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When I joined PayPal in 2014, I was new to the payments industry—but not new to analytics. I had been working in data analytics for over a decade, so when I was asked to analyze approval rate trends and transaction declines in Brazil, I expected it to be a fairly straightforward task.

After all, most analytics work boils down to three things:

• Business understanding
• Data understanding
• Basic programming skills

How hard could it be? All I needed to do was answer two questions:

1. Who declines a card-funded transaction?
2. Why do they decline it?

But answering even the first question—who—turned out to be more complicated than I imagined.

I spoke with veteran analytics colleagues, product managers, and business leads. They walked me through the transaction flow: the transaction goes from the merchant to the authorizer, to the card network, and finally to the issuer. Initially, I assumed that each player in this chain might influence the approval or decline decision. But after much digging, I learned that in reality, it is the card issuer who makes the final approval or decline decision—not the other players.

Today, this is fairly well understood—thanks to the wealth of LinkedIn articles and PSP educational content. But in 2014, such information was much harder to find.

In the specific case of Brazil, I eventually uncovered that the fluctuations in approval rates were not being driven by players in the payments ecosystem at all. Instead, they were caused by merchant-side factors—such as merchant churn, acquisition strategies, and changes in the merchant landscape.

Later that year, I attended Glenbrook Partners’ Payments 101 training, a three-day deep dive into the payments ecosystem. That experience dramatically improved my understanding of how the ecosystem really works and made me a far more effective payments analyst.

The biggest lesson? To be a great payments analyst, it takes more than data and programming skills—you need a deep understanding of the payments industry itself: the ecosystem, the players, and the dynamics that influence data trends.

What has your payments analytics journey been like? I would love to hear your experience!