You know that feeling when you look at your bank statement and see twenty different subscription charges? Netflix here, Spotify there, three different cloud services, that productivity app you swore you'd use... It's a modern financial headache. But here's the thing—seeing the numbers in a list doesn't really help. Our brains aren't wired to process monthly costs as abstract digits. We need to see the impact.
That's exactly why the developer community went wild over a simple subscription cost visualizer shared on r/webdev last week. The original tool used a treemap layout to make subscription spending visually intuitive. But the real magic happened in the comments. Developers asked for more layouts. They wanted to handle multiple currencies. They needed something that would make the data "click" for different types of thinkers.
And the creator listened. The updated version now includes three distinct visualization layouts and live multi-currency support—all while keeping everything 100% local. No data sent to servers. No privacy concerns. Just pure, useful visualization.
In this guide, we're going to break down exactly how you can build something similar. We'll explore why different visualization layouts matter, how to handle real-time currency conversion without compromising privacy, and what makes this approach so effective for personal finance tools in 2025. Whether you're building this for yourself or as a portfolio piece, you'll walk away with practical, implementable strategies.
Why Visualization Beats Spreadsheets for Subscription Tracking
Let's be honest—most of us have tried tracking subscriptions in a spreadsheet. You create columns for service, cost, billing cycle, cancellation URL... and then you never look at it again. Why? Because spreadsheets don't trigger the right cognitive responses. They're analytical, not intuitive.
Visualization works differently. When you see a large rectangle representing your $15/month streaming service next to a tiny square for your $2/month RSS reader, something clicks. The relative size communicates importance immediately. You don't need to do mental math. You just see where your money's going.
This isn't just speculation. Research in data visualization consistently shows that humans process visual information 60,000 times faster than text. For financial decisions—especially recurring ones we make on autopilot—that speed matters. A good visualization can help someone immediately identify "subscription creep," where small services add up to significant monthly expenses.
The original Reddit post proved this concept beautifully. Users reported discovering subscriptions they'd forgotten about entirely. Others realized they were paying for overlapping services. One commenter mentioned finding three different note-taking apps in their visualization—all charging monthly fees for essentially the same functionality.
The Three Layout Philosophy: Treemap, Bubbles, and Beeswarm
The updated visualizer offers three distinct layout options, and this choice matters more than you might think. Different people process visual information differently. Some prefer strict organization. Others respond better to organic shapes. Let's break down each approach.
Treemap Layout: The Classic Organizer
The original treemap approach uses nested rectangles sized proportionally to subscription costs. It's efficient with space and creates a clear hierarchy. Each service gets a rectangle, with the area representing the monthly cost. Color can represent additional dimensions—maybe category (entertainment, productivity, utilities) or billing frequency.
Treemaps work particularly well when you have a wide range of values. Your $200/month cloud hosting service will naturally dominate the visualization compared to your $5/month weather app. The spatial relationship is immediately apparent.
Implementation-wise, treemaps are relatively straightforward with libraries like D3.js. The key challenge is ensuring readability—you need to handle labels carefully, especially for small rectangles. The original implementation used interactive tooltips that appear on hover, which solves the labeling problem without cluttering the visual.
Bubble Layout: The Organic Approach
p>Bubble charts (or circle packing) offer a more organic, less rigid visualization. Instead of rectangles fitting perfectly together, you get circles that may have spaces between them. This creates a different kind of visual weight—the eye naturally goes to the largest circles first.Some users find bubble layouts more approachable. The shapes feel less technical, more friendly. There's psychological research suggesting people associate circles with unity and harmony, which might make confronting your subscription spending feel less stressful.
From a technical perspective, bubble layouts require more sophisticated packing algorithms. You need to calculate positions that minimize overlap while maintaining the proportional sizing. D3.js has built-in circle packing functions that handle most of this complexity, though you'll want to add collision detection to prevent labels from overlapping.
Beeswarm Layout: The Pattern Spotter
This is the most interesting addition from a data visualization perspective. Beeswarm plots position items along an axis (usually cost) while avoiding overlap. They're fantastic for spotting clusters and outliers.
Imagine all your subscriptions arranged along a horizontal line by monthly cost. You'd immediately see if most of your services cluster in the $10-$15 range, with a few expensive outliers. This layout reveals patterns that might be hidden in other visualizations—like realizing you have five different services all costing exactly $9.99/month.
Beeswarm plots are particularly useful for subscription analysis because they help identify "tier clustering." Many SaaS products price at specific tiers ($9, $19, $29, etc.), and a beeswarm layout makes these pricing patterns visually obvious. You might discover you're paying for multiple services at the "pro" tier when you only need one.
Implementing Multi-Currency Support with Live Exchange Rates
Here's where things get really practical for 2025. More developers than ever work internationally or subscribe to services priced in different currencies. The original Reddit discussion highlighted this as a major pain point—users wanted to visualize their USD, EUR, and JPY subscriptions in a single coherent view.
The updated visualizer handles this elegantly. Each subscription can have its own currency, with live exchange rates pulling from a public API. But here's the crucial part: everything happens locally. The exchange rates fetch once (or cache with reasonable expiration), then all calculations happen in the browser.
Choosing an Exchange Rate API
You have several options here, each with trade-offs. Free tiers of services like ExchangeRate-API or Open Exchange Rates typically offer enough requests for personal use. The key considerations are reliability, update frequency, and whether you need historical rates (for analyzing past spending).
For a purely local application, you'll want to implement smart caching. Store exchange rates in localStorage with a timestamp, and only fetch new rates when the cached ones are older than, say, 24 hours. This minimizes API calls while keeping data reasonably fresh.
One clever approach mentioned in the Reddit comments: use the browser's built-in Intl API for currency formatting once you have the converted amounts. This handles locale-specific formatting automatically—commas vs. periods, currency symbol placement, etc.
Handling Currency Conversion in Visualizations
This is trickier than it sounds. When you convert everything to a single base currency for visualization, you need to decide when to convert. Do you convert at the current rate for future projections? Do you use historical rates for past months? The visualizer takes the practical approach: everything converts to your primary currency at current rates for a "right now" snapshot.
For developers building similar tools, consider adding a toggle. Users might want to see their spending in their local currency for budgeting purposes, but also in USD (for example) to compare against typical SaaS pricing. The visualization should update dynamically when the base currency changes.
Keeping It 100% Local: Privacy and Performance Benefits
This might be the most important design decision. The visualizer runs entirely in the browser—no server-side processing, no data sent anywhere. In 2025, with increasing concerns about data privacy and surveillance capitalism, this approach resonates deeply with users.
Fintech applications typically want your data. They analyze it, monetize it, sometimes sell it. A local-first approach says: "Your financial data belongs on your device." This builds immediate trust. Users know they can input their real subscription costs without worrying about where that information might end up.
Technically, this means using localStorage or IndexedDB to persist data between sessions. The original implementation uses a simple JSON structure stored in localStorage. Each subscription includes name, cost, currency, category, and billing cycle. The visualization reads this data, processes it, and renders—all client-side.
Performance benefits are significant too. Once loaded, the application responds instantly. Filtering between visualization layouts? That's just changing some D3.js parameters. Switching base currency? A quick recalculation and re-render. No network requests, no waiting for servers.
If you're building something similar, consider adding export/import functionality. Let users download their data as JSON for backup or to move between devices. This maintains the local-first philosophy while providing data portability.
Technical Implementation: Building Your Own Version
Ready to build your own subscription visualizer? Here's a practical roadmap based on what worked for the Reddit project and what I've learned building similar tools.
Start with the data structure. Keep it simple:
{
"subscriptions": [
{
"id": "unique_id",
"name": "Netflix",
"cost": 15.99,
"currency": "USD",
"category": "entertainment",
"billingCycle": "monthly",
"color": "#E50914"
}
],
"settings": {
"baseCurrency": "USD",
"preferredLayout": "treemap"
}
}For the visualization layer, D3.js remains the gold standard in 2025, though newer libraries like Observable Plot are worth considering for simpler cases. D3 gives you complete control, which you'll need for implementing all three layout types.
The treemap uses d3.treemap() with a hierarchy generated from your subscription data. The bubble layout typically uses d3.pack() with similar hierarchical data. The beeswarm is trickier—you'll need d3.forceSimulation() with custom forces to position nodes along the x-axis by cost while preventing overlap.
For the UI, consider a minimalist approach. The original visualizer uses a clean sidebar for adding/editing subscriptions, with the main canvas for visualization. Layout toggles are simple buttons that switch between D3 layouts. Currency selection is a dropdown that triggers recalculation.
Common Challenges and Solutions
Building this seems straightforward until you hit specific edge cases. Here are the problems developers typically encounter, based on the Reddit discussion and my own experience.
Handling Annual vs. Monthly Billing
This comes up immediately. Some subscriptions bill monthly, others annually. For visualization, you need everything in comparable units. The simplest approach: convert everything to monthly equivalent. An annual $120 subscription becomes $10/month in the visualization.
But what about quarterly billing? Or biennial? Create a standardized conversion function that handles any billing cycle. Store the original amount and cycle, then calculate monthly equivalent for visualization. This preserves the original data while enabling apples-to-apples comparison.
Dealing with Free Trials and Variable Costs
Some subscriptions have free tiers. Others have usage-based pricing. The visualizer needs to handle these gracefully.
For free tiers, you might still want to include them in the visualization—perhaps as very small, lightly colored elements. They're still part of your subscription portfolio, even if they don't cost money today.
Variable costs are trickier. If you have a cloud service that costs $50-$200/month depending on usage, you could visualize the average, the maximum, or a range. The Reddit discussion suggested using gradient fills or error bars to represent uncertainty. Personally, I'd visualize the maximum cost—it's the conservative approach for budgeting.
Managing State Across Layout Changes
When users switch between treemap, bubble, and beeswarm layouts, you want the transition to feel smooth. The subscriptions shouldn't jump randomly. D3's update pattern is essential here.
Use key functions to bind data to DOM elements consistently. When changing layouts, update the positioning attributes with transitions. This creates an animated morphing effect that helps users track individual subscriptions across layout changes.
Beyond Visualization: Adding Practical Features
The visualization is powerful, but it's just the beginning. Several Reddit commenters suggested features that would make the tool even more useful.
First, categorization and filtering. Let users group subscriptions by type (entertainment, productivity, utilities) and filter the visualization to show only specific categories. This helps answer questions like "How much am I spending just on streaming services?"
Second, time-based analysis. Show how subscription spending has changed over the past year. A simple line chart alongside the main visualization can reveal trends—are you adding more subscriptions each month? Have you successfully reduced costs?
Third, integration possibilities. While the local-first approach is core to the philosophy, some users might want to pull subscription data automatically. Browser extensions could detect subscription charges on bank statement PDFs. With user permission, you could even connect to financial APIs like Plaid (though this moves away from the 100% local model).
If you're not comfortable building these integrations yourself, you could hire a specialized developer on Fiverr to implement specific features. The freelance marketplace has experts in both D3.js visualization and financial API integration who could help extend your project.
Why This Matters for Developers in 2025
Building tools like this subscription visualizer isn't just about solving a personal problem. It's about practicing skills that matter more every year: data visualization, local-first architecture, and user-centric design.
Data visualization skills are increasingly valuable as more applications need to present complex information clearly. Whether you're building dashboard interfaces, analytics tools, or even game UIs, understanding how to visualize data effectively sets you apart.
Local-first architecture represents a growing trend in 2025. As privacy concerns increase and devices become more powerful, running applications locally makes sense for many use cases. This project gives you hands-on experience with localStorage, client-side processing, and offline functionality.
Finally, there's the portfolio value. A well-executed subscription visualizer demonstrates multiple skills: clean UI design, interactive visualization, currency handling, and thoughtful user experience. It's the kind of project that sparks conversation in interviews—because almost everyone can relate to the problem it solves.
If you want to dive deeper into data visualization techniques, consider picking up Interactive Data Visualization for the Web. It's been updated for modern practices and covers D3.js in depth.
Getting Started with Your Own Implementation
The beauty of this project is that you can start simple and expand. Begin with a single visualization type (treemap is probably easiest). Get the basic rectangle sizing working with static data. Then add currency support. Then implement additional layouts.
Use the original Reddit project as inspiration, not prescription. Think about what you would find useful. Maybe you want to visualize not just cost, but also usage—how much you actually use each service relative to its cost. Maybe you want to integrate cancellation links directly into the visualization. Maybe you want to add collaborative features for household budgeting.
The core insight remains: visualization makes subscription spending tangible in ways spreadsheets never will. By building this tool, you're not just creating another app—you're creating a lens that helps people see their financial reality more clearly. And in 2025, with subscription models dominating software, services, and even physical products, that clarity is more valuable than ever.
Start with a simple version this weekend. Input your own subscriptions. See what you discover. I guarantee you'll find at least one "Wait, I'm still paying for that?" moment. And that moment—that sudden clarity—is exactly why tools like this matter.
