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How $1 trials f*cked our acquisition

r/indiehackers
8/15/2025

Content Summary

The post discusses how implementing a $1 trial for an AI-powered SEO/GEO platform led to a significant drop in signups, especially from the US and UK. The author initially believed the trial would filter out non-serious users and cover onboarding costs, but it backfired, causing a 90% drop in signups. The team reverted the change after 10 days. Comments suggest that users were suspicious of the $1 charge, and alternative solutions like demo accounts or shorter free trials were proposed.

Opinion Analysis

Mainstream opinion suggests that $1 trials can be perceived as scams, especially in cold traffic. Many users and commenters believe that the trial created unnecessary friction and deterred potential customers. There is also a debate about whether the trial was the main cause of the drop in conversions or if other factors played a role. Some suggest that better A/B testing could have prevented the issue. A few users advocate for alternative methods like demo accounts or gated features instead of charging even a small fee. The discussion highlights the importance of user trust and the need for careful experimentation when making pricing decisions.

SAAS TOOLS

SaaSURLCategoryFeatures/Notes
[No specific SaaS tools mentioned][N/A][N/A][N/A]

USER NEEDS

Pain Points:

  • Users are skeptical of $1 trials, perceiving them as scams
  • High onboarding costs for free users
  • Difficulty in distinguishing serious users from casual testers

Problems to Solve:

  • How to filter out non-serious users without deterring potential customers
  • How to reduce the cost of onboarding free users
  • How to maintain conversion rates while implementing cost-recovery mechanisms

Potential Solutions:

  • Implementing a demo account without upfront costs
  • Shortening the free trial period and gating premium features
  • Requiring a card upfront but not charging until the trial ends
  • Adding a manual onboarding step to filter out casual users

GROWTH FACTORS

Effective Strategies:

  • Testing pricing models and being ready to revert if they fail
  • Listening to user feedback and adapting based on real-world results

Marketing & Acquisition:

  • The importance of maintaining a seamless user experience to avoid losing potential customers
  • The risks of implementing changes without A/B testing

Monetization & Product:

  • The challenge of balancing onboarding costs with user acquisition
  • The need for a strong product-market fit to justify pricing decisions
  • The risk of alienating users with perceived scam-like practices (e.g., $1 trials)

User Engagement:

  • The value of community input and peer feedback in shaping product decisions
  • The importance of clear communication about pricing and user expectations