YOUNG PEOPLE ARE NOT ONE GROUP: WHAT HAPPENS WHEN CONTENT FEELS MADE FOR THEM

Written by the Shujaaz Inc team in collaboration with iMedia Associates

Last year, Shujaaz Inc and iMedia Associates set out to answer a deceptively simple but game-changing question with a digital media experiment: 

Would we see faster/bigger/better outcomes if we used tailored digital content (versus generic messages) in our campaign aimed at supporting new knowledge, attitudes, beliefs and SRH behaviours among different groups of young people in Kenya? 

This question sits at the heart of our Free To Choose (F2C) learning program in partnership with the Gates Foundation’s Family Planning team. 

After six months of experimentation across Shujaaz’s social media channels, we designed a digital quasi-experimental study (using an RCT framework) via the Virtual Lab platform. In this study, almost three thousand young people – carefully recruited and labeled by segment – experienced one of the following: 

1. No intervention (Control Arm)  
2. Exposure to Shujaaz generic SRH content (Non-F2C Arm) 
3. Exposure to Shujaaz hyper-tailored, segment-specific F2C content (F2C Arm)

Then we tracked what changed. 

What We Learned (and why it matters)

Lesson 1: Tailored content works, but the type of impact varies significantly. 

Overall, both intervention arms (Tailored F2C and Generic Non-F2C) demonstrated more consistent positive shifts in SRH knowledge and behaviours compared to the Control group. 

However, the type of shift was closely correlated with the type of content. 

While people exposed to generic SRH content showed surprisingly positive results at building foundational skills like “joint decision-making with the partner”, people consuming tailored F2C content showed very positive results in shifting deep-rooted norms and specific SRH behaviors. 

Here are examples of how this played out amongst our different segments: 

• Barasa Wa Town (Young Independent Male): This segment showed the only significant increase in consistent male condom use after viewing tailored content. However, this behavioural win came with a tension: the group also showed a rise in restrictive gender norms, such as distrusting partners who use contraception without consultation. 
• Nice Girl Nana (Adolescent Girl not in a relationship): This segment showed exciting signs of successful normalisation of contraception use, leading to a massive increase in the belief that unmarried girls in her community use it. But this awareness triggered a backlash: a significant increase in the fear that women who use contraception are “promiscuous,” highlighting the struggle to reconcile personal safety with her “good girl” identity. 
• Nina Baddie (Young Single Mother): The consumption of tailored content helped the young mother shift her focus from financial survival mode to financial health/stability. By feeling increased access to resources, she showed a renewed interest in building a steady relationship with her co-parent (a.k.a. the baby daddy) rather than seeking a “sponsor”. In addition, Nina Baddie was able to reduce her dependence on emergency methods (e.g ePill) while simultaneously reporting an increase in the use of long-acting methods of contraception.
• Nina Siri ‘secret’ (Young Woman dating privately): For this segment, the tailored approach appeared to unlock a specific behavioural win: she was one of the two segments (together with Nina Baddie) to show an increase in the use of long-acting contraceptive methods, moving beyond reactive choices. Moreover, the exposure to tailored content appeared to stimulate Nina Siri’s conversations about protection with her sexual partner, albeit not with a medical professional or a digital counselor.

Tailoring works, but every group interprets SRH messages through their own pre-existing worldviews, social pressures, fears and aspirations. The same message can land as empowerment for one segment, and as a threat or contradiction for another.

Lesson 2: Some norms shift fast. Others barely move. 

Our sentiment analysis revealed that conversational attitudes can shift quickly. For example, the Barasa Amerix segment moved rapidly from viewing contraception with “moral suspicion” to discussing it as a practical “cost-benefit” issue within just months. But deep-rooted norms and behaviours? Those lag behind and take time and persistence. We learned that sentiment is a precursor to behaviour change, not a proxy for it. 

• The “Sentiment-Behaviour Gap”: While online talk became more progressive, deeply ingrained power dynamics (like male authority in relationships) were slower to change.
• Message Misinterpretation: A critical risk we identified is that audiences may twist progressive messages to align with old views. For instance, Barasa Wa Town interpreted relationship advice as confirmation of male authority, rather than partnership.
   

Lesson 3: The segments behave differently and require different media strategies.

For the first time, we could trace which specific storylines and framings worked best for each segment to unlock “relief” from their specific pressures. 

• Barasa Amerix needed relief from the pressure to conform. Once relieved of the burden to “play the role” of a traditional husband, he stepped back into the dating pool to seek genuine compatibility. 
• Nice Girl Nana needed relief from isolation. The most effective content shifted her perception of social norms, showing her that “girls like me” are using contraception, allowing her to move from denial to curiosity. 
• Nina Baddie needed relief from the pressure of economic instability. Content focusing on financial resources helped shift her focus from transactional survival (sponsors) to long-term stability. 

This gives us a replicable recipe: identify the pressure point, provide relief through tailored content, and unlock the healthy behavior. 

Lesson 4: And technically? Running experiments on social platforms is messy. 

We cracked a model that we can replicate, but this experiment generated huge technical learnings for the field: 

• The Attention Economy: During the experiments we saw high attrition rates among the youngest segments (Nice Girl Nana) and young men (Barasa Wa Town), underscoring the challenge of retaining attention in a competitive digital ecosystem. 
• Platform Unpredictability: Even in a controlled experiment, you cannot fully control who Meta shows your content to or prevent “noise” from the algorithm.
• Dosage Matters: The results suggest a need for either shorter “flash” experiments to minimize attrition, or more immersive, long-term engagement formats to drive deeper engagement – and behavioural change.
  
  

WHY THIS MATTERS FOR THE FUTURE OF DIGITAL SBCC 

This study boldly set out to segment digital youth by real conversational behavior and measure change by experimenting with content, delivery approaches and digital measurement tools. 

The results show something powerful: Young people’s attitudes and behaviours do shift when messages feel like they were made for them. 

But to get it right, we must design for specific social norms, identities, and pressures, and anticipate how audiences might misinterpret messages based on their fears and context. We must be ready to design “correction” content proactively. 

Shujaaz and iMedia are now shaping our upcoming experiments, where we will continue to share what we’re learning and packaging the main takeaways in shareable toolkits for replication and scale.