TikTok Dataset for Research, Trend Analysis, and Market Intelligence

Targeted data scope
Time-stamped trend data
Managed source updates

Need TikTok data that matches your research or business case? DataOx collects a custom TikTok dataset around the videos, creators, hashtags, comments, and engagement signals that matter to your use case.

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Scalable data access solutions

Start with a single TikTok dataset and expand it to scheduled data streams as your data needs grow

Scheduled trend tracking data updates

Update TikTok trends data on videos, creators, hashtags, and user engagement at a consistent frequency

Continuous source maintenance partnership

Data collection logic remains intact even if changes are made to TikTok’s public interface

TikTok Dataset That Remains Usable

Most TikTok datasets are one-time exports. DataOx validates the quality of the output and maintains the collection logic as TikTok changes its public interface, helping keep the data consistent and ready for use. Your team doesn’t have to manually identify incomplete records, rebuild field mappings, or replace the entire dataset after every source change.

Video information

Video URL and ID
Caption
Publication date
Duration
Sound details

Creator information

Username and profile URL
Display name
Follower and following counts
Total profile likes
Verified status

Hashtags and topics

Hashtags used
Caption keywords
Mentioned accounts
Linked sounds
Topic labels, if required

Engagement signals

View count
Like count
Comment count
Share count
Time-stamped metric snapshots

Comment information

Comment text
Publication date
Reply structure
Comment likes
Public commenter handle

Collection metadata

Source URL
Collection timestamp
Search query or hashtag
Language and market filters
Data freshness status

use cases

Product Questions in TikTok Comments

After a smaller beauty creator posts a review, the same questions start appearing in the comments: Does the SPF pill? Is it suitable for oily skin? Can it be worn under foundation? The brand did not commission the video and only notices the conversation by chance. DataOx collects relevant TikTok video data, TikTok creator data, captions, hashtags, and comments into a TikTok dataset, so the team can see which questions and concerns are starting to repeat.

Delivery Problems on TikTok

There is no large-scale issue in the support inbox yet. But on TikTok, people are already saying that orders have stalled, no one is responding, and the promised delivery has not arrived. Some comments do not mention the brand at all, only the product name or a tracking screenshot. For this type of task, TikTok data scraping can be configured around the brand, product names, delivery topics, and complaint variations, so the team sees the videos and conversations before the issue escalates.

Viral Video or Real Demand?

On Monday, a buyer sees a viral video about a thermos mug and asks to increase the next order urgently. By Tuesday, it becomes clear that the video took off because of the joke in it, not because of the product itself. TikTok trends data helps the team see whether interest continues in new videos and over time, or whether it is simply short-lived hype.

Finding Creators Who Fit Your Audience

The team compiles a list of creator accounts by follower count. Then they open the profiles and find that one creator with a large audience has been posting comedy videos for months, another focuses on local restaurant reviews, and only a third regularly talks about the right product category. DataOx can collect TikTok video data and TikTok creator data on video topics, language, posting frequency, brand mentions, and comment reactions, so creator selection starts with content fit rather than an impressive number on a profile.

Promo Code Questions After a Campaign

The campaign ended two weeks ago, but an older creator video keeps gaining views. In the comments, people ask whether the code still works, why the price is different, and where to find the product. DataOx structures the TikTok dataset around promo codes, product mentions, publication dates, and related comments, so the marketing team can see which older posts are still shaping expectations and what needs to be updated or clarified.

Businesses we serve

Small agencies Medium-sized companies Enterprises

Delivery schedule

Real-time Daily Weekly Monthly Custom On demand

Keep Your Research Context

DataOx creates a TikTok dataset that can grow with your research needs over time. Instead of receiving a disconnected collection of videos, creators, hashtags, and comments, your team gets one structured dataset with the context needed to filter, compare, and reuse records for new research questions. This means your team does not have to start from scratch every time.

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Data Delivery Formats

TikTok Data for Your Workflow

DataOx delivers your TikTok dataset in a format and structure that fit your team’s existing tools and workflows.

CSV

Excel (XLSX) / Google Sheets

Excel

JSON

API Integration

API

Database Direct

Database

Custom

Python web scraping – Web scraping with Python for pricing and inventor

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Let’s talk

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Why choose DataOx

Data you can rely on

Custom Solutions

DataOx builds the process and dataset around your task instead of making you adapt to a ready-made product.

Change Management

When sources, fields, or your requirements change, DataOx updates the process without interrupting operations.

Cost Efficiency

You pay for the data volume and work you need, not for features you do not use.

Security

Project data and requirements are protected by NDAs, restricted access, and agreed working rules.

unlock market insights with our TikTok dataset

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what our clients say about us

I’ve worked with Vladislav and DataOx twice now and have been impressed both times. They don’t just do everything they committed to do — on time and on budget — but they go above and beyond. On this second project, they showed initiative and added something they suspected I would want. They were right. I cannot recommend him and them any more enthusiastically. I’m a big fan.

jeff leitner

March 13, 2026

We worked with the DataOx team on a complex internal project that involved building a custom software solution with Slack Bot integration, sophisticated server-side logic, and automated API workflows. The system needed to fetch, process, and store data in an intermediate database, and—only if specific conditions were met—push that data through additional APIs to our target software. It was no small task.
So far, everything is running flawlessly, and we couldn’t be more satisfied. Their communication was consistently sharp, fast, and proactive—so fast, in fact, we sometimes had to catch up with them! Whether it was refining a feature, squashing a bug, or adjusting requirements on the fly, the team was always on it.

What really stood out was the professionalism: we had a dedicated, experienced project manager who kept everything aligned and moving smoothly. DataOx truly listens, understands your needs, and delivers high-quality work with precision.

If we could give 10 stars, we would. Highly recommend this outstanding team—and we’re definitely looking forward to working with them again!

ilia sokolovskiy

March 13, 2026

We’re a UK based operation, and have worked on a couple of projects with DataOX over the last two years. I’ve been impressed with every project, as they’ve been delivered to the spec I’ve requested, alongside all the changes I asked for along the way.

I was initially concerned about whether there would be a language barrier, but the developers, business leads and representatives of the company communicate in excellent English.

We’ll continue to work with DataOX on projects in the future, and I’d highly recommend them to anybody reading this!

andrew napier

March 13, 2026

Prompt. Got Job Done exactly how we wanted. Communicated clearly with the team about expectations and deadlines.

mike goetsch

March 13, 2026

High Quality, fast data scraping from the team at DataOx. Very communicative and always proactive in understanding requirements before starting the work. Used multiple times, and will be using in the future!

andrew haynes

March 13, 2026

Both the quality and the speed of delivery were awesome, and the communication along the way with our project manager and sales leader was perfect. They were both good at eliminating ambiguity in our requirements which resulted in a delivery we are very happy with.

josh albrechtsen

March 13, 2026

I worked with DataOx on a data scraping. everything was done on time and with high quality. Vladislav and his team showed a high level of professionalism and attention to detail. I recommend DataOx to anyone looking for reliable specialists in web scraping!

olim rakhmatov

March 13, 2026

These guys are simply the greatest. They are timely and accurate in their work, they communicate quickly, and I feel they genuinely understand and care for our needs. Whatever we have asked for, they have delivered. They made us a web scraper and automated many processes for our webshop. We started working together with Andrew and Bogdan in November 2022, and they are a delight to work with. Bogdan as our project leader, has been great! We will continue to work with DataOx for our projects.

petter trønsdal

March 13, 2026

FAQ: common questions about DataOx TikTok datasets

Why are TikTok datasets important?

Without structure, TikTok often remains a collection of disconnected videos, links, and screenshots that are difficult to analyze. TikTok datasets help teams view TikTok trends data in context.

Why do companies need multiple datasets?

Your team may need to analyze TikTok creator data, review comments, and compare TikTok data with sales or campaign results at the same time. Separate but aligned TikTok datasets help avoid putting every task into one overloaded file and make previously collected data easier to reuse.

What are the three main types of data a TikTok dataset can combine?

A TikTok dataset can combine structured data, such as IDs, dates, and engagement metrics; semi-structured data, such as hashtags, mentioned accounts, or lists of related objects; and unstructured data, such as captions and comments. TikTok’s official Research API documentation describes fields such as video IDs, publication time, usernames, region codes, and video descriptions.

What are the main quality criteria for a TikTok dataset?

The key criteria are completeness, accuracy, uniqueness, consistency, and relevance to scope. For TikTok data, this means required fields are present, date and metric formats are consistent, duplicates are flagged or removed according to agreed rules, and records match the selected topics, markets, and time period. AWS also identifies completeness, accuracy, and uniqueness as critical data-quality attributes. See AWS data-quality guidance.

What does TikTok dataset management involve?

Managing a TikTok dataset includes maintaining the schema, naming conventions, metadata, versioning, selection criteria, and retention rules. For recurring deliveries, this also means preserving context: which fields were collected, when the data was updated, and which rules determined whether a record was included in the dataset.

What types of fields can a TikTok dataset contain?

TikTok video data can include numbers, for example views and likes. TikTok creator data can include categories, for example language, market, or creator category. Text fields may include captions and comments. Time-based fields can show when a video was published and when the data was collected. The dataset may also contain lists of hashtags or mentioned accounts. The exact fields depend on the project scope.

How does the dataset scale as data volume and research needs grow?

TikTok data scraping can begin with a one-time dataset for a narrow scope and later extend to new topics, markets, creator lists, or scheduled updates. DataOx agrees the schema, delivery cadence, data volume, and retention rules in advance, so expanded coverage can build on the existing structure, mappings, and delivery workflow rather than requiring a full rebuild.