Eugen.Product Designer

Main page

Copy Trading App — Redesigning the Subscription Experience

In this app, clients can subscribe to experienced traders and automatically copy their strategies. Clients profit from the traders’ successful deals, while traders earn a commission from the profits they generate for subscribers.

Business goals

Double 7-day retention
Increase MAU
Improve first subscription conversion

Double 7-day retention
Increase MAU
Improve first subscription conversion

Starting point

When I joined, the team had never conducted structured UX research and had little understanding of how users actually experienced the product. My first task was to involve the team in the design process and equip them with tools to see the product from the user’s perspective.

Research phase

To uncover the core problems, I conducted a research phase. I started by framing the challenge with a User Story Map, JTBD, and a Customer Journey Map. Next, I ran 17 user interviews, which revealed that while users aimed to earn money, they struggled to understand commissions and subscription types. To capture ongoing insights, we added an in-app feedback form — within two weeks we collected 600+ responses highlighting recurring issues. Finally, data analytics confirmed the findings: many users made no copied trades at all, and among the rest, only 57% of trades were copied. This showed a failure in the core functionality directly affecting retention.

Below, I go into more detail about key steps.

JTBD

I conducted workshops with the team to establish the stages of the investor's life cycle and their primary tasks.

We created an expert evaluation of these stages and defined the user's core functional job. I planned to confirm this result in qualitative and quantitative research.

I conducted workshops with the team to establish the stages of the investor's life cycle and their primary tasks.

We created an expert evaluation of these stages and defined the user's core functional job. I planned to confirm this result in qualitative and quantitative research.

User interwiews

Based on the JTBD and CJM, I formulated a list of questions for users and conducted a series of interviews. The main goal of the research is to understand how users progress through the funnel from registration to obtaining their first result, as well as to validate artefacts.

Here are excerpts of prepared interview questions for different stages of the user journey:

After conducting 17 interviews, I reviewed the results with the team, and we reached several conclusions:

the goal of our clients is to earn additional income through investments (confirmed hypothesis from JTBD)
all respondents consider a combination of different metrics when choosing a subscription
all respondents choose a master trader from the top 10 ranking
100% of the respondents could not explain how the commission and types of subscriptions for master traders work

the goal of our clients is to earn additional income through investments (confirmed hypothesis from JTBD)
all respondents consider a combination of different metrics when choosing a subscription
all respondents choose a master trader from the top 10 ranking
100% of the respondents could not explain how the commission and types of subscriptions for master traders work

In-app feedback form

We gained a clear understanding of the user’s life cycle, their motivation, and the main barriers they faced. To keep receiving timely insights on subscription quality — and to measure the impact of future solutions — I designed and introduced a feedback form that enabled us to continuously collect user input on subscriptions.

I designed a simple feedback form — a 5-point rating and open text field — shown right after users unsubscribed from their master trader. Since users had no direct way to share thoughts on subscriptions before, this generated plenty of insights, which we later categorized to create a second version with predefined options.

In the second iteration of the form, we uncovered six main issues that users were consistently raising. By this point, the feedback wasn’t just helping us understand the problems — it was guiding us to prioritize which issues mattered most to our users.

lack of understanding of subscriptions and commission being among the top ones

Key problems identified

No clear information on the minimum investment needed to fully copy trades.

Confusing subscription types and comissions. 100% of the respondents could not explain how the commission and types of subscriptions for master traders work

Nearly 1/3 of users didn’t get any trades copied at all. 30% of new users had zero copied trades; among the rest, only 57% of trades were copied. This core functionality failure directly impacted retention, MAU, and DAU.

No clear information on the minimum investment needed to fully copy trades.

Confusing subscription types and comissions. 100% of the respondents could not explain how the commission and types of subscriptions for master traders work

Solutions

A. Fixing the “Minimum Investment” issue

Problem

No clear information on the minimum investment needed to fully copy trades.
Nearly 1/3 of users didn’t get any trades copied at all. 30% of new users had zero copied trades; among the rest, only 57% of trades were copied. This core functionality failure directly impacted retention, MAU, and DAU.

Context

Some traders set unrealistically low minimum investment amounts to attract more subscribers. As a result, their big trades can’t be copied properly by users with small budgets, causing losses. Meanwhile, the trader still ranks high in the top charts simply because of the number of subscribers, not the success of their strategy.

Solution

Removed manual minimum setting from trader accounts.
Built an algorithm to calculate the real minimum based on trading strategy. If the user didn’t meet the requirement, the system suggested an alternative trader.
Implement into the app and web

Problem

No clear information on the minimum investment needed to fully copy trades.
Nearly 1/3 of users didn’t get any trades copied at all. 30% of new users had zero copied trades; among the rest, only 57% of trades were copied. This core functionality failure directly impacted retention, MAU, and DAU.

Context

Solution

Removed manual minimum setting from trader accounts.
Built an algorithm to calculate the real minimum based on trading strategy. If the user didn’t meet the requirement, the system suggested an alternative trader.
Implement into the app and web

Then, together with the team, we have developed an algorithm that calculates the minimum subscription amount based

on the trading strategy

After implementing the solution, we observed a 28% improvement in the trade copy metric, as well as an increase in the overall copied trade statistics in the user profile to 98%.

Then, together with the team, we have developed an algorithm that calculates the minimum subscription amount based

on the trading strategy

After implementing the solution, we observed a 28% improvement in the trade copy metric, as well as an increase in the overall copied trade statistics in the user profile to 98%.

B. Redesigning the Subscription Scenario

Problem

Confusing subscription types and comissions. 100% of the respondents could not explain how the commission and types of subscriptions for master traders work
Nearly 1/3 of users didn’t get any trades copied at all. 30% of new users had zero copied trades; among the rest, only 57% of trades were copied. This core functionality failure directly impacted retention, MAU, and DAU.

Context

Our research revealed that users couldn’t explain how the master trader’s commission or the two subscription types worked. Even some of our analysts couldn’t answer all my questions on this topic. Naturally, users lacked that level of expertise and were making decisions mostly by guesswork. Most importantly, they couldn’t predict the potential returns of a strategy or how much they needed to invest. Being able to assess risk and return is critical in trading.

Solution

Users choose a copy proportion based on their volume, not the trader’s.
The system automatically calculates the required investment.
Users can set aside support amount to protect against market instability.
All subscription details are shown upfront before confirmation.

In the proportional copy type, users didn’t understand how to set the trade volume or how the keeper balance that protects their investment works.

Subscription screen before changes:

The first prototypes showed only new mechanics and were poorly detailed. But they gave me the opportunity to quickly check a series of corridor tests.

After a few iterations, I prepared a prototype that completely repeats the future functionality and gave it to users for testing.

I designed an entirely new scenario that replaced the previous subscription types. Now, users could choose the proportion that suited them best for copying trades, based on their own volume rather than the master trader's volume.

Key change

The system will calculate the required investment amount for the user based on the selected proportion. One universal subscription type instead of two.

Support amount feature

Users can also set aside an amount to help them withstand losses in case of market instability

Summary screen

Users can view all subscription details before making a decision

Results

Despite fears about user reaction to major changes, A/B testing and interview feedback were strongly positive. And we made the decision to launch.

💡 Outcome:
Through deep research, data-driven decisions, and iterative design, we turned a confusing and unreliable subscription process into a transparent, predictable experience — directly boosting engagement, satisfaction, and key business metrics.

Despite fears about user reaction to major changes, A/B testing and interview feedback were strongly positive. And we made the decision to launch.

Next case

#media

#sports-tech

Sports online’s redesign

Quick overview on redisigne sports statistick

Learn more