Jeffrey Tjendra
Dec 8, 2024
Reverse trial was created by Elena Verna and has now become the standard for product-led growth (PLG) playbook within the product management community.
Basically, a reverse trial is a pricing model that gives users access to a product's paid features for a limited time. After the trial ends, users are downgraded to a free plan with more limited access
The 2 main types of reverse trials are optional and mandatory that are known are:
Optional reverse trial: Users can choose whether to start with a free plan or a trial of the premium tier.
Mandatory reverse trial: Every new user is automatically enrolled in a free trial.
However, there is a third type of reverse trial that is less common and wasn't possible until AI came along - Triggered Reverse Trial.
The Emerging Third Type: Triggered Reverse Trial
Triggered reverse trial activates trial for paid features based on usage-based triggers. The trigger can either be based on rules or anomalies:
Rule-Based Trigger (Quantitative Activation)
Rule-based triggers are predefined conditions that automatically initiate a premium trial when specific, measurable thresholds are met. These triggers create a systematic approach to unlocking advanced features based on quantitative metrics that indicate potential value or growth.
Consider an A/B testing software using a rule-based trigger approach. In this scenario, the trial could be activated when:
The number of website visitors reaches a specific milestone (Eg. 40,000 visitors)
Total test runs exceed a predetermined limit (Eg. 10 concurrent A/B tests)
Data collection volume approaches a critical threshold (Eg. 50,000 data points analyzed)
The rule-based trigger is predictable and scalable across user segments since it's objective and metrics-driven.
Pattern-Based Trigger (Qualitative Activation)
Pattern-based triggers represent a more sophisticated approach to initiating premium trials, which leverages advanced behavioral analytics and machine learning to identify nuanced user engagement signals.
Unlike rule-based triggers that rely on simple quantitative thresholds, pattern-based triggers analyze complex behavioral sequences, user interactions, and contextual usage - then autonomously determine optimal moments for trial activation.
In this scenario with the same A/B testing software, the trial is triggered after the user demonstrates a specific behavior pattern that indicates they're likely to benefit from premium features. For example:
The user creates multiple A/B tests
The user tests variations across different pages
The user shows advanced segmentation needs
The user frequently checks detailed statistical significance of test results
The pattern-based trigger relies heavily on tracking the user behavior at which stage of the journey, then using algorithm to make decisions on which premium features and/or paid plan to enable for the user.
Real-World Examples of Triggered Reverse Trial
Here are how some of known tech companies are applying triggered reverse trial:
Slack triggers premium features when:
Message history limits are approached
Integration complexity increases
Communication volume expands
Calendly activates advanced features upon:
Multiple event type creation
Complex scheduling rule requirements
Team collaboration needs
Mailchimp unlocks premium capabilities when:
Email list size grows significantly
Advanced segmentation becomes necessary
Detailed reporting is repeatedly accessed
The Future
The future of product activation lies not in rigid, one-size-fits-all models, but in adaptive, context-aware experiences that anticipate and address user needs before they even articulate them. It wasn't practical until AI started to mature.
In line with building an AI-first operations, more and more companies will look to change their traditional upgrade paths into intelligent, adaptive experiences that feel intuitively aligned with user needs and product potential.
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