How to Effectively Iterate with Content Creators for UA

Role of Content Creators

‍In the competitive landscape of user acquisition (UA), partnering with content creators has become a go-to strategy for mobile app marketers. However, the traditional approach of working with influencers can be expensive and limit scalability. In this article, we share our proven method for collaborating with content creators to drive UA success while maximizing efficiency and minimizing costs.

Over the course of two years, we produced over 100,000 videos across 22 of our own apps and 50+ of our customers' apps by working with hundreds of diverse actors. Our unique approach allowed us to create 100 ads in just one hour, spread across three different apps, with only six actors. The key to our success? Extensive A/B testing and a focus on optimization.

Through rigorous testing, we identified top-performing actors and tailored our campaigns to specific audiences, particularly in the gaming industry. By continuously refining our methods and leveraging data-driven insights, we developed a robust pipeline of content creators that consistently delivered results.

Creative Iterations in 4 Easy Steps

In this article, you'll discover how to:

1. Establish clear objectives and optimize resources for maximum ROI
2. Leverage data and analytics to identify top-performing content creators and strategies
3. Iterate based on findings and insights to stay ahead of the competition
4. Incorporate audience and stakeholder feedback to refine your UA approach

By implementing these strategies and working with a diverse pool of content creators, you can significantly reduce costs, increase ad volume, and drive long-term UA success. Let's dive in.

Establishing Clear Objectives and Expectations

‍To effectively A/B test a large volume of ads featuring a diverse array of actors while also controlling production costs, we implemented a strategic, three-pronged approach. This method not only maintained the rigor of compliance with TikTok policies and production quality but also optimized expenses. Here's how we achieved more with less:

Optimizing Studio Resources for Premier Ad Quality: 

By forging a partnership with a film studio, we gained access to their underutilized space and top-tier equipment—ranging from advanced cameras and dynamic lighting to versatile green screens and high-quality microphones. This strategic move drastically reduced our operational costs while ensuring our ads consistently met high production standards. The meticulous control over production elements like resolution and aspect ratio was critical, transforming what was typically considered a luxury into a fundamental requirement for creating impactful ads.

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Efficient Filming Processes to Slash Editing Costs: 

We refined our filming process to heighten efficiency dramatically. During sessions, actors would record various segments of the ad—hooks, core messages, and calls to action—separately. This methodical separation allowed our editing team to swiftly compile these elements into numerous distinct ads. By restructuring our production workflow, we managed to cut down the standard editing time for a single ad from 30-45 minutes to approximately 10 minutes, thereby halving our editing expenses and accelerating our output rate.

Leveraging Flexible Backgrounds to Expand Ad Diversity: 

We strategically chose to film actors against a trio of backgrounds: green-screen, podcast-style, and traditional couch setups. This approach did more than just test the influence of different backgrounds on ad performance; it unlocked endless creative possibilities for future campaigns. The use of green screens was particularly advantageous, enabling our editors to seamlessly integrate a variety of engaging scenarios or trending TikTok visuals behind the actors, significantly boosting the ads' appeal and relevance.

Leveraging Data and Analytics

To align our content production with the dynamic demands of our clients, we developed a targeted approach for selecting and deploying actors. This strategy relied on identifying the specific attributes and trends that consistently yield high engagement on platforms like TikTok. By closely analyzing the performance across various demographics and tailoring our selections accordingly, we crafted a refined method to ensure each campaign's success. Here are the key performance indicators that guided our decisions:

Demographic Insights:

• Younger women generally outperformed men in gaming apps.
• Male actors were more successful in niche areas such as fintech and meditation apps.
• We typically maintained a 4:1 female-to-male ratio, aligning with performance trends.

The Halo Effect:

• TikTok’s algorithm showed a preference for conventionally attractive, Eurocentric female features, demonstrating the psychological 'halo effect'.

Appearance Guidelines:

• Actors were advised to wear solid, neutral-colored clothing to ensure a cleaner video appearance, which proved more effective than eye-catching attire.

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The true effectiveness of creators could only be determined through rigorous testing:

After moving past TikTok’s initial learning phase and understanding the core concepts and scripts that resonated with our audience, we focused on narrowing down variables to identify the best creators. For each client, we tested 6-10 actors to find the best performer. Here’s an example workflow from one of our apps where we tested various actors and styles to determine the best combination:

• Actors Tested:
  • Ilene: Female, young 20s, white, petite, black hair.
  • Cindy: Female, mid-20s, white, petite, black hair.
  • Claire: Female, young 20s, white, petite, blonde hair.
  • Nikki: Female, late 20s, Indian, broad, black hair.
  • Shelly: Female, mid-20s, white, petite, blonde hair.
  • Ralph: Male, late 20s, Latin, broad, black hair.

• Script
  • Each video included one hook, one base, and one call to action (CTA).
• Styles:
  • Typical green screen: Actor stands in front of a green screen.
  • Podcast style: Actor sits at a desk and acts like a podcast host.

This methodical testing approach led to the production of 12 diverse videos, allowing us to maintain a constant in other variables while focusing on actor performance and style efficacy. Despite our efforts to ensure diversity, we noted a preference in TikTok's audience for certain demographics, which informed future strategic adjustments. Through continuous data analysis and feedback integration, we have optimized our content creation process to consistently exceed client expectations with engaging, high-quality videos.

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Learn More: How we test 3k+ videos weekly without blowing up our UA budget

Iterate based on your findings and insights

In our quest to optimize content performance, we adopted a data-driven approach, iterating based on our findings and insights. A critical aspect of this process involved conducting scenario tests to identify the most effective actors and styles.

Test Set-Up:

We designed a test scenario with six actors (listed above)—five female and one male—across two distinct styles.

We created two ad-groups:
1. One ad-group included six creatives utilizing the green screen style.

2. Another ad-group featured six creatives in the podcast style.

For apps with the highest conversion rates and lowest CPIs, we could test with as little as a few hundred dollars daily for an ad group. This is where we expect you to jump in and say that this is not enough to reach statistically significant results. Most of the time, you'd be right, we'll post another blog post detailing this.

Analyzing Results:

Upon completion of the ad-groups, we analyzed key metrics such as Click-Through Rate (CTR) and Cost Per Install (CPI) to identify the top performers. For instance, the results might reveal different winners from each group, such as Cindy excelling in the podcast style from ad-group 1, and Ralph standing out in the green screen style from ad-group 2.

Based on these results, we had two strategic options:

1. Focused Testing: Continue testing all ads with only Cindy and Ralph in their respective styles. This approach capitalizes on the proven success of these specific combinations.
2. Expanded Testing: Re-run the tests with Cindy and Ralph while introducing new actors and styles. This broader approach aims to identify additional top-performing combinations, ultimately surfacing five winners that could be applied across all creatives.

By iterating on our insights, we continuously refined and optimized our content strategy. Leveraging data and analytics at every stage ensured high-quality content and effective user acquisition, consistently meeting client expectations. This meticulous, dynamic approach allows us to stay competitive in the market.

Get feedback from your audience and stakeholders

Case Study: WeWard

WeWard, a highly acclaimed rewards app with a rapidly growing TikTok presence, has been collaborating with our team for the past eight months to create engaging content that resonates with their user base. Through rigorous A/B testing, we have consistently identified winning creative elements, including compelling storylines, attention-grabbing hooks, relatable actors, captivating footage, and immersive music.

Over the last three months, we have successfully delivered winning creatives each month, which WeWard has scaled for 3-5 months each, resulting in significant success for both parties. As our partnership progresses, WeWard has challenged us to explore edgier tactics beyond the proven "happy" and "vanilla" videos that have been the foundation of our success.

This new direction required us to push the boundaries of our testing and get more creative. We had already spent months perfecting our strategy and identifying the top three actors that resonated with WeWard's audience. Now, we needed to experiment with the emotional delivery of the script to uncover fresh ways to engage their users.

We reached out to our top three creators and asked them to re-enact the winning script from the previous month in four different tones:

1. Happy (control emotion to beat)
2. Sassy (adding a touch of sarcasm to certain lines)
3. Super Hype (over-exaggerating emotions for heightened impact)
4. Alluring/Mysterious (incorporating an element of surprise to intrigue the audience)
   
   

In this test, we maintained all other variables (script, actor, footage, music) and only changed the creators' execution. This approach allowed us to preserve the insights from eight months of testing while conducting a true A/B test to answer the client's question. Although the "happy" emotion still performed the best, the "sassy" creative came in a close second, prompting us to incorporate this delivery in future testing batches.

In addition to exploring various emotional deliveries, we considered other avenues to introduce an edgy element to the videos, such as changing the actors' clothing, incorporating potentially comedic animations, or adding an edgy thumbnail at the beginning of the video. These variables aligned with WeWard's openness to testing new approaches. However, after careful consideration, we mutually agreed that the "emotion" variable held the most potential to resonate with WeWard's audience at this stage in our collaboration.

By continually pushing the boundaries of our creative strategies and maintaining a data-driven approach, we aim to strike a balance between the proven elements that have driven our success and the discovery of innovative ways to captivate WeWard's ever-growing user base. This ongoing collaboration demonstrates WeWard's commitment to delivering engaging content and ensuring user satisfaction, while highlighting the power of data-driven creative strategies in maximizing an app's potential and captivating its growing audience.

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Conclusion

‍Our collaboration with content creators has fundamentally shifted how we produce ads for our clients, enabling continuous and consistent testing of new variables to adapt to TikTok's ever-evolving algorithm. We've successfully learned to maximize outputs while minimizing resources—reducing time, cutting editing costs, and streamlining personnel—thereby enhancing ad volume, diversity, and the sophistication of our A/B testing methods. This is precisely why we created Poolday.ai: to allow our clients to leverage this smart approach without the hassle of working with real actors. Our approach ensures that each campaign is both budget-conscious and highly impactful, crucial for maintaining relevance on dynamic platforms like TikTok. With Poolday.ai, we've distilled the essence of what makes content creators so effective in driving UA, and we've made it accessible to our clients in a streamlined, cost-effective platform that gives them the power to autonomously create winning ad campaigns.

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FAQ

What is the iterative process for content marketing strategy?

• The iterative process for content marketing strategy involves four key steps: establishing clear objectives, leveraging data and analytics, iterating based on findings, and incorporating feedback. This approach ensures that resources are optimized for maximum ROI, top-performing content and strategies are identified, and the strategy stays ahead of the competition. By continually refining the approach based on audience and stakeholder input, the content marketing strategy remains effective and relevant. Refer to the "Creative Iterations in 4 Easy Steps" section for more detail.

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How do you approach content creation?

• The approach to content creation is driven by data, stakeholder input, and a focus on proven strategies. By leveraging data and analytics, the most effective content creators, styles, and campaign elements are identified. This involves conducting rigorous A/B testing with a diverse pool of actors and analyzing key metrics to determine top performers. Stakeholder feedback is actively sought and incorporated into the creative process, ensuring that the content aligns with the target audience's preferences and the client's goals. Once winning combinations of actors, styles, and creative elements are identified, the approach is to double down on these proven strategies while continually testing new variables to stay ahead of the curve. Refer to the "Leveraging Data and Analytics" and "Get feedback from your audience and stakeholders" sections for more detail on this data-driven, iterative approach to content creation.

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How do you handle content creation?

• Content creation is handled through a data-driven approach that involves working with diverse content creators, conducting A/B testing, and tailoring campaigns to specific audiences. By analyzing demographic insights and performance trends, top-performing creators and styles are identified(i.e., different types of “variables”), and campaigns are optimized accordingly. Continuous data analysis and feedback integration ensure that the content creation process remains effective and aligned with audience preferences. The "Leveraging Data and Analytics" and "Iterate based on your findings and insights" sections offer more details on this process.
  
  

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*In this article, the terms "content creators," "influencers," and "actors" are used interchangeably.

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