Short answer
CSV fits tables with stable columns; JSON supports explicitly structured objects and lists. Choose a format the destination accepts and define types, missing values, encoding and identifiers. Preserve phone numbers as text and test a round trip with fictional data before importing actual contacts.
Key verification: Read the transformed sample again and compare identifiers, phones, characters, missing fields and lists with the original.
Sources and limitationsA file extension does not guarantee another application understands its contents. CSV and JSON can represent a contact but require different agreements about columns, types and structure. Choose according to the destination contract rather than apparent modernity.
What differs between CSV and JSON
CSV organises rows and fields. RFC 4180 documents a common comma-based format with quoting rules; confirm the actual variant. JSON supports objects, arrays and typed values. The MDN JSON reference explains its syntax.
CSV does not itself declare each column's type. JSON distinguishes numbers, strings, booleans and null, but does not define a key's business meaning. Both require a specification.
The same fictional sample in both formats
contact_id,name,phone
demo-01,Demo,+34900000000{"contact_id":"demo-01","name":"Demo","phone":"+34900000000"}Identifiers and values are fictional; do not call the phone number. JSON represents it as a string. For CSV, require the reader to treat that column as text. A spreadsheet altering the initial sign or zeros can damage data before integration receives it.
Original selection matrix
| Need | CSV | JSON |
|---|---|---|
| Stable reviewable table | Simple row reading | Possible with another viewer |
| Several phones per contact | Needs a convention or related table | Can use an array |
| Missing value and empty text | Needs an agreed rule | Can distinguish null and empty string |
| Existing destination | Only if it accepts that contract | Only if it accepts that contract |
JSON supporting arrays does not mean the receiving API accepts one. Confirm names, mandatory fields and additional-field behaviour. Flattening a list may lose relationships even without an error.
Minimum contract before transformation
Document encoding, delimiter where applicable, field names, types, stable identifier and date format. Decide missing versus empty meaning: leaving unchanged and clearing a value are different actions depending on the destination.
Include accented characters, commas in names, an empty phone and multiple related values in samples. Use format readers and generators rather than manual character replacement. Do not execute field contents as instructions.
How to check in Make
Make documents data structures for parsing and serialising formats. A sample-generated structure requires review: one record without a phone does not establish that all lack it, and one tag does not describe a complete list.
Prepare a test scenario without production delivery. Read the sample, transform it, generate output and read it again. Compare values and contact counts, including edge cases. If data disappears, correct the contract or mapping before enabling delivery.
Make may fit transformations between applications; choosing a format does not require it. CallsIQ has not executed this account scenario. The examples and matrix are reproducible reading resources rather than results from an actual import.
Sources and limitations
Documentary review: . Content type: Documentation-based guide with original resource.
Sources describe terms and capabilities stated by their owners. Proposed protocols and fictional examples do not establish product tests performed by CallsIQ.
- RFC 4180www.rfc-editor.org
- MDN JSON referencedeveloper.mozilla.org
- data structures for parsing and serialising formatshelp.make.com
Check current terms
Consider these options if they solve the problem described. Confirm features, limits and availability in your country.
MakeAffiliate linkThe labelled commercial links may earn CallsIQ a commission or referral reward. Our commercial policy.
Official sources, explained calculations and clearly labelled examples. Read about our methodology and use of AI in writing.