Measure TikTok more effectively with media mix modeling
TikTok continues to strengthen its MMM data capabilities, providing more actionable insights for your TikTok campaigns.
Media mix modeling (MMM) has long been a reliable way to measure the holistic impact of marketing investments and optimize budget allocation in a fragmented media environment. As the industry continues to move away from cookies and toward privacy-first solutions, MMM has re-emerged as a resilient way to measure impact across marketing touchpoints and gain accurate, actionable insights for your campaigns.
What's new: API in open beta and earned data now available
Media mix modeling is generally carried out as a collaboration between several key players, ranging from media agencies, media mix modeling research vendors, advertisers, publishers, and more.
Data quality is the foundation of any successful MMM—poor-quality data leads to inaccurate insights and unreliable models. But with the right insights, advertisers can make more informed decisions about budget allocation and optimization.
We previously partnered with key media mix modeling industry leaders—Nielsen, Circana (formerly IRI and NPD), Analytic Partners, Ekimetrics, and Transunion (formerly Neustar)—to streamline the global media mix modeling process for advertisers. Now, we’re introducing two major updates to strengthen TikTok’s MMM capabilities.
1. API integration is now in open beta: Say goodbye to manual data pulls! Our new API automatically provides access to your TikTok data, making it easier than ever to feed data into your MMM systems. Want early access? Fill out a form to join the allow list.
2. Earned data now available: You can now integrate earned data from Branded Mission and Branded Effect packages into your MMM alongside traditional paid metrics like ad spend, impressions, clicks, and conversions.
Why media mix modeling matters more in 2025
Traditionally used to measure offline media like TV, media mix modeling has become essential for digital marketing—especially as the industry moves toward privacy-protected measurement approaches.
This method is particularly valuable for TikTok because user journeys aren’t always linear. People discover products through entertainment, not just by clicking on ads. They engage, create, search, and eventually purchase—often across different platforms or in physical stores.
This means that traditional last-click models don't capture TikTok's true contribution to the purchasing journey. According to a recent MMM analysis by Ovative Group, on average, TikTok’s actual ROI is 23x higher than what last-click attribution models report.¹ A separate MMM study by Nielsen showed that TikTok is 2.5x more efficient than both online video and TV, and 20% more efficient than social media at driving retail sales.²
“Marketers have long been misled by last-click models, which capture only a fraction of the true value,” says Beth McKigney, SVP of Measurement and Technology Solutions at Ovative Group. “With enhanced measurement, we’re proving TikTok’s revenue-driving power—not just in conversions, but in building long-term, profitable customer relationships.”
Media mix modeling, on the other hand, provides a more holistic view of ad performance and actionable insights to guide your marketing strategy. German carmaker Volkswagen was able to shift budgets from underperforming channels to TikTok after an MMM study with Annalect revealed it to be three times more efficient than other digital media platforms. Similarly, by leveraging MMM, beauty and skincare brand Boots found that aligning TikTok campaigns with TV ads resulted in a 1.4x boost in TikTok's ROI.
The benefits of TikTok's API
TikTok's media mix modeling API allows for the automated scheduling of data downloads, ensuring a consistent and up-to-date flow of information. Integrating the API into your systems saves time, reduces manual errors, and maintains a steady stream of insights for your MMM. Nielsen was among the first measurement partners to integrate TikTok's MMM API.
"MMM relies on high quality, granular data received in a timely manner," said Karen Gentleman from Nielsen’s Strategic Partnerships team. "Nielsen was delighted to be selected to test TikTok's Alpha API MMM data feed workstream to continue to automate the data collection process and ensure an accurate and on-time data delivery for our mutual clients. We look forward to partnering with clients to leverage this process for future MMM engagements."
By prioritizing API integration, advertisers and measurement partners can streamline their workflows and focus on extracting meaningful insights from TikTok’s robust data offerings.
How to get started with media mix modeling
For brands and agencies
If you're already using MMM, we recommend incorporating both paid and earned data into your models through our new API. But if you're new to MMM or unsure about using media mix models, here are some simple steps to help you get started.
Understand the limitations of last-click attribution for your TikTok ad strategy using Attribution Analytics, available in TikTok Ads Manager.
If you're primarily reliant on TikTok, TikTok Shop, and one other channel for marketing, use the ‘Assisted conversions’ feature to see how TikTok contributes to conversions that might otherwise be attributed to earned or direct traffic.
If you have a broader media mix, analyze how TikTok impressions and clicks influence conversions through a media mix model, helping you build a more holistic measurement approach.
Leverage the TikTok API to simplify your workflows and ensure accurate, timely data integration for your clients. Here is how you can get started.
Evaluate your current data strategy across all channels and streamline data collection by using APIs where possible.
For measurement partners
We invite MMM vendors and measurement teams to explore our API integration. This will streamline your workflows and ensure you get accurate, timely data for your clients.
Building the future of holistic measurement together
As the volume and frequency in which brands and agencies incorporate TikTok into their media mix models increases, these new API updates will help to seamlessly integrate even more data, unlocking powerful insights to further refine their mix learnings.
Over the last few years, we've built up an effectiveness portfolio for marketers to help prove and improve how they can build their business outcomes on TikTok," said Jorge Ruiz, Global Head of Marketing Science at TikTok. "In this journey, media mix models have grown in importance as the learnings are evolving beyond 'Does TikTok work?' into 'How can TikTok work the best in my media mix?' By fostering a strong ecosystem of partnerships across specialists, brands, and agencies, we hope to build on these effectiveness learnings."
Are you interested in becoming a TikTok badged measurement partner? Reach out to your partner manager today and discover how we can work together to drive measurement innovation and campaign success.
The future of marketing effectiveness is here – let's build it together.
Source:
Nielsen MMM Study commissioned by TikTok, US only (study of 7 Retail advertisers covering February 2021 - January 2023)