Guided Workflows
Last updated
Last updated
This section provides essential workflows to help you gain actionable insights from the app. These workflows address specific challenges and offer clear solutions, ensuring a smoother, more efficient experience.
Tracking user behavior and platform performance begins with monitoring key metrics: visitors, sessions, transactions, active wallets, page visits and wallet spent. Together, these metrics provide a comprehensive view of how users engage with your platform, helping you identify areas for improvement.
Visitors represent all users who land on your platform, regardless of whether they connect their wallet. A high number of visitors without conversions can indicate the need for better engagement strategies. Sessions reveal how long users stay active, with more sessions or longer durations reflecting higher engagement. Short sessions may point to user experience issues.
Transactions track wallet interactions like purchases or transfers, offering insight into how users engage financially. A low number of transactions could suggest that users are not finding enough value. Active wallets measure meaningful user engagement, and drops in this metric can signal retention problems.
Page visits show which areas of your platform are drawing the most attention, helping you identify high-traffic pages that are valuable to users and low-traffic ones that may need adjustments. Lastly, wallet spend tracks user financial activity, allowing you to identify high-value customers and the campaigns driving the most revenue.
Tracking where your high-value users come from helps you make smarter marketing decisions. In this section, you'll learn which referrers (like social media, campaigns, or websites) bring in users who spend the most or interact with your platform.
Instead of just looking at traffic volume, focus on wallet spend. By sorting referrers based on how much users from those sources spend or engage, you can figure out which channels are giving you the best return. This lets you invest in the ones that bring real value and avoid those that don’t.
By selecting a specific referrer, you can explore Session Details to understand how visitors interact with your platform and see which Wallets were connected during these sessions. This helps you identify which referrers bring in the most valuable users and which wallets drive significant activity, allowing you to optimize your marketing efforts and focus on high-value sources.
In Referrer Sessions, you can see detailed information about each session, such as how long users stayed, their actions, where they dropped off, and where they came from.
This helps you answer key questions:
Which campaigns or links did they click to get acquired by the referrer?
Identifying the specific campaign or referral source that brought the users to your platform will help you understand which acquisition channels are most effective.
Are users from this referrer engaged?
See how long they stay and what actions they take to determine if they’re getting value from your platform.
Do these sessions lead to wallet connections or transactions?
Track what users do during their visit to measure whether this referrer drives meaningful engagement.
When you look at Referrer Wallets, you can track which wallets were acquired through a particular referrer and sort them by Lifetime Wallet Spend. This shows how much each wallet has spent on your platform since their first transaction, allowing you to spot your most valuable customers.
Retaining users is just as important as acquiring them. Retention metrics reveal whether users are finding value in your platform and returning after their first interaction. These metrics help you identify what’s working to keep users engaged and how to replicate those successes across new campaigns or features.
Retention metrics, like Day 7, Day 30, and Day 90, offer a snapshot of user engagement over time. Tracking these critical intervals allows you to better understand user behavior and identify opportunities to improve long-term retention.
Tracking Retention at Key Intervals: Day 7, Day 30, and Day 90
Day 7 Retention measures how many users return within a week of their first visit. The first week is crucial for hooking new users. Low Day 7 retention often points to issues with the first impression your platform makes, such as onboarding or immediate value.
Day 30 Retention tracks how many users return a month after their first visit. A strong Day 30 retention suggests users are finding ongoing value and are more likely to become loyal. Low Day 30 retention indicates users may lose interest after the initial few weeks.
Day 90 Retention shows how many users are still active three months after their first interaction. This metric reflects long-term loyalty. Users who stick around for 90 days are often your most valuable customers. Low Day 90 retention signals a need to improve long-term engagement.
Retention heatmaps help visualize user retention over time. They show how well you retain users (wallets) and how many return after specific periods.
Here’s how to read and use a retention heat map:
Cohorts: Each row represents a group of wallets that first connected to your platform during a specific week or month. This allows you to see how different groups of users behave over time.
Columns (0, 1, 2, etc.): These columns show how many weeks or months have passed since the wallets' first interaction. The percentages within each column show the proportion of wallets from that cohort that returned in subsequent weeks or months.
Start with the First Week/Month (Column 0):
The values in the first column (0) represent the number of wallets that initially connected to your platform in the given week or month.
The rows represent different cohorts of wallets based on the week they were first seen on the platform.
Example: In the row labeled "01/07/24," 6,376 wallets first connected to your platform during this week.
Track Retention over Time:
As you move right across the row, the percentages show how many wallets from that cohort returned after 1 week, 2 weeks, etc.
Example: For the cohort starting on "01/07/24," 12% of wallets returned after 1 week, 7% after 2 weeks, 5% after 3 weeks, and so on.
Higher percentages across time indicate better retention and continued engagement.
Identify Drop-Off Points:
Look for where the percentages drop significantly across the weeks or months. This shows where user engagement is declining.
Example: For the cohort that connected during "01/07/24," retention falls from 12% in Week 1 to 7% in Week 2, and then to 5% in Week 3. This decline could indicate a point where users lose interest, signaling that improvements may be needed to sustain engagement beyond the first week or two.
Compare Different Cohorts:
Compare retention rates across different cohorts (rows) to see how well specific groups of users are retained.
Example: In the cohort from "15/07/24," 9,680 wallets connected during that week, and 12% returned after 1 week, followed by 8% in Week 2, which is a slightly stronger retention compared to the "01/07/24" cohort. This comparison helps you identify whether product changes or marketing efforts are more effective in driving better long-term engagement.
Tracking notable wallets and high-value transactions allows you to focus on your most valuable users, particularly those who contribute the most to your platform. By understanding wallet activity and spending patterns, you can optimize your efforts toward retaining premium customers and identifying opportunities for growth.
Notable wallets are those that engage the most or spend the most on your platform. By analyzing wallet data, you can easily identify your top customers based on their activity. Users with high lifetime spend or frequent transactions are typically your most valuable users.
Navigate to the Wallets Section: On the left side of the app, you’ll find the Wallets section. This area provides detailed insights into each wallet’s activity.
Sort by Wallet Spend: Once in the Wallets section, you can sort wallets by Wallet Spend to view the top spenders for a selected time period. This allows you to quickly identify your most engaged and valuable customers based on how much they’ve spent on your platform over time.
Investigating Notable Wallets
Once you’ve identified your notable wallets, it’s important to dig deeper into their activity to understand how they were acquired and how they interact with your platform.
Here’s how to investigate notable wallets:
First Seen Date: By checking when a wallet was first seen on your platform, you can track when they were acquired and understand the timeline of their engagement. This helps you pinpoint which campaigns or events may have brought them in.
Lifetime Wallet Spend & Net Worth: Look at the Lifetime Wallet Spend to see how much they’ve contributed to your platform since their first transaction. Their Net Worth gives you a broader sense of their financial activity and potential as a premium customer.
Drill Down into Sessions: By drilling down into their sessions, you can identify their behavior, such as how they interact with your platform during each visit. This includes tracking what pages they visit, their actions, and when they drop off. You can also determine the source that brought them in or their first touch attribution, which helps you pinpoint the source that initially brought these users to your platform. By identifying the acquisition channel or campaign responsible for bringing in high-value users, you can focus your efforts on strategies that attract and convert similar users. For example, if a significant number of high-value users consistently come from a particular campaign, you can prioritize similar approaches to increase user acquisition.
High-value transactions are those with significant wallet spend made on your platform during a specific time period, whether it’s a transfer, purchase, or any other financial activity. These transactions highlight user engagement and the monetary flow within your platform.
To find high-value transactions:
Go to the Transactions Section: On the left side of the app, click on Transactions to view all activities.
Sort by Wallet Spend: In the Wallet Spend (USD) column, sort to display the highest-value transactions for the selected time period.
Once you've identified high-value transactions, it's essential to dive deeper into these transactions to understand the behavior and motivations behind them. High-value transactions often represent key moments of engagement, and analyzing them can provide insights that help optimize your platform for premium users.
Steps to Investigate High-Value Transactions:
Use the Transaction Dropdown for Detailed Analysis: In the Transactions section, click the dropdown next to a transaction entry to uncover essential details:
Tokens Transferred: See the tokens involved to understand what assets are being transferred.
Wallet Addresses: Analyze the wallet addresses of both the sender and recipient. This provides insight into which users are engaging in significant transactions.
Gas Fees and Value: Understand the gas value and total value in USD to confirm the financial importance of the transaction.
Identify Spending Patterns:
Transaction Frequency: Are high-value transactions happening frequently with specific wallets or just as one-off events? Identifying repeat transactions can help you understand which users are deeply engaged.
Transaction Timing: Are these large transactions connected to your platform's specific promotions, features, or events? You can pinpoint what drives this type of activity by identifying when these transactions occur.
Connect High-Value Transactions with Campaigns: If high-value transactions are tied to specific campaigns or events, you can identify which strategies attract your most valuable users. This helps you focus future marketing efforts that drive the most revenue.
Analyzing high-value transactions, you understand where your platform generates revenue and gain insights into user motivations. This allows you to build stronger engagement strategies and cater more effectively to high-spending users.
Tracking active wallets and growth accounting provide essential insights into user engagement and platform growth. These metrics help you monitor wallet activity, understand user behavior, and evaluate the effectiveness of your marketing and retention strategies.
Key Wallet Metrics:
New Wallets: These wallets represent new users engaging with your platform for the first time, offering insight into acquisition success. Monitoring new wallets gauges the effectiveness of acquisition campaigns. A spike in new wallets indicates a successful campaign or marketing push.
Retained Wallets: Users who consistently return after their first interaction. Tracking retained wallets measures user satisfaction and long-term engagement. Low retention may indicate issues with the user experience or platform value.
Churned Wallets: Wallets that stop engaging after being active for a period of time (e.g., 30 days). This helps you spot drop-off points and potential issues with user retention. An increase in churned wallets signals a need to reassess your user engagement strategies.
Resurrected Wallets: Wallets that were once inactive but have re-engaged with your platform. Monitoring resurrected wallets evaluates the success of your re-engagement campaigns or events that drive users back.
View these wallet metrics in weekly or monthly formats to track growth over different periods. By switching between these views, you can:
Analyze Short-Term and Long-Term Trends: Use weekly views to measure the immediate impact of campaigns, while monthly views can help identify broader patterns in wallet growth and retention.
Adjust Strategies Quickly: If you notice a decline in retained wallets or an increase in churned wallets in weekly views, you can implement quick fixes to improve engagement before the problem escalates.
Understand Growth Accounting: The breakdown of new, retained, and resurrected wallets over time offers a clear understanding of how your platform is growing and retaining users.
Monitoring active wallets and applying growth accounting helps you:
Focus on strategies that retain users and minimize churn.
Assess the success of your marketing and re-engagement campaigns.
Improve user loyalty by identifying what works and replicating a successful strategy.
User stickiness helps you understand how often users (wallets) come back to your platform on selected time period. It compares daily, weekly, and monthly activity to show how engaged users are over time. The goal is to see how frequently users return to interact with your platform, which tells you if they find value in your services.
Daily Active Wallets (DAW): This tells you how many wallets are active on your platform each day. A higher DAW means users are interacting frequently on a daily basis.
Weekly Active Wallets (WAW): This measures how many unique wallets are active over a week. A higher WAW means users are coming back throughout the week.
Monthly Active Wallets (MAW): This tracks how many unique wallets are active in a month. A higher MAW shows long-term engagement.
What to look for:
A higher DAW/WAW ratio means users are coming back regularly within the week.
A higher WAW/MAW ratio shows consistent engagement on a weekly basis throughout the month.
A higher DAW/MAW ratio means wallets are returning daily over the course of the month, which shows very strong user loyalty.
In short, the higher the percentage for these ratios, the more "sticky" your platform is. Sticky platforms keep users coming back again and again!
Interpreting the User Stickiness Chart
For example, in this chart:
DAW / WAW (17.81%): About 18% of weekly active wallets also engage daily. This suggests daily engagement is low, indicating the need for improvement.
WAW / MAW (34.01%): Approximately 34% of monthly active wallets are also active weekly. While this shows some consistency, there’s an opportunity to enhance weekly engagement through targeted campaigns.
DAW / MAW (6.06%): Only 6% of monthly active wallets are active daily, indicating that users may not find enough value to return daily.
By focusing on these metrics, you can create strategies to boost user stickiness and retention on your platform.
Measuring your campaigns' success is crucial for understanding their effectiveness. You can gain insights into how well your campaigns are performing by tracking key metrics such as wallet connections, transactions, and wallet spend. This data helps you assess their impact on your overall platform performance and identify areas for improvement.
Wallet Connections: Monitor the number of new wallets connecting as a result of your campaigns. A spike in new wallets signals that your outreach and messaging are effective.
Transactions: Analyze the volume and value of user transactions tied to your campaigns. High transaction numbers show successful conversion of interest into action.
Wallet Spend: Track how much users are spending via each campaign. Higher wallet spend indicates more revenue, helping you gauge ROI and optimize future efforts.
Use the dashboard to review visitor activity, session duration, and engagement while identifying top-performing campaigns to replicate their success. Leverage charts and graphs to track trends over time—if a campaign shows consistent growth in wallet connections and transactions, consider investing in similar strategies. Regularly analyzing your campaign performance allows you to refine your marketing approach and stay aligned with your business objectives.
Creating a Campaign
Creating a marketing campaign enables you to target specific audiences effectively and measure the success of your initiatives.
To create a new marketing campaign, follow these steps:
On the campaigns table, Click on Create New
Fill in the Required Fields:
Name: Provide a name for your campaign.
Source: Specify where the traffic is coming from (e.g., Twitter, Google).
Medium: Select how your campaign will reach users from the drop-down list (e.g., affiliate_social).
Content: Optionally, add additional information about the campaign.
Paid Advertising: If applicable, check the box to enter the Campaign Term and Campaign ID.
Once all fields are completed, click Create Campaign to set up your campaign.
Once the campaign is created, copy the UTM link and use it in your marketing efforts to effectively track performance.
Important Note:
Newly created campaigns will appear in the last few rows of the campaign table until any spend is tracked.
Importing campaigns allows you to utilize existing marketing efforts efficiently by consolidating them in one place. This process helps you save time and ensures that all your campaigns are organized and monitored effectively.
To import a campaign, follow these steps:
Navigate to the Campaigns Table and Click on the Discovered tab to view all available campaigns for import.
Review the list of campaigns and select the ones you wish to import.
Complete the fields as you did when creating a campaign, including Base URL, Name, Source, Medium, and Content.
Once you've filled out the required fields, click the Import button to complete the process.
After importing, return to the campaign table to confirm that your selected campaigns are now visible.
Managing your campaigns allows you to change their status or remove them altogether.
To manage your campaigns:
Select the checkbox next to the campaigns you wish to manage.
Update the status of the campaigns by choosing from options like Pause, Active, Stopped, Archive, or Delete.
You can also update the status of multiple campaigns at once by checking their boxes, allowing for more efficient monitoring and adjustments.
UTM (Urchin Tracking Module) tags are essential for accurately tracking the performance of your marketing campaigns. They provide valuable data that helps you understand where your traffic is coming from and your marketing efforts' effectiveness. Here's why UTM tags matter:
Accurate Tracking:
UTM tags allow you to specify the source, medium, and campaign name associated with each link you share. This ensures that you can accurately attribute wallet connections and transactions to specific campaigns when users click these links.
Critical Insights:
With proper tagging, you can gain critical insights about user behavior. For example, you may need to determine whether new wallet connections originated from an email campaign, social media post, or another source. This information is vital for understanding which channels are most effective in driving traffic.
Wallet Acquisition Analysis:
By using UTM tags, you can easily drill down to see which wallets have been acquired through a specific campaign. Suppose a campaign successfully generates a substantial amount of wallet activity. In that case, you can investigate at the wallet level to understand how much each acquired wallet spends and how they interact with your platform.
Optimizing Marketing Strategies:
By analyzing the data collected through UTM tags, you can identify successful campaigns and those that need improvement. This enables you to refine your marketing strategies, allocate resources effectively, and increase overall campaign performance.
Measuring ROI:
UTM tags provide the data necessary to measure your campaigns' ROI. By linking wallet spend and transactions to specific UTM-tagged links, you can assess the financial impact of your marketing efforts.
In summary, using UTM tags is crucial for clearly understanding your marketing performance. By implementing them in your campaigns, you ensure you have the insights to make informed decisions and drive your marketing strategies forward.
The Wallet Overview page helps you understand your users by tracking individual wallet activity and engagement on your platform. By drilling down into the details provided, you can uncover valuable insights about user behavior, spending habits, and session activity. This will help you identify your most valuable users and optimize your platform accordingly.
Lifetime Wallet Spend (USD): The total amount spent by the wallet since its first transaction on your platform. High spend indicates a valuable, engaged user, helping you prioritize retention efforts.
Wallet Spend (USD): Measures wallet activity within a specific period. Significant recent spending may indicate an active and engaged user.
Net Worth (USD): The total value of assets held by the wallet. While not directly tied to platform engagement, it shows financial strength and potential for high-value interactions.
Sessions: Tracks how often and for how long the wallet interacts with your platform. Multiple sessions suggest repeated engagement and opportunities for long-term retention.
Transactions: Shows the number of transactions made by the wallet, indicating the user’s financial engagement with your platform.
Age (Days): The age of the wallet since it was created or first appeared on the blockchain. This helps distinguish new from long-standing wallets.
Last Active/Last On Chain: Tracks the wallet’s last interaction with your platform or the blockchain, indicating recent user activity and when re-engagement efforts might be needed.
Digging into Wallet Insights:
Clicking on a wallet in the overview provides detailed insights:
Analyze Session Activity: See how users interact, including session duration, events, and transaction details. This reveals which features users engage with most and where they might lose interest.
Identify Drop-Off Points: Pinpoint where users leave, helping you identify and resolve pain points in the user journey.
Track Acquisition Channels: See how wallets arrived—through a campaign, referral, or direct visit—allowing you to focus on the acquisition channels that bring in the most engaged users.
Identify High-Value Users: Focus on wallets with high Lifetime Spend and Transaction Count to create personalized retention strategies.
Optimize User Experience: Use Session Data to understand user behavior and improve platform layout or flow to reduce drop-offs.
Refine Marketing Strategies: Track Acquisition Channels to see which campaigns bring in valuable users, and adjust marketing efforts accordingly.
Boost Retention: Analyze Sessions to identify barriers causing users to drop off, and address them to improve conversion and retention.
Re-Engage Inactive Users: Use the Last Active metric to target users who haven’t engaged recently with special offers or incentives.
Custom Funnels let you track user actions step by step, combining on-chain and front-end events to give you a clear picture of user behavior. From spotting drop-offs to improving onboarding and campaigns, funnels help you make smarter decisions and enhance your dApp experience. Here’s a simple workflow to help you get started.
This section focuses on how to conceptualize and construct a funnel specific to your dApp. You will learn how to identify the essential steps in your user journey, translate these steps into events in the funnel creation process, and apply filters to each event that pinpoint actions specific your needs.
Page Visits: Track users landing on your site or specific pages.
Page Clicks: Track interactions with specific elements on those pages.
Wallet Connections: Monitor users connecting their wallets to engage with your dApp.
Transactions: Follow completed transactions, swaps, or other on-chain activities.
Remember that the steps in the funnel are specific to the unique journeys your users take. The steps above are not a one-size fits all. For instance, wallet connections are not always a key step in everyones workflow. If your product does not explicitly require a user to connect their wallet, then it may be more valuable to track page or click events followed by a transaction.
Pro Tip: Think of your funnel as a map. Each step should represent a critical action in your dApp that helps you achieve your goals (e.g., onboarding, campaign success, or user engagement).
Navigate to the Funnels Tab in your 0xArc dashboard.
Click Create New Funnel.
Add a Name and Description for your funnel to keep it organized and easy to identify.
Here, the key steps identified above will be added to your funnel to define your user journey. Each step of the funnel should occur in sequence, ie. a previous step occurs at a time less than or equal to the next step. Select to add a condition to your step and choose from one of the provided event types. As you add steps, you will see a preview of your funnel results on the right hand-side.
Using Filters for Precision
Filters let you narrow down your analysis by focusing on the most relevant data. For each step in your funnel, you can select different filters to tailor your insights.
Instead of manually inputting values, you can search and select from a dropdown, ensuring consistency and accuracy.
These dropdowns are available for filters and step conditions, making it easier to refine user segments.
Example: When filtering a Transaction event, users can select from a predefined list of token types instead of manually entering contract addresses.
By setting up precise filters and leveraging dropdown selections, you can create a more accurate and efficient funnel analysis.
Add Filters for Precision
Each condition within a step can be further filtered by various properties. Add property filters to narrow down your analysis by focusing on the data most relevant to you. For instance:
Transactions can be filtered by ETH value sent or total wallet spend (estimated in USD).
Page Visits can be filtered by page-specific query parameters and by url host. The referred url, its host, and any associated query parameters can also be applied as filters.
Leverage the autofill in the drop-downs to help guide your selection, monitor the updates to the funnel preview, and continue to fine-tune your funnel to identify the user journey of interest.
A Conversion Window defines the maximum time a user has to complete a funnel, starting from their first step. This ensures only users who finish within the set timeframe (e.g., 1, 7, 30 days) are counted conversions.
It is important to remember that the data flowing through your funnel is bounded by the date range selected at the top of the page. When the conversion window is not set, any sequence of steps taken within this range will be counted toward a conversion. When the conversion window is set, it bounds the time a sequence of steps can occur within that range.
Why Use It?
Track time-sensitive goals (e.g., onboarding, campaigns).
Filter out users who take too long to convert.
Align reporting with business timelines (e.g., measuring 30-day ROI).
How It Works
The conversion window measures the time between when a user enters the funnel and when they complete the final step. If the user completes the funnel within the specified timeframe, their action is counted as a conversion. If they take longer than the conversion window, their action is not counted.
To better understand how the conversion window works, some scenarios are provided below.
Scenario 1: Time-Sensitive Campaign
Goal: Track users who sign up and upgrade within 7 days.
Conversion Window: 7 days.
Result: Only users who upgrade within 7 days of signing up are counted.
Scenario 2: Delayed Conversion
Goal: Include users who have had a delayed conversion.
June 1: User starts the funnel.
June 25: User completes it (24 days later).
July 1:
You analyze June data with a 30-day window.
Result: ✅ User converted within 30 days and is counted.
You analyze June data with a 7-day window.
Result: ❌ User did not convert within 7 days is not counted.
Scenario 3: Retroactive Counting
Goal: Exclude users who have a delayed conversion.
June 1: User starts the funnel.
July 10: User completes it (40 days later).
July 15:
You analyze June data without a conversion window.
Result: ❌ User did not convert within the specified date range.
You analyze June through July data with a 7 day conversion window.
Result: ❌ User did not convert within the 7 day window.
You analyze June through July with a 60 day conversion window.
Result: ✅ User converted within 60 days and is counted.
In summary, the conversion window ensures that only users who complete the funnel within the specified timeframe are counted. If no conversion window is set, the funnel will count all conversions within the selected date range, regardless of how long it took the user to complete the funnel.
Once all steps are configured:
Click Save Funnel.
Use the Preview Tool to ensure your funnel accurately reflects the user journey.
Once your funnel is set up, it’s essential to understand how well it performs and identify opportunities for improvement. The funnel view page is designed to give you a simple workflow to analyze and act on the results effectively.
At the top of the funnel view page, the funnel results will be displayed relevant to the global date range applied in the app. These results should help track the user progression from initial visits, through each step, and finally to complete conversion.
Each funnel step is represented as a bar relative to the total in the previous step. The bars are labelled with the total number of users that completed that step. Conversion rates, displayed as percents, are calculated relative to the previous step.
A summary of the condition and filters that define a step is provided to the right of the figure. Click within each step to show the relevant filters, if desired.
Look closely at conversion rates between steps to identify drop-off points. High drop-offs suggest friction or unclear instructions, while smooth transitions indicate a seamless user experience. For example, in the funnel presented above:
All is the number of users entering the funnel with the specified date range (114,491 users).
Session start: Nearly all users (114,044 users, or 99.959%) began a session. This indicates minimal drop-off at the initial stage, suggesting effective user acquisition or entry points.
Wallet connections: Only 41.647% of users (47,515 users) who started a session connected their wallet. This drop-off (~58%) highlights potential friction points.
Transactions: Just 14.616% of users who connected (16,675 users) proceeded to complete a transaction. This reflects another significant drop-off (~64.9%).
This data indicates that while user acquisition is strong, significant drop-offs occur at the wallet connection and transaction stages, highlighting areas where the user experience or instructions could be improved.
Use the weekly or monthly visualization chart to identify patterns and trends over time. These visual insights help you connect user behavior with specific events, campaigns, or platform updates. Sudden spikes in activity may indicate a successful marketing push, while drops could highlight areas requiring immediate attention or adjustments.
Drill down into the data table to compare user retention at each step and across time periods. This helps you identify drop-offs and opportunities for optimization.
The table shows how users progress through each funnel step, allowing you to spot patterns in retention and conversion rates.
By default, the funnel breakdown is presented as a completion-based funnel type by default with percents calculated relative to the previous step. The settings icon in the top-left of the table allows you to change the funnel type and the percent change calculation depending on your needs.
The percent change calculated relative to the previous step matches what is presented in the overall funnel results at the top of the page, where the percent is calculated relative to the previous step. The percents can also be calculated relevant to the total population that initially entered the funnel within that time interval, ie. the All value.
Funnel types are described in more detail in the next section.
When funnel data is broken down by time, the time-based entry and completion conditions for a user must be defined. A time interval is defined as one period of time within the global date range, in units of week or month. A time-based cohort refers to the actual group of users that flow through the funnel within that time interval. A user is considered a candidate for a time-based cohort depending on the rules set by the funnel type, which places importance on entry, completion, or both entry and completion within a specific time interval. When a user is a candidate for a time-based cohort we say they belong to the audience for that interval, specified by the “All” column in the table.
If a user is part of the audience for an interval and that user completes an intermediate step in the funnel they will be counted for that intermediate step. For which time interval the user should be considered fully converted, ie. completed all steps in the funnel, is dependent on the funnel type specified:
Completion-based – Default. Count if user completes in interval. Users are counted only if they convert within the selected time frame. If they complete any portion of the funnel in later weeks, they are not counted for the remaining steps for that interval. The user must be fully converted in the interval to be counted in the last step for that interval. The user can enter anytime in the previous intervals. Notice for this funnel type, as the intervals go forward in time, the "All" column for the intervals strictly increases since audiences from the previous intervals are included.
Entry-based – Count if user is active in interval. Users are only considered to be part of the audience for an interval if they are active within that interval. The user will be counted for any of the steps in the funnel even if they occurred in later intervals. This means that a user can be fully converted within their active interval even if they reached the last step in a later interval. If a user enters a funnel in one interval and completes in another interval, they will be counted for the interval in which they entered, ie. their journey is counted toward their entry interval.
Strict – Count if user enters and completes in interval. The user must enter and be fully converted within that interval to be counted. The user will only be counted in later intervals if they happen to complete the funnel again in another interval.
Since different funnel types track user progress differently, always ensure you're analyzing trends based on the correct funnel setting.
Example: A spike in "Step 1" during Week 52 might coincide with the launch of a marketing campaign that effectively drove traffic. However, a significant drop-off in subsequent weeks could suggest that users lost interest due to lack of follow-up communication, inadequate onboarding, or unmet expectations. Monitoring these patterns allows you to act quickly—either by replicating successful strategies or addressing weak points to re-engage users and improve retention.
💡Tip: If you're using an entry-based funnel, user progress may be distributed across multiple weeks, while in a completion-based funnel (default), each step represents users completing within the same period.
Example: If "Step 4" consistently shows low retention across weeks, it may indicate a friction point in the user journey, such as a complex process or unclear instructions. Optimizing this step—through simplified UX, clearer guidance, or added incentives—can help improve overall retention and conversion rates.
Funnel creation and analysis is only the first step; the real value comes from acting on the insights to enhance user engagement and optimize performance. Here's how you can use your findings effectively:
Optimize Drop-Off Points:
High drop-off rates between steps indicate friction in the user journey. Address these issues by simplifying the user interface, clarifying instructions, or reducing unnecessary steps. For example, if many users drop off at the "Wallet Connection" step, consider providing clearer guidance or improving compatibility with different wallets.
Replicate Successes:
Identify steps in the funnel where users move through seamlessly, indicating strong engagement or clarity. Apply the strategies from these successful steps to those with lower retention. For instance, if the "Transaction" step has a high conversion rate due to a streamlined checkout process, adapt similar approaches to earlier steps.
Refine Filters:
Use filters to target specific user segments for deeper insights. For example, focus on users making high-value transactions or first-time users to understand their unique behaviors and tailor improvements to their needs. This precision ensures your optimizations address the most impactful areas.
By turning insights into targeted actions, you can refine the user journey, reduce drop-offs, and enhance your dApp's overall experience. Regularly reviewing and acting on your funnel data ensures your strategies stay aligned with user needs and business goals.
This guide walks you through creating and setting up a new project in 0xArc.
If you want to track data for two different domains, creating separate projects ensures clean, organized, and structured tracking. Keeping projects distinct prevents data overlap, making it easier to analyze user behavior and campaign performance effectively.
Tracking multiple domains: If you need analytics for different websites or applications.
Managing different client projects: Ensure customer data is not intermingled.
Segmenting product versions: Useful for major updates or new iterations.
Follow the steps below to set up a new project.
Locate the Project Menu
In the upper-left corner of the screen, click the current project name.
Click the •• (Actions) menu next to the project name.
Start a New Project
Select Create New Project from the dropdown.
In the pop-up window:
Enter a Project Name (e.g., “ClientX_Staging”).
Click Get Started to create the project.
💡 Tip: Use a clear, descriptive name to distinguish projects!
After creating the project, follow the installation instructions provided in the documentation to integrate the SDK.
Once the SDK is installed, confirm that the integration is successful by checking the project settings.
By following these steps, you can ensure well-structured and effective data tracking across multiple projects within 0xArc. If you need additional help, reach out to our support team!
What is the difference between new, retained, churned, and resurrected wallets?
New Wallets: First-time users who connect a wallet.
Retained Wallets: Users who return to your platform regularly.
Churned Wallets: Users who have stopped engaging with your platform for the last 30 days.
Resurrected Wallets: Users who were inactive but have returned after a period of disengagement after 30 days.
How do I identify high-value users?
How can I reduce user churn?
How do I analyze retention heat map?
How do I create a campaign?
To create a campaign, follow these steps:
Click on Create New in the Campaigns Table.
Fill in the required fields, including Base URL, Name, Source, Medium, and Content.
If applicable, check the box for Paid Advertising to enter Campaign Term and Campaign ID.
Click Create Campaign to finalize your setup.
What are Daily Active Wallets, Weekly Active Wallets, and Monthly Active Wallets, and how are they measured?
Daily Active Wallets (DAW): This metric counts the number of unique wallets that interact with your platform each day. It measures short-term engagement and user activity. A higher DAW indicates strong daily user interaction.
Weekly Active Wallets (WAW): This metric tracks the number of unique wallets that engage with your platform over the span of a week. It's useful for assessing engagement trends and the performance of weekly campaigns. A higher WAW suggests users are consistently returning throughout the week.
Monthly Active Wallets (MAW): This metric measures the number of unique wallets active over a month. It provides a broader view of long-term engagement and helps assess overall user retention. A high MAW indicates that users find sufficient value to return regularly over a longer period.
What is Wallet Spend and Lifetime Wallet Spend?
Wallet Spend refers to the total amount spent in USD ($) by a wallet on your platform during a specific period. This includes all transactions, such as purchases, fees, or gas costs. Tracking wallet spend helps you understand user activity and engagement within that timeframe.
Lifetime Wallet Spend is the total amount a wallet has spent in USD ($) on your platform since their first transaction. It’s the cumulative value of all transactions over time, helping you identify your most valuable users and allowing you to target them with special offers or loyalty programs to maintain engagement.
What insights can I gain from the Multi-Chain Analytics feature?
Multi-Chain Analytics provides detailed insights into wallet behavior, transaction volumes, and user engagement across multiple blockchains. You can also see which blockchains are contributing the most to your platform’s performance and identify key opportunities for expansion and improvement.
How do I use Multi-Chain Analytics to monitor cross-chain activity?
Multi-Chain Analytics lets you view wallet connections, transactions, and user activity across different blockchains. You can set up workflows that include cross-chain comparisons, analyze how users behave on each chain, and identify which chains are driving the most engagement and value for your platform.
What if we want to track two different domains? Is it possible?
Base URL: Enter the URL for your campaign (e.g., ).
Start by identifying the key steps in your user journey and the order in which these steps occur. It can be helpful to think about how these steps align with . For example, the key steps could include:
If available, add steps that align with from your clickstream SDK to monitor specific actions that are unique to your needs, such as smart contract interactions or metadata about the version of your dApp.
📌 For detailed installation steps and a full configuration checklist, refer to the configuration guide:
Use the workflow to analyze wallets by transaction volume. High-value users typically show a pattern of repeated transactions and significant wallet spend. You can engage them through personalized offers or VIP programs.
Start by analyzing your Retention Metrics. If you see a significant drop-off, implement re-engagement campaigns, such as email reminders, incentives, or content aimed at reconnecting with churned users. Monitoring churned wallets in the section can also give you insights into user behavior.
To analyze retention metrics effectively, we recommend reviewing section. This guide provides detailed instructions on how to interpret the heatmap's layout, identify retention rates, examine specific cohorts, and spot significant drop-off points.
For detailed instructions, refer to the section in our guide.
For detailed insights and analysis, refer to thesection in our guide.
Yes! If you need to track multiple domains we recommend creating a separate project for each one. This ensures that data remains clean and prevents overlap between different domains. Keeping them as distinct projects makes it easier to analyze performance and user behavior specific to each domain. Need a step-by-step guide? .
