Kochava study shows TikTok impact 35% higher with marketing mix modeling

Measurement technology company Kochava announced on September 23, 2025, research findings that demonstrate a substantial gap between last-touch attribution and marketing mix modeling when measuring TikTok advertising impact. The study, which analyzed major Android and iOS applications across North America during the first quarter of 2025, found that marketing mix modeling revealed TikTok campaigns generated an average of 35% higher incremental impact compared to last-touch attribution reporting.

The research arrives during heightened industry focus on measurement accuracy as mobile advertising becomes increasingly complex. Gary Danks, General Manager of AIM by Kochava, emphasized the significance of this attribution gap in the company's announcement. "MMM uses data science to measure what's really driving conversions across the whole marketing mix," Danks explained.

The findings highlight persistent challenges in mobile advertising measurement, where consumer journeys frequently span multiple platforms within minutes. According to the research, TikTok advertisements often serve as launch points for customer exploration across other channels, rather than direct conversion paths. This behavior pattern creates measurement complexities that traditional last-touch attribution fails to capture adequately.

Technical measurement differences emerge

Last-touch attribution assigns conversion credit to the final touchpoint before a user action, while marketing mix modeling employs statistical analysis to evaluate all marketing activities' contribution to business outcomes. The Kochava study demonstrates how these methodological differences produce significantly different results when measuring TikTok's advertising effectiveness.

TikTok's unique video platform characteristics contribute to these measurement challenges. User engagement patterns on TikTok differ substantially from other digital advertising platforms, with distinctive content viewing experiences that don't follow straightforward click-and-convert paths. The research indicates that TikTok advertisements frequently initiate broader customer exploration journeys that traditional attribution models struggle to track comprehensively.

Marketing mix modeling addresses these limitations by incorporating market conditions and historical performance data while accommodating seasonal variations. The methodology quantifies how campaigns, both paid and earned, contribute across the entire conversion funnel to installations, engagement metrics, and revenue generation.

Privacy concerns drive measurement evolution

The resurgence of marketing mix modeling reflects growing data privacy concerns affecting traditional attribution methods. Mobile advertising measurement faces increasing constraints as operating systems implement stricter privacy protections and regulatory frameworks evolve globally.

Kochava's research timing coincides with industry-wide adoption of privacy-first measurement solutions. Major technology companies have introduced open-source marketing mix modeling tools to address these challenges. Google launched Meridian, an open-source marketing mix modeling platform, in March 2024 to help marketers navigate fragmented media consumption and privacy regulations.

The measurement landscape has experienced significant developments throughout 2025. Prescient AI announced in Julywhat the company describes as the first marketing mix model built entirely from scratch since the 1960s. Traditional measurement approaches face pressure from privacy changes and increasingly complex consumer journeys across multiple touchpoints.

Marketing professionals have recognized the limitations of relying solely on last-touch attribution. Industry analysis from March 2025 emphasized that combining multiple measurement approaches delivers more accurate advertising performance pictures. The Institute of Practitioners in Advertising released comprehensive guidance recommending systematic approaches that integrate marketing mix modeling, experimentation, and attribution methodologies.

TikTok partnership expands measurement capabilities

Kochava serves as a badged partner in TikTok's marketing mix modeling focus area, providing specialized measurement expertise for the video platform. This partnership reflects TikTok's commitment to addressing measurement challenges that affect advertiser decision-making on the platform.

The collaboration enables more sophisticated measurement techniques to optimize advertising spending and reveal performance drivers for brands advertising on TikTok. Marketing mix modeling provides holistic measurement capabilities that consider the interconnected nature of modern media ecosystems, where individual channels influence each other's performance.

TikTok has invested in measurement improvements across multiple initiatives. The platform introduced Brand Lift Studies in July 2021, integrating with Kantar as a third-party verification partner to help advertisers understand campaign impact. These measurement tools enable experimentation processes and data-driven resource allocation toward impactful campaigns.

Industry measurement consolidation accelerates

The marketing measurement sector has experienced significant consolidation activity throughout 2024 and 2025. Circana announced acquisitions of NCSolutions and Nielsen's Marketing Mix Modeling business in August 2024, expanding media measurement capabilities and unified measurement solutions.

These consolidation efforts reflect increasing demand for sophisticated measurement and optimization tools as consumer behavior complexity grows alongside digital platform proliferation. The integration of multiple measurement approaches under unified platforms provides advertisers with more comprehensive solutions for campaign planning, execution, and performance analysis.

Technology developments continue reshaping measurement capabilities. Adverity launched an AI-powered intelligence layer in September 2025, combining conversational artificial intelligence with collaborative analytics to address resource constraints in modern marketing teams.

Mobile advertising complexity increases

Mobile advertising measurement faces unique challenges as advertising spans new platforms and consumer journeys become increasingly fragmented. Each operating system, application, and platform presents distinct measurement requirements that must balance user privacy protection with accurate performance tracking.

The research indicates that advertising across entire mobile ecosystems requires multiple data points, specialized skills, and strategic planning. Different brands achieve success in varying areas, making comprehensive performance measurement across multiple channels essential for optimized advertising spending.

TikTok's distinctive user engagement patterns create specific measurement requirements. The platform's video-first approach generates user interactions that differ from traditional digital advertising channels. These engagement differences necessitate measurement approaches that capture the full impact of TikTok advertising on broader marketing objectives.

Marketing mix modeling provides capabilities to track these complex interactions by analyzing historical data patterns and identifying relationships between marketing activities and business outcomes. The methodology considers external factors such as market conditions and seasonal variations that influence advertising performance beyond direct attribution touchpoints.

Budget allocation optimization benefits

The 35% measurement difference identified in Kochava's research carries significant implications for advertising budget allocation decisions. Underestimating TikTok's incremental impact by such margins could result in suboptimal spending distribution across marketing channels.

Marketing mix modeling enables strategic roadmap development for efficiency improvements over extended periods, transforming reactive marketing strategies into proactive approaches. The methodology supports scenario planning and budget optimization, providing marketers with data-driven insights for cross-channel media allocation decisions.

Accurate measurement becomes increasingly critical as marketing budgets face greater scrutiny and performance expectations. The research demonstrates how measurement methodology selection directly impacts perceived channel effectiveness and subsequent investment decisions.

Companies utilizing marketing mix modeling can quantify the relationship between TikTok campaigns and other marketing channels, revealing interconnected performance effects that traditional attribution methods miss. This comprehensive understanding supports more informed budget allocation decisions based on actual incremental impact rather than last-touch credit assignment.

Implementation considerations for marketers

The transition from last-touch attribution to marketing mix modeling requires careful consideration of organizational capabilities and data infrastructure. Marketing mix modeling demands sophisticated analytical resources and comprehensive data collection practices across all marketing channels.

Implementation success depends on establishing proper data collection frameworks and maintaining consistent measurement practices over time. The methodology requires historical performance data spanning sufficient periods to identify meaningful patterns and relationships between marketing activities and business outcomes.

Organizations must consider their specific measurement needs when evaluating different approaches. Industry guidance suggests that companies with monthly marketing expenditures exceeding $100,000 should explore implementing multi-touch attribution modeling and marketing mix modeling capabilities.

The research underscores the importance of selecting measurement approaches that align with business objectives and platform characteristics. TikTok's unique engagement patterns require measurement solutions capable of capturing complex customer journey interactions across multiple touchpoints and timeframes.

Marketing professionals must balance measurement sophistication with practical implementation requirements, ensuring that chosen methodologies provide actionable insights that improve advertising performance and budget allocation decisions.

Timeline

• July 2021: TikTok introduces Brand Lift Studies with Kantar as third-party verification partner
• May 2022: TikTok earns TAG certification against ad fraud and for brand safety
• March 2024: Google unveils Meridian, open-source Marketing Mix Model to address privacy concerns
• May 2024: TikTok launches Media Buying Certification program for digital marketing professionals
• June 2024: Marketing Mix Modeling sees resurgence as privacy-focused measurement tool
• August 2024: Circana expands measurement capabilities with NCSolutions and Nielsen MMM acquisitions
• March 2025: IPA releases comprehensive measurement guidance combining MMM, experiments, and attribution
• July 2025: Prescient AI unveils new marketing mix model built from scratch since 1960s
• September 2025: Adverity debuts AI-powered intelligence layer for marketing analytics
• September 23, 2025: Kochava announces research showing TikTok impact 35% higher with marketing mix modeling

Summary

Who: Kochava, a measurement technology company, conducted research in partnership with TikTok as a badged partner in the platform's marketing mix modeling focus area. Gary Danks, General Manager of AIM by Kochava, presented the findings.

What: Research revealing that marketing mix modeling shows TikTok campaigns generate an average of 35% higher incremental impact compared to last-touch attribution reporting. The study analyzed major Android and iOS applications across North America.

When: The research was announced on September 23, 2025, analyzing data from the first quarter of 2025 across North American mobile applications.

Where: The study focused on major Android and iOS applications in North America, with findings applicable to mobile advertising measurement globally.

Why: The research addresses persistent measurement challenges in mobile advertising as consumer journeys become increasingly complex and span multiple platforms. Privacy concerns and fragmented media consumption have made traditional attribution methods less effective, driving demand for sophisticated measurement approaches like marketing mix modeling that can capture true advertising incrementality.