PODCAST

The Attribution Challenge: How to Track Organic Growth When Users Don't Click Links

Author
Jason LouroJason Louro

Attribution is one of the biggest headaches for B2C startups, especially when it comes to organic social media growth. Users see content, remember your app name, then search for it directly in the app store—creating a measurement nightmare for marketing teams. Amy Cameron, Head of Marketing at Sylvi AI, developed creative solutions to track organic performance despite these limitations.

Speaking on the Levels Podcast, Amy shared practical approaches to attribution that any startup can implement, even without sophisticated tracking infrastructure.

The Fundamental Attribution Problem

Amy's team faces the same attribution challenge that plagues most B2C apps: users don't always follow clean conversion paths:

"Yeah, it's a good point. So on the on the Sylvi account, we have a one link in our bio that people can click on and we track all the conversions from that one link for all the other accounts. They just say Sylvi in the bio. There's no link or anything."

This setup creates immediate measurement challenges. While the main account can track direct conversions, the majority of their 15 test accounts rely on users manually searching for the app:

"So people have to then go to the app store and download the app. And while there's a bit of friction there, we are getting more downloads from TikTok than we are met where we're paying for downloads."

This finding is crucial—despite the attribution challenges, organic social is outperforming paid channels in terms of total downloads.

The Timing-Based Attribution Method

When direct link tracking isn't possible, Amy uses timing correlation to understand which content drives results:

"However, I have a pretty good idea that like, so yesterday we posted one, for example, and about 10 minutes after I posted it, we got like 15 new trials."

This approach requires:

  • Consistent posting schedules across different accounts
  • Real-time monitoring of signup activity
  • Clear timing documentation of when content goes live
  • Pattern recognition across multiple posting cycles

While not perfectly precise, timing-based attribution provides actionable insights about content effectiveness.

Self-Reported Attribution Systems

Sylvi implements user surveys during onboarding to capture attribution data directly:

"So we do, we have self attribution on onboarding. So people stay where they heard from us. Unfortunately, we can't see which like ad it is, how, or not ad, sorry, which post is."

Self-reported attribution has limitations—users don't always remember exactly where they first encountered your brand—but it provides valuable directional data about marketing channel effectiveness.

Direct User Engagement for Attribution

One of Amy's most effective attribution methods involves personal outreach to new users:

"As soon as people come on and start a subscription, add them as friends, talk to them. Where did you find out about us? And like, it's such a manual process, but I cannot stress how insightful it's been for myself or Sam to be talking to people in the app and like where they've come from, how long have you been learning? What post was it that you found us from?"

This manual approach provides several benefits:

  • Detailed context about user discovery paths
  • Content-specific attribution down to individual posts
  • User journey insights beyond just the final touchpoint
  • Relationship building that improves retention

While labor-intensive, this direct engagement often reveals attribution patterns that automated systems miss.

The Disconnect Between Viral and Valuable

Amy's manual tracking revealed a crucial insight about content performance:

"So we've had a couple of viral posts at zero installs. We've had a couple of posts that have done like 20K views, but there are hundreds of comments being like, what is this app? Where can I get it?"

This finding highlights why traditional social media metrics can be misleading for app marketers. High engagement doesn't necessarily correlate with business outcomes, making attribution even more important for understanding true content ROI.

The Butter Post Case Study

Amy's most unexpected attribution success illustrates the challenges of measuring organic content:

"I posted a really silly TikTok yesterday on my personal account about like where French people keep their butter, like you keeping your butter in the fridge or you keeping your butter on the side... But that created, like yesterday we had one of the most, like the highest subscribers we've had in a while."

This post about butter:

  • Never mentioned Sylvi directly
  • Appeared on a personal account, not the brand account
  • Only connected to Sylvi through Amy's bio
  • Generated significant app downloads despite indirect attribution

The success demonstrates how authentic, engaging content can drive results through indirect pathways that are nearly impossible to track with traditional analytics.

Cross-Platform Attribution Complexity

Sylvi's multi-platform strategy compounds attribution challenges:

"When something then does well on TikTok we reuse it on Instagram, on the Sylvi account but I think you cannot you cannot focus on every channel."

Repurposing successful content across platforms makes it difficult to determine which channel actually drove conversions, especially when users might see the same content multiple times before converting.

Platform-Specific Attribution Limitations

Different social platforms present unique attribution challenges:

  • TikTok: Users rarely click bio links, preferring to search app stores directly
  • Instagram: Story links expire, making historical attribution difficult
  • Reddit: Community rules often prohibit direct promotion, requiring indirect attribution methods
  • Organic word-of-mouth: Completely untrackable but potentially the most valuable channel

The Volume Validation Approach

Amy uses overall download volume to validate attribution assumptions:

"So people have to then go to the app store and download the app. And while there's a bit of friction there, we are getting more downloads from TikTok than we are met where we're paying for downloads."

By comparing total organic downloads to paid channel performance, she can validate that their organic efforts are driving meaningful results, even without perfect attribution.

Attribution Tools and Workarounds

For startups facing similar challenges, Amy's team uses several practical solutions:

  • Branded Search Tracking: Monitor app store search volume for brand terms
  • UTM Parameter Testing: Use trackable links when possible, even if adoption is limited
  • Cohort Analysis: Compare user behavior from different acquisition periods
  • Survey Integration: Ask detailed attribution questions during onboarding
  • Manual Outreach: Direct conversations with new users for qualitative insights

Framework for Organic Attribution

Based on Amy's experience, here's a practical framework for B2C startups:

Immediate Implementation (Week 1)

  • Add attribution questions to user onboarding
  • Set up basic timing tracking for content posts
  • Create standardized UTM parameters for trackable links

Short-term Systems (Month 1)

  • Implement manual user outreach processes
  • Establish correlation analysis between posting and signups
  • Set up branded search term monitoring

Medium-term Infrastructure (Month 3)

  • Develop cohort analysis capabilities
  • Create cross-platform content performance tracking
  • Build systematic user feedback collection

Long-term Optimization (Month 6+)

  • Implement advanced attribution modeling
  • Develop predictive attribution algorithms
  • Create automated attribution reporting systems

Key Takeaways

Amy's approach to attribution offers practical lessons for resource-constrained startups:

Start with manual processes - Direct user conversations provide the richest attribution insights

Use timing correlation - Post timing vs. signup spikes can reveal content effectiveness

Focus on patterns over precision - Look for directional trends rather than perfect attribution

Validate with volume metrics - Compare channel performance at the macro level

Build relationships for insights - User conversations provide attribution data and improve retention

Accept imperfection - Approximate attribution is often sufficient for strategic decisions

Perfect attribution remains elusive for most B2C startups, especially in organic social media. However, creative approaches like timing analysis, user surveys, and direct engagement can provide sufficient insights to guide marketing strategy effectively.

The goal isn't perfect measurement—it's actionable intelligence that helps you double down on what works while avoiding what doesn't.

Listen to the full conversation to hear more about Amy Cameron's practical approaches to marketing measurement and attribution.