoints cost just 1 credit. All pricing is transparent in our API documentation with no hidden fees.

Can I use this for AI model training?

Yes. KeyAPI provides structured, AI-ready data ideal for training datasets, fine-tuning LLMs, and building AI pipelines. Our historical archives are particularly valuable for large-scale training workloads.

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