AlgoTest had 10,000+ signups a month but barely any paid conversions. No funnel visibility, no activation definition, and one generic onboarding flow for everyone from first-time traders to seasoned algo builders.
We interviewed 150+ users across four segments, mapped every drop-off, defined what "activated" actually meant, and rebuilt the entire onboarding around how different traders actually behave — in 6 weeks.
AlgoTest is a no-code options trading platform for Indian markets. It lets traders build, backtest, and execute strategies through a drag-and-drop interface, with paper trading, live execution, and 25+ broker integrations all in one place.
The platform serves two distinct trader types: systematic traders running rule-based strategies, and discretionary traders making judgment calls on market conditions.
Same platform, completely different needs.
The Problem
Through trading courses, community building, and targeted promotion, AlgoTest had built strong top-of-funnel. 10,000+ signups every month. But users weren't converting to paid, and the team couldn't pinpoint why.
Three problems were compounding each other:
No funnel visibility No clear picture of where users dropped between signup and payment. The team was optimizing blind.
No activation definition No shared understanding of what success looked like for a new user. Nothing to optimize toward.
Onboarding that didn't match the user One flow for every trader, regardless of skill level, goals, or trading style. Beginners and experts hitting the same screens in the same order.
Get more paying customers by designing an onboarding experience that works for every trader type — from first-timer to experienced algo trader.
Specifically:
Make the process of systematic trading easier to understand
Map user behavior and define measurable outcomes
Create an onboarding journey that guides users to their first win
Build communication that adapts to each user's progress stage
1. Customer Analysis: Understanding Who Was Dropping Off
2. Funnel Analysis: Finding the Real Drop-Off Points
With the qualitative picture clear, we mapped the full user journey and measured conversion at every stage.
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The Tour → Backtest gap was the biggest opportunity. Users were losing interest before they ever experienced the product's core value.
3. Onboarding Journey: Education First, Conversion Second
The insight from research was consistent: users didn't need more upgrade nudges. They needed to experience a win first. We redesigned the onboarding around that principle.
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Timing and content were mapped directly to the drop-off points found in research. Segment-specific variations for beginners vs. advanced traders throughout.
4. Activation Metrics: Defining What Success Looks Like
Before this engagement, AlgoTest had no hard definition of an activated user. We built one from the behavioral data.
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From this, the team had a clear baseline activation-to-monetization rate — and a concrete target to improve against.
5. User Cohorts: Behavior-Based Segmentation
Instead of grouping by persona or acquisition source alone, we built cohorts using three behavioral dimensions:
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Every cohort mapped to a clear objective: activation, conversion, retention, or expansion. Communication, incentives, and product nudges all tied directly to where the user was in their journey.
6. Messaging: Three Trader Types, Three Flows
With segmentation in place, we built lifecycle messaging triggered by actual user behavior, not time-based blasts.
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Every message personalized with name and current backtest count. Brand voice consistent throughout: "At AlgoTest, we Test Then Trade."
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Before this engagement, we had no clear picture of why users weren't converting. The research process alone changed how we think about our users, we finally had language for the different problems different traders were facing. The onboarding system gave us a framework we're still building on.
Rohit Mukul | Founder
Zeelab Pharmacy
