How to Convert OLM to JSON

OLM files are ZIP archives full of Microsoft-specific XML, with one file per message, HTML that's often entity-encoded more than once, and addresses stored as attributes. Writing a parser is a weekend project you probably don't want. Converting to JSON gives you clean, structured data straight away.

What the JSON looks like

The output is one array, one object per email:

[
  {
    "folder": "Inbox/Clients",
    "subject": "Revised quote",
    "from": [{ "name": "Priya Shah", "address": "priya@example.com" }],
    "to": [{ "name": "Sam Lee", "address": "sam@example.com" }],
    "cc": [],
    "date": "2021-03-12T09:14:00.000Z",
    "text": "Hi Sam, attached is the revised quote…",
    "html": "<p>Hi Sam, attached is the revised quote…</p>",
    "attachments": [{ "name": "quote-v2.pdf", "type": "application/pdf", "size": 86016 }]
  }
]

• text is always filled in. If an email only has HTML, a clean text version is generated.
• html is null for plain-text emails.
• folder keeps the Outlook folder path, so you can group or filter by it.

How to convert OLM to JSON with ZapMorph

1. Open the converter

Go to the OLM to JSON converter.

2. Add the OLM

Drop in the .olm file. It's processed locally, which matters if the archive contains client or employee data.

3. Convert and download

Click Convert to JSON.

What people use it for

• E-discovery and audits: load every email into a script and filter by sender, date range or keyword.
• Analytics: count emails per correspondent or per month with a few lines of Python or JavaScript.
• Migration: push messages into a CRM, help desk or database through its API.
• AI and search: chunk the text field into a vector database for question-answering over an old mailbox.

A quick start in Python:

import json
from collections import Counter

emails = json.load(open("archive.json", encoding="utf-8"))
senders = Counter(e["from"][0]["address"] for e in emails if e["from"])
print(senders.most_common(10))

Tips

• Explore it first in the JSON viewer. Collapsible nodes make large files easy to skim.
• Need a spreadsheet instead? OLM to CSV gives one row per email.
• Big archive? Use a streaming parser (such as ijson in Python) rather than loading everything into memory at once.

Troubleshooting

"No emails were found." The export probably contains only contacts or calendar items. Re-export from Outlook for Mac with Mail ticked.

Some from arrays are empty. A few system messages and drafts have no sender recorded. Guard for it in your code, as the example above does.

Summary

The OLM to JSON converter skips the parsing work and gives you an Outlook for Mac archive as clean, structured JSON.