Most technical writing about data formats reads like it was optimized for search engines rather than humans. Let's skip that and talk about what actually matters when you're choosing between CSV and JSON.
Both are plain text formats. And…that's about where the similarity ends.
CSV (short for "Comma-Separated Values") organizes data in rows and columns, basically a spreadsheet saved as text. JSON (short for "JavaScript Object Notation") uses key-value pairs that can nest inside each other, creating structures that look more like trees than tables.
The choice between them shapes how your data moves, what you can express, and where you'll hit friction.
Structure: tables vs trees
CSV works beautifully when your data is naturally flat, like customer lists with consistent attributes or daily metrics where each row follows the same pattern. The data is fast to parse, easy to scan, compatible with nearly everything.
JSON handles complexity without breaking, like a customer with multiple email addresses, an account hierarchy with nested teams, or event sequences with varying properties. JSON lets you express these relationships directly.
CSV on the other hand forces you to flatten them, which usually means duplicating rows or creating artificial column schemes that obscure what the data actually means.
This matters more as data gets richer. Modern GTM systems don't just track individual attributes. They also map relationships, work histories, and company data. Flattening that into tables loses information or creates maintenance headaches.
Performance and the hidden costs
CSV parses faster in most cases. It's a split-on-delimiter operation, so it's lightweight and predictable. JSON requires more processing, especially when structures get deep.
But raw parsing speed is just part of it. CSV brittleness shows up over time. When you add a new field, you're updating header logic across your pipeline. Optional attributes force decisions between empty columns or null conventions. Merging data from different sources means reconciling schema mismatches manually.