Designing and Testing Messenger Conversations to Grow Threads Followers
This project focused on an acquisition experiment designed to grow Threads followers through Messenger outreach. Aimed at parents navigating the holiday season, the experiment tested three key messaging approaches: resourceful, connection-driven, and relatable.
The goal was to determine which messaging style would best resonate with parents, providing them with valuable tips, fostering a supportive community, or simply offering a relatable voice to help them through the chaos of the holidays.
By testing these value propositions, the experiment sought to increase engagement and grow the Threads following while providing a space for parents to connect, find support, and access helpful resources during a stressful time of year.
The project also highlighted my expertise in designing conversational experiences. Through strategic scripting and chatbot design, I crafted a seamless, empathetic dialogue flow that responded to users’ needs, offering tailored tips and a sense of community, all while keeping the interaction personal and relevant.
Messaging Frameworks
My role
Tools
Outline
Timeline
Sr. Digital Producer
Chatfuel
Figma
FigJam
Project Insights
Objectives
Process
User Research
Chatbot Design
Experimentation
Reflection
≈1 week
Project Insights
Optimized Messenger-based acquisition
Tested different messaging strategies on Messenger to convert users into Threads followers, focusing on the holiday season.
Tailored messaging for parent engagement
Developed personalized messages that aligned with parents' needs during the busy holiday season, using relatable, resourceful, and supportive tones
Enhanced user connection through conversational design
Focused on creating a seamless and empathetic conversation flow that encouraged meaningful interactions and built rapport with the audience
This project is about a 8 min read.
Objectives
Primary
Increase Threads followers through organic acquisition on Messenger.
Secondary
Determine which messaging tones—resource-value, support-value, or relatability-value—drive the highest engagement and follower growth.
Process
I focused on understanding the audience's needs through user research, then crafted personas to inform messaging strategies. To drive engagement, I tested three messaging tones—resource-value, support-value, and relatability-value. I also made design decisions around the Nani chatbot persona and conversational pathways to ensure a seamless, empathetic user experience across Messenger.
User Research & Persona Creation
Understanding the target audience was key. Through analyzing user behaviors and feedback, I built personas to better understand their needs, pain points, and preferences during the holiday season. This helped guide the tone and structure of the messaging. In particular, I designed the “Nani” persona as the friendly, relatable guide that would lead the conversation, ensuring it felt personal and empathetic throughout.
Message Development & Testing
I collaborated with the content manager to design Messenger flows with three frameworks—resourceful, supportive, and relatable. Each flow prioritized engaging dialogue and user-centric CTAs to drive connection and follower growth on Threads.
Chatbot Design & Flow Creation
With the messaging strategy in place, I worked on creating a user-friendly, engaging chatbot flow. This involved designing multiple pathways tailored to the personas, including empathetic responses, helpful tips, and calls to action. I ensured the conversation felt natural and humanized, aligning with Nani's persona. The key was to keep it light, relatable, and valuable, with an emphasis on offering support during the holiday season.
A/B Testing & Metrics Tracking
Each message variation was sent to a small test group to evaluate the effectiveness of each messaging tone. Key metrics like click-through rates (CTR) and conversion rates were tracked. Based on these insights, I identified the relatability-focused message as the winner and deployed it to a broader audience of approximately 200,000 users.
Post-Test Analysis & Optimization
After sending the winning message to the full audience, I analyzed post-send metrics, including follower growth rate, CTR, and secondary insights. This helped refine the messaging for future campaigns and assess the success of the campaign in driving organic acquisition and fostering community engagement.
Iterative Feedback Loop
The chatbot pathways were designed to deliver value while collecting user data through saved attributes. This data helps identify user needs, segment audiences, and tailor content effectively. Collaborating with content moderators, I analyzed user input and sentiment to refine messaging, explore new product opportunities, and enhance audience development. Feedback from interactions supports continuous improvements, ensuring the chatbot remains engaging and responsive to user needs.
Understanding our users
To design the user personas and pathways,
I evaluated the bot's offerings, the action I wanted the user to take, our organization's products and services, and historical data from user feedback through content moderation on direct messaging and social platforms.
By aligning these insights, I developed three user personas.
User Personas
Jess, 38
As a single mom of three, I often feel like I’m doing it all alone. I just need advice that actually helps and a community that gets what I’m going through.
Taryn, 26
Being a first-time mom is overwhelming. There’s so much advice out there, but none of it feels right for me. I just want help that fits my life and my child.
Gwen, 58
Raising my grandkids with my husband is a whole new world. I need guidance on parenting tweens today and a space where I can connect with others like me.
User Pathways
Macro Flowchart (High-level)
The macro flow chart was designed to create a seamless and concise user journey, aligning with the holiday theme while keeping interactions efficient. Each pathway guided users toward actionable resources, emotional support, or relatable content.
Additionally, the design incorporated mechanisms to collect user data from input and button choices, enabling future segmentation based on parenting support needs and topics of interest.
Conversational pathways
Leveraging user personas, I designed three conversational pathways tailored to address distinct parenting challenges during the holiday season. Each pathway was designed to reflect user motivations while fostering meaningful engagement
Practical Tips
By focusing on these pathways, the chatbot’s design aligned with the real-life challenges parents face during the holidays, fostering deeper engagement and a sense of support during a busy and often stressful time of year
Offers actionable advice to help parents navigate common holiday stressors, such as time management and family dynamics.
Emotional Support
Providing empathy and reassurance, helping parents feel understood during the chaos and emotional intensity the holidays often bring.
Relatable Conversations
Building connection through shared holiday experiences, ensuring parents feel seen and validated in the midst of seasonal struggles.
Scripted Dialogue
For the chatbot script, I focused on creating a human-centered, empathetic conversational experience designed to meet parents where they are during the often stressful holiday season. My approach began with user research to understand common challenges, emotional triggers, and the types of support parents typically seek during this time.
Based on these insights, I crafted a multi-path script with relatable, conversational language that mimics a genuine dialogue, ensuring users feel heard and supported.
The process involved designing three distinct paths—“Holiday Stress Relief,” “Parenting Tips,” and “Find Community”—each tailored to specific user needs. I tested different tones and structures to ensure the bot felt approachable and engaging while maintaining clarity and purpose. I also incorporated strategic CTA buttons to drive engagement, each limited to 20 characters for clarity and accessibility.
The buttons were carefully crafted to guide users naturally toward actionable steps, whether it was receiving another tip, sharing their thoughts, or connecting on Threads.
Throughout the design, I prioritized first-person language and a warm, empathetic tone to ensure Nani felt like a real, caring individual rather than a generic bot. Each path included branching options, allowing users to explore deeper support while maintaining autonomy in the conversation.
The final script is not just a tool for information but a bridge to a supportive parent community, fostering meaningful connections in an inclusive space.
This project reflects my focus on balancing user needs with conversational flow, ensuring that every message serves a purpose while creating an experience that feels personal, helpful, and engaging.
Experimentation
To optimize engagement and follower growth, I designed an A/B/C test targeting the parenting segment of the Messenger audience. Test groups were randomized to ensure unbiased results and representative performance metrics.
Hypothesis
If Messenger messaging emphasizes relatability, shared experiences, and emotional support, users will feel more connected to the Threads community and be more likely to follow the platform.
Assumption
Messenger users, particularly parents navigating the holiday season, prioritize authentic, empathetic communication and will engage more with content that reflects their experiences and needs.
A/B/C Testing Design
Three distinct messaging tones were tested to highlight the value of Threads:
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Message A (Resourceful): Framed Threads as a hub for parenting tips, actionable advice, and community support.
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Message B (Supportive): Positioned Threads as a safe space for emotional support and connection, particularly during the holiday season.
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Message C (Relatable): Highlighted Threads as a friendly, authentic space, emphasizing shared experiences and parent-to-parent relatability.
Outcome
Winning Message: Message C (Relatable) achieved a 0.40% growth rate during testing, confirming that a conversational and empathetic tone drives the most engagement.
Full Audience Send: Message C was deployed to the broader audience, resulting in a 0.95% follower growth rate and a 0.44% click rate.
Final Chatbot Design
demo.
This demo showcases the winning user journey with 'Relatability' messaging designed to support parents feeling overwhelmed during the holiday season.
In this journey, the chatbot responds with empathy, offering two practical tips to ease holiday stress. After providing actionable advice, it invites the user to connect further on Threads for even more support and inspiration.
This pathway highlights the bot’s relatable tone and thoughtful design, ensuring parents feel seen and supported while seamlessly guiding them toward the next step. It’s all about creating a meaningful, helpful experience during a busy time of year.
Retrospective
Key Learnings
What worked well
The use of relatable, conversational messaging (Message B) was highly effective in driving user engagement and follower growth. By focusing on a warm, friendly tone, I was able to create a sense of connection that resonated deeply with the audience. Additionally, testing and refining the messaging approach through A/B testing allowed me to optimize for the highest-performing content, ensuring the final message aligned with users' emotional needs and interests.
Challenges
Designing a concise user journey that was both engaging and effective at guiding users to the intended CTA—following on Threads—was a significant challenge. The bot needed to provide enough immediate value to be helpful while leaving users intrigued enough to seek more on Threads. Additionally, moving users from Messenger to a separate platform like Threads presented its own hurdles. This transition assumed users either already had a Threads account or were motivated enough to create one, which represented a substantial ask. Balancing these factors required thoughtful design and strategic messaging.
Next steps
To build on the success of this experiment, the next steps involve implementing enhanced sentiment analysis tools to gain deeper insights into user input and emotions. Using the segmentation data collected during the chatbot interactions, tailored follow-up content can be designed to align with parenting topics that resonate most with users. Additionally, seasonal testing of messaging strategies will ensure the bot continues to adapt to evolving user behaviors and needs, fostering ongoing engagement and relevance.