JSON holds objects inside objects inside arrays, to any depth. A spreadsheet holds rows and columns and nothing else. The conversion is not a format change, it is a restructuring, and every restructuring throws something away.
Converters that promise to do it automatically are choosing on your behalf. Knowing which choice they made is the difference between a useful file and thirty thousand columns.
First: what is a row?
Everything follows from this and it is the question people skip.
A response containing orders, each with several line items, can become one row per order or one row per line item. Both are correct. One is right for counting revenue by customer; the other is right for counting units by product.
Pick the level of the thing you are going to count. The rest of the document is then either columns on that row or repeated onto it.
Nested objects: dotted paths
An object inside an object flattens cleanly. A customer with an address containing a city becomes a column called customer.address.city.
This part is unambiguous and reversible. The only cost is column names that get long, and the mild nuisance that a key containing a dot becomes indistinguishable from a nesting level.
Arrays: the actual decision
Three strategies, and no converter can pick for you because the right answer depends on what you are going to do next.
Explode. One row per array item, with the parent's fields repeated on every row. An order with three line items becomes three rows carrying the same order number. This is what a database join produces and it is what pivot tables expect. The cost is that the file no longer has one row per order, so summing an order-level column triple-counts it.
Widen. One column per position: tags.0, tags.1, tags.2. Fine when every record has the same small number of items, and catastrophic otherwise — the column count is set by the single longest array in the document, and every other row leaves those columns empty.
Join. The whole array in one cell, separated by semicolons. Compact and readable by a person; no longer readable by a machine, and it breaks if any value contains the separator.
Explode when the items are the thing you care about. Join when the array is descriptive — tags, labels, categories. Widen almost never.
What a spreadsheet cannot represent
Types. CSV has none. A number, a string containing digits and a boolean all become text, and whatever opens the file guesses again from scratch — which is where leading zeros vanish and codes become dates.
Null against missing against empty. Three different states in JSON, one empty cell in a spreadsheet. If the difference matters, encode it deliberately.
Order and identity. Once an array is exploded, nothing in the file says those rows belonged to one record. Keeping the parent's identifier on every row is what lets anyone put it back.
Ragged objects
Real API responses rarely have identical keys on every record — optional fields are absent rather than null, and different record types carry different fields.
Flattening collects every distinct path across the whole document into the column set, so a handful of unusual records widens the file for everybody. A thousand records with eight fields each and one record with forty produces a forty-column file.
Worth checking the column count against the number of fields you expected before doing anything else with the result.
Doing it
A converter handles the mechanics once you have decided the row level and the array strategy. Formatting the JSON first is worth the extra step — you cannot choose a row level from a minified document, and reading the shape is most of the work.
Doing it in the browser matters more here than for most conversions, because the JSON that needs flattening is usually an API response containing customer records.
The short version
Decide what one row is before anything else. Nested objects become dotted columns and that part is safe. Arrays are the real decision: explode when the items matter, join when they are labels, and treat the CSV as an export rather than as the source.