**OBJECTIVE** This study evaluates whether implementing the **Disclosure Integrity Protocol (DIP)** (https://www.swayid.com/disclosure-integrity-protocol) — a statutory-grade behavioral compliance system — can restore consumer trust and legal defensibility in influencer advertising by replacing ad hoc disclosure practices with standardized, verifiable FTC-compliant workflows. The intervention — the SwayID Smart Disclosure System (https://www.swayid.com/smart-disclosure-system) — operationalizes DIP by equipping brands and creators with shared infrastructure for generating, publishing, and logging disclosures. Using a stepped-wedge field design, the study measures changes in disclosure consistency, auditability, and operational burden before and after system implementation. **BACKGROUND** Influencer marketing in the AI era is under siege from public skepticism and legal scrutiny. Synthetic endorsements, undisclosed sponsorships, and increasingly AI-generated content have eroded consumer trust — while a new wave of regulation and litigation has made failure to disclose a legal liability as well. The ****Disclosure Integrity Protocol (DIP)** offers a unified standard to mitigate these risks, modeled after regulatory frameworks like SOC 2 and GDPR. On August 8, 2024, the Federal Trade Commission announced its finalized rule banning fake reviews and deceptive endorsements, codifying a USD $43,792 per-post fine (https://www.ftc.gov/news-events/news/press-releases/2024/08/ftc-announces-final-rule-banning-fake-reviews-testimonials). By July 2025, class action lawsuits tied to influencer campaigns ballooned past USD 400 million in aggregate exposure, including an estimated USD 450 million in recent filings (https://www.dglaw.com/the-rise-of-class-actions-in-influencer-marketing-what-brands-need-to-know-to-protect-themselves/). DIP aims to provide brands, creators, and regulators with the legal infrastructure necessary to prevent, detect, and defend against these risks. **SYSTEM COMPONENTS** The behavioral compliance system tested in this study implements the Disclosure Integrity Protocol (DIP) through the SwayID Smart Disclosure System. Core components include: - **Disclosure Generation Interface:** A standardized, creator facing interface for producing FTC compliant disclosures tied to verified brand relationships. This replaces informal methods such as manual caption drafting or platform native tagging. - **Dynamic Disclosure Registry:** A public facing compliance layer embedded on creator and brand surfaces (for example, social media bios, websites). Each creator receives a personalized disclosure link that auto updates with every disclosure generated through the system. Each brand receives a corresponding dynamic link that auto populates as connected creators generate disclosures. These links function as continuously updated, public records of disclosure status. - **Court Grade Audit Log:** A shared, immutable record of disclosure actions, time stamped in ISO 8601 format and accessible to both brand and creator. Designed to meet evidentiary standards in regulatory investigations, internal compliance reviews, and civil litigation. **STUDY DESIGN** - **Design type:** Stepped wedge field trial - **Participants:** 5 to 7 mid market US beauty brands - **Volume requirement:** Each brand works with 10 or more creators per month, each publishing at least one paid TikTok video that requires FTC disclosure - **Duration:** 6 to 8 weeks - **Design:** Each brand acts as its own control. Outcomes are measured pre and post implementation. **HYPOTHESES** **Primary (H1):** Implementation of the behavioral compliance system will increase the percentage of TikTok videos containing standardized, verifiable FTC compliant disclosures at the time of publication. **Secondary** - H2: Labor hours required to reach compliance will decrease - H3: Legal costs will decrease - H4: Stakeholders will report higher confidence in legal defensibility and compliance reliability **OUTCOME METRICS** **Primary outcome:** FTC compliant disclosure rate at time of publication, scored using a pre-registered audit rubric **Secondary outcomes:** - Labor hours per compliant post - Compliance cost per campaign - Time from draft to compliance - Creator edit cycles - Stakeholder confidence in legal defensibility - Audit trail completeness per post **ANALYSIS PLAN** **Primary analysis:** - We will estimate the change in FTC-compliant disclosure rate before and after implementation using a mixed effects logistic regression with brand-level random intercepts. Effect sizes will be reported with 95% confidence intervals. **Secondary outcomes:** - Time, cost, and coordination metrics will be summarized descriptively and compared pre/post using paired t-tests or nonparametric equivalents. Results will be interpreted as exploratory. **Missing data:** - Posts without complete audit trail linkage (registry + log) will be treated as non-compliant in sensitivity analyses. **PARTICIPANT CRITERIA** - US based DTC beauty or wellness brands - Annual revenue between 10 million and 250 million dollars - Work with at least 10 creators per month posting at least one paid TikTok video that requires FTC disclosure - Willing to participate for 6 to 8 weeks and share anonymized operational data **DATA COLLECTION** - Pre and post FTC compliance audits (rubric hosted in OSF “Audit Rubric” component) - Internal time and cost logs - SwayID platform generated compliance logs - Creator coordination records (edits, resubmissions) - Structured interviews with marketing and legal stakeholders **DATA HANDLING, PRIVACY, AND SECURITY** Personal data from creators and brand users may be captured in platform logs. All raw data will be stored securely and anonymized before analysis. No personally identifiable information will be published or shared outside the research team. Post level data will be de identified prior to reporting. Brand names will remain confidential unless written permission is granted. Audit trail data will be time stamped and stored in secure infrastructure. Public outputs will contain only aggregate statistics. A de identified analysis dataset and all code used for statistical analysis will be deposited in the OSF “Analysis & Results” component upon study completion, subject to participant consent and contractual constraints. **RISK, ETHICS, AND CONFLICTS** - This is a field study of operational compliance processes. No intervention targets consumers directly. - This study was led by Kaeya Majmundar (https://www.linkedin.com/in/kaeya), Founder and CEO of SwayID, the company that developed the Smart Disclosure System evaluated in this protocol. - The study team is affiliated with SwayID (https://www.swayid.com). This conflict is disclosed here and will be disclosed in any publications. - No IRB approval is required for the operational metrics collected. - No compensation is provided to creators or consumers as part of this study. - For more information or to access the system evaluated in this study, visit the [SwayID Research Center for Evidence-Based Advertising Compliance in the AI Era](https://www.swayid.com/research). **PROJECT COMPONENTS (OSF)** 1. Registration (this document) 2. Recruitment and Consent 3. Audit Rubric and Codebook 4. Data Collection Instruments and Schemas 5. Analysis Plan and Results 6. Publication and Dissemination Materials **TIMELINE** - Project created: July 26, 2025 - Participant recruitment: August 2025 - Fieldwork: September 2025 - Final analysis and reporting: October 2025 **Note:** The Disclosure Integrity Protocol (DIP) was developed by SwayID and is offered as an open standard for compliance in user-generated advertising.