Onboarding project | Mudrex

Have you ever wondered what a user onboarding journey looks like on a financial app, especially crypto? What are the granular steps and touch points that drives the user to complete the onboarding? Or what are the key mistakes which makes the user drop off the onboarding flow? How small yet effective copies create cognitive biases that fuel onboarding?

Let us take a deep dive into the Onboarding Flow for Mudrex, a crypto investment platform, to understand the nuances of user onboarding, right from the discovery of the product till the first milestone for the user.

Time to call some users 📞

Disclaimer: No Devi Prasad or Babu Rao were harmed in this process. Calls were only made recently onboarded users.

After talking to several users about their onboarding experience, there were some key insights and trends that could be summarised as:

Who are these users?

After talking to these users, we were able to figure out some key cohorts in which these users lie. These user cohorts differ significantly in terms of their lifestyle, preferences, spending habits, pain points and requirements.

Let us take a look at these cohorts.

ICP 1 (Crypto Bros and DeFi Gurus)

This user cohort consists of the native crypto ecosystem audience. Folks who know ins and outs of the ecosystem. The believers in Decentralised Finance.

ICP 2 (Traders and Arbitrage Hunters)

This cohort consists of professional traders who utilise small market movements to book profits. They are native traders who use various technical analysis strategies to predict market movement.

ICP 3 (Explorers and HODLers)

This cohorts comprises of new adopters, core believers and risk-averse users. These users focus on investing for long-term for potential capital gain from the value appreciation.

Prioritising ICPs

The above defined ICPs can be prioritised as:

This analysis clearly shows that ICP 2 (Traders and Arbitrage Hunters) check all boxes when comes to prioritisation based on given parameters, followed by ICP 3 (Explorers and HODLers) and ICP 1 (Crypto Bros and DeFi Gurus) respectively. ICP 2 shows a high frequency of usage along with a high appetitie to pay, while ICP 3 also shows a moderate adoption rate given their willingness to try new asset classes and a decent appetite to pay, with a significant TAM.

Hence, we can prioritise ICP 2 and ICP 3 for onboarding.

Customer Journey Mapping

Now that we have clarity on who these users are. Let us try to look at how the customer journey looks like. What they are trying to do with our product? What are the use cases they are hiring our product for?

Customer Journey Map

Our main goal from defining a customer journey map is to figure out what the user is trying to do. Let us look at the journey map for a Mudrex user to analyse the different phases from discovery to activation for the user - to see how the user behaves, feels and interacts with the product.

This journey will be slightly different for different ICPs given different goals that they are trying to achieve with the product and hence different interactions and behaviour. However, the core goals for using the product might be the same, which we will discuss further through JTBD.

For this journey, consider a 25 year young professional Rahul, working in Bangalore, who wants to explore crypto investing but is confused about the options available and has trust issues due to high number of financial frauds in the market.

This customer journey map clearly indicates how the customer experiences during different stages of the journey and how their action are derived from their emotions, highlighting the complexity of each stage for the user.

JTBD - Jobs to be done

Each type of user has different goals, and hires your product for different jobs they want to achieve. For Mudrex ICPs, the main use cases for each user cohort can be seen as:

Validating User Goals

We can now validate these defined goals based on the observed user behaviour and insights from our user calls. This will help draw a parallel between what the user conveys and what their actions tell us, hence forming a correlation between the both.

Analysing User Behaviour

Correlating User Behaviour to User Insights

Let us now do a quick deep dive into the current onboarding process used at Mudrex. This exercise will help us determine what is working in the flow, what is not working and what are the improvements that can be done to improve the onboarding experience. Further, we also highlighted the key cognitive bias that drive user behaviour across the onboarding flow.

Onboarding Teardown_ Mudrex.pdf

A user is not successfully onboarded until they have completed their activation milestone. Hence, the activation metrics are extremely useful.

Based on the user insights, goals and their behaviours, we can define a couple of hypothesis which might indicate a successful user onboarding and then validate them based on some supporting metrics to conclude on the activation metrics to be used for Mudrex.

Activation Hypothesis

Hypothesis 1

Hypothesis:

First deposit within 24 hours of signup

Explanation:

Users who complete their first deposit within 24 hours of signup are more likely to continue investing and engaging with the platform.

Making the first deposit quickly is a strong indicator of user intent. A seamless deposit experience reduces friction and ensures users don’t drop off after signup. Faster deposits also build trust in the platform’s security and efficiency. If users delay depositing, it may indicate uncertainty or usability issues.

Key Metrics to Track:

• Deposit conversion rate (D0, D1, D7) - number of signed up users depositing
• Time taken to first deposit (median and average)
• Drop-off rate between signup and first deposit
• Retention rate of users who deposit vs. those who don’t

Hypothesis 2

Hypothesis:

Investment/trade in 3 different coins within 7 days

Explanation:
Users who invest/trade in at least three different coins within the first 7 days are more likely to stay engaged and develop long-term trading habits.

Exploring multiple assets increases user engagement, diversification, and exposure to different opportunities. If a user limits themselves to just one asset, they might be less inclined to continue trading. Encouraging broader exploration enhances retention and increases trading volume.

Key Metrics to Track:

• Percentage of active users trading in 3+ coins within 7 days
• Average number of different assets traded per user
• Retention rate of multi-asset traders vs. single-asset traders
• Trading volume growth over time

Hypothesis 3

Hypothesis:

$100 AUM in 14 days

Explanation:

Users who accumulate at least $100 in Assets Under Management (AUM) within 14 days are more likely to continue investing and become long-term customers.

Higher AUM indicates a stronger commitment to the platform. If a user reaches $100 quickly, it suggests they trust the platform and see value in their investments. Low AUM early on may indicate hesitation or lack of confidence. This metric also correlates with revenue potential, as platform fees depend on AUM.

Key Metrics to Track:

• Percentage of users reaching $100 AUM in 14 days

• Average AUM per user over time

• Churn rate of high vs. low AUM users

• Correlation between AUM and trading frequency

Hypothesis 4

Hypothesis:

5+ overall trades/investments in 7 days (can be same assets/coins)

Explanation:

Users who make at least 5 trades/investments within the first 7 days are more likely to become active, recurring traders.

Frequent trading early on suggests that users are comfortable with the platform and see value in continuing to engage. A low trade count may indicate that the user is still hesitant or does not find the trading experience compelling enough. Encouraging multiple trades increases platform stickiness and long-term engagement.

Key Metrics to Track:

• Percentage of users making 5+ trades within 7 days

• Average number of trades per user in the first week

• Retention and engagement rates of high-trade vs. low-trade users

• Trading volume growth over time

Hypothesis 5

Hypothesis:

First withdrawal within 14 days of signup

Explanation:

A user completes their first withdrawal within 14 days of signing up.

This measures whether users see full-cycle value in the platform. A withdrawal indicates that they have deposited, traded/invested, and now trust the platform enough to cash out their funds. If users complete a withdrawal within the first 14 days, it shows that they are actively engaging with the platform beyond just experimentation. A smooth withdrawal experience also builds confidence, making users more likely to reinvest, deposit again, and continue using the platform. If withdrawal rates within this timeframe are low, it could indicate friction in the process or a lack of perceived value in cashing out, signaling areas for optimization.

Key Metrics to Track:

• Percentage of users making a withdrawal within 14 days.
• Average time taken from first deposit to first withdrawal.
• Retention rate of users who complete a withdrawal vs. those who don’t.
• Number of users who re-deposit after withdrawing.

Validating Hypothesis

Given Mudrex is in early scaling, we can track three key outcomes to validate our hypothesis. These include:

1. Impact on retention curve
2. Impact on referral and wom
3. Impact on LTV

Impact on Retention Curve

Impact on Referrals

Impact on LTV

Conclusion