Most effective planning, research and evaluation in the public and not-for-profit sectors

Summary
The “Wild Algorithm Reset” campaign, executed for Ampara, Brazil’s leading animal protection organization, addressed the urgent issue of wild animal trafficking. By leveraging the power of social media insights and SEO data, we identified and disrupted demand-driving content on Instagram and TikTok. This emphasis on social media educated millions on resetting their social algorithms, leading to a significant reduction in engagement with trafficking-related content. The initiative not only raised awareness but also resulted in a notable drop in search volumes for trafficked animals and sparked law enforcement actions.

Objective/Brief
Wild animal trafficking in Brazil is a growing crisis, necessitating innovative solutions for awareness and reduction. Ampara, a prominent OSCIP (Civil Society Organization of Public Interest) recognized by the Brazilian Ministry of Justice, sought to combat this issue by raising public awareness and reducing demand for trafficked animals. Our primary objective was to create a data-driven campaign that could track and influence public engagement with trafficking-related content on social media.

We began by immersing ourselves in social media environments where trafficked animal content was prevalent. Through extensive research on Instagram and TikTok, we identified key hashtags and engagement patterns. This insight informed our social listening strategy, allowing us to track content and engagement trends over two years. Additionally, we analyzed Google search trends to gauge the demand for trafficked animals.

Our measurement approach aimed to provide actionable insights by correlating social media engagement with search behaviors. By understanding the drivers of demand, we sought to educate the public on disrupting harmful algorithms and promote awareness. This comprehensive strategy highlighted the importance of measurement in addressing the complex challenge of wild animal trafficking and demonstrated the critical role of data in shaping effective communication campaigns.

Strategy
Our strategy revolved around a robust measurement and reporting approach to understand social media and search behaviors related to wild animal trafficking. We adopted an integrated methodology, leveraging social listening and SEO tools to track and analyze data from multiple touchpoints. Instagram and TikTok were identified as key channels, with specific keywords and hashtags guiding social listening efforts, allowing us to monitor engagement with content featuring trafficked species.

We leveraged SEO tools like Ahrefs, SEMRush, and Google Keyword Planner to assess the demand for wild animals through search trends, focusing on high-intent keywords for relevant data. We developed a time-series regression model to investigate whether engagements with social media content featuring rare animals could predict future search volumes. This analysis aimed to quantify social media’s role in driving interest in rare animal purchases.

Our model employed sophisticated power-additive time series techniques, analyzing data for factors such as the delay between initial media exposure and subsequent search actions, how media impact persists and fades over time in the public mind and adjustments for the impact of media saturation.

This approach helped us quantify the influence of each media channel on rare animal purchases, including monkeys, parrots, and snakes. We assessed causality using Granger causality tests and measured the campaign’s effectiveness by tracking changes in social media engagement and search volumes before and after the campaign launch. Our reporting included real-time dashboards and periodic reports, integrating social media and search data to evaluate the campaign’s impact and the interaction between different channels.

Execution/Implementation
The execution of the “Wild Algorithm Reset” campaign involved innovative measurement approaches tailored to address the complexity of wild animal trafficking content on social media. Our implementation began with a deep dive into social media platforms, where we tracked and analyzed content featuring trafficked animals.

We used advanced social listening tools to monitor engagement with specific keywords and hashtags identified during our preliminary research. This allowed us to track over 11,000 accounts and their interactions with content featuring monkeys parrots, and snakes. In parallel, we conducted extensive SEO research to understand the demand for trafficked animals through Google search trends.

We aggregated daily search volumes and employed power-additive time series regression models to analyze the relationship between social media engagement and search behaviors. Through this extensive measurement research, we learned that Instagram and TikTok directly generated 37% of searches for monkey purchases and 18% of searches for snake purchases.

Our insights were brought to life with the launch of the campaign at a public exhibition in São Paulo. This exhibition, featuring real cages used by traffickers and mobile phones displaying social media posts of trafficked animals, served as a powerful visual representation of the issue and generated sharable content for social media.

On National Animals Day, we collaborated with prominent Brazilian influencers to promote the “Wild Algorithm Reset” across various social media platforms. With a combined following of 106 million, these influencers guided their audiences through a simple process to reset their social media algorithms, thereby reducing demand for trafficked animal content. This multi-channel approach combined on-the-ground activations with digital engagement to ensure widespread reach and impactful results.

Effectiveness of Assignment
The “Wild Algorithm Reset” campaign delivered significant and measurable outcomes, effectively addressing the objectives set by Ampara. Our comprehensive measurement strategy provided actionable insights that informed both the campaign’s execution and its ongoing evaluation.

Our robust data modeling approach has demonstrated a clear and causal relationship between social media engagement and search behaviors related to wild animal trafficking. The power-additive time series regression models, with a mean absolute percentage error (MAPE) of 3% to 6%, allowed us to predict changes in weekly search volumes with 94-97% accuracy. This high level of precision underscored the reliability of our research findings and provided a solid foundation for our recommendations.

The campaign’s impact was evident in both online and offline metrics. Social media engagement with videos featuring wild animals on Instagram declined by 12%, while global search volumes for trafficked animals decreased significantly: 15% for monkeys, 6% for parrots, and 5% for snakes. These reductions in demand were directly attributable to the campaign’s success in educating the public and disrupting harmful social media algorithms.

Furthermore, the public exhibition in São Paulo and the involvement of high-profile influencers generated substantial media coverage and public discourse around the issue of wild animal trafficking. The initiative successfully re-educated the algorithms of 12.1 million individuals and garnered a total of 111 million impressions. This heightened awareness prompted a series of law enforcement actions, demonstrating the campaign’s effectiveness in driving tangible social change.

The insights gained from this campaign not only informed Ampara’s immediate strategies but also provided valuable learnings for future communications planning. The ability to quantify the impact of social media on consumer behavior related to rare animal sales offered a new dimension to Ampara’s advocacy efforts.

By leveraging data-driven insights and innovative execution strategies, we achieved significant reductions in demand for trafficked animals and raised public awareness about the issue. The campaign’s success demonstrated the power of integrated measurement approaches in driving impactful and lasting social change.