In this circle, after hanging around for a long time, I’ve discovered a pattern: users usually leave not because of some shocking technical failure. You hardly hear anyone complain about oracle delays being outrageous or data processing logic being completely broken.

The reality is much more subtle. When you open the app, the price is several dollars worse than other leading exchanges; collateral that looks very safe suddenly gets liquidated after a night’s sleep; sports prediction markets have already ended for half an hour, but the results are still stuck and no conclusion is reached.

Users won’t discuss technical details with you. They just silently think that this thing is unreliable, and then delete it.

This is the most frightening — no complaints, no feedback, only silent attrition.

Data is such a thing. It’s invisible and intangible most of the time. But as soon as there’s a slight deviation, trust can shatter like glass in an instant. Many products today stack features very complexly. A small error from a single data source can spread like ripples, fragmenting the entire experience. Users feel that this app is becoming increasingly unreliable.

So where is the key problem? It lies in balancing data authenticity and real-time performance.

That’s why some products are dedicated to doing this. Their core idea is straightforward: first process and verify real-world information off-chain locally, then prove it in a verifiable way on-chain, so that smart contracts can use it with confidence. The benefit of this approach is that it not only avoids those fatal big issues but also eliminates the small discrepancies that accumulate over time — the head-scratching details of user experience.

In actual operation, an interesting phenomenon is that users rarely run away after a major failure. More often, they experience several small issues and then become completely disappointed in the product. The behind-the-scenes culprit of these small problems is often data quality.

Some teams put a lot of effort into front-end experience — making wallets smarter, reducing prompts, lowering Gas costs, improving authorization flows. These optimizations do help, but with one premise: the backend data must be reliable.

Otherwise, all these improvements are like decorating a bucket with a hole in the bottom — it looks refined, but using it still leads to disappointment.