This is part 2 in my series on the trading card data problem. If you haven't read The Data Problem Every Card App Faces, start there for the full context.

Tom discovered a new portfolio tracking app with features he's been wanting for years. His old app even has an export function—but the new app can't import the data. Different field names, different set numbering, different card identification systems. The export file might as well be written in a foreign language. Tom is still using his old app.

This is the hidden cost of trading card data silos: it's not just that data is locked away, it's that even when platforms try to be helpful, the lack of standards makes data mobility nearly impossible.

The User Tax

Every trading card collector pays an invisible tax: they can't access the full value of the collective knowledge that exists across platforms.

Imagine you're researching a 1986 Fleer Michael Jordan rookie card. Platform A has the most accurate recent sales data. Platform B has the best condition assessment guides. Platform C has comprehensive authentication tips. Platform D tracks the card's long-term price trends. Each platform holds a piece of the puzzle.

The dedicated collector will do what you'd expect: manually visit each platform, extract the relevant information, maybe create a spreadsheet to compare the data. But this requires knowing all these platforms exist, paying for multiple subscriptions, and spending hours on research that should take minutes. Most collectors either don't have the time for this manual aggregation, or they don't even know about all the specialized platforms that could help them.

The expertise exists. The data exists. The insights exist. But accessing the full picture requires manual detective work that turns what should be a quick lookup into a research project.

The Ecosystem Tax

The real cost isn't just the manual research burden on collectors—it's the innovation that never happens because most trading card data can't flow between applications.

Consider what's possible when data IS accessible. eBay's sales data powers applications like CardLadder, which provides market analysis and price tracking that eBay itself doesn't offer. Developers can build specialized tools—investment trackers, market prediction services, portfolio optimizers—because they have access to the underlying transaction data through APIs.

But eBay is the exception, not the rule. Most trading card platforms keep their data locked away. One platform has the best card identification system, another has comprehensive set checklists, a third has detailed condition assessments. Each could enhance the others, but they exist in isolation. Developers who want to build the next CardLadder equivalent using card database information, or create collection management tools that integrate with grading services, hit a wall: the data simply isn't accessible.

This isn't just inefficient—it's actively holding back innovation. How many brilliant applications never get built because the barrier to entry is reconstructing an entire data ecosystem from scratch?

The Developer Dilemma

For every trading card app that makes it to market, there are probably three that never launch because the developers gave up during the data collection phase.

Building a trading card application should be about solving user problems—better portfolio tracking, smarter collecting insights, innovative trading mechanisms. Instead, developers find themselves becoming reluctant data archaeologists, spending months cataloguing card sets and building databases before they can write a single line of user-facing code.

The math is brutal. A comprehensive sports card database might include 50,000+ individual cards across hundreds of sets. Even with efficient data entry processes, that's months of work before you have enough coverage to be useful. For a solo developer or small team, that timeline can kill a project before it starts.

And the data work never really ends. New sets release constantly, errors need correction, variations get discovered. Take something like 2024 Panini Prizm Football. The base set alone has dozens of parallel variations (Silver, Gold, Red, Blue, etc.), each with different print runs and values. What started as a three-month data project becomes an ongoing maintenance burden that competes with actual feature development. How many innovative features never get built because the team is too busy cataloguing Prizm parallels?

The Vicious Cycle

These costs don't exist in isolation—they compound and reinforce each other in a vicious cycle that holds back the entire ecosystem.

Fewer developers attempt trading card apps because the data barrier is too high. With fewer apps competing, existing platforms have less pressure to innovate or improve user experience. Users get stuck with limited options, which reduces demand for new solutions. This makes it even harder to justify building new apps, since the market appears smaller than it actually is.

Meanwhile, the data silos get deeper. Each platform that succeeds has more incentive to keep their data locked away as a competitive moat. New developers who do attempt to enter the market find the barriers even higher, because they're not just competing on features—they're competing against years of accumulated data advantage.

The real tragedy is that this cycle prevents us from discovering what trading card applications could actually become. We're not just missing incremental improvements—we're missing entire categories of innovation that could transform how people collect, trade, and interact with cards.

Coming Up

Next week, we'll dive deeper into the specific innovations that never see the light of day because of these data barriers. What kinds of applications could exist if developers could focus on solving user problems instead of rebuilding the same data infrastructure? The possibilities might surprise you.

Have you experienced the switching tax as a collector? Or hit the data barrier as a developer? Share your story in the comments below.