Slack messages. Microsoft Teams channels. Google Workspace files. Box folders. Zoom recordings. The average enterprise now runs on a sprawling network of collaboration and communication tools, each generating massive volumes of data every day. When a legal hold, regulatory inquiry, or internal investigation requires you to collect and review that data, the process can quickly become overwhelming.

This guide is for legal operations leaders, compliance officers, enterprise IT leaders, and heads of information governance who need a repeatable, defensible process for auditing data from collaboration apps. Whether you are responding to litigation, preparing for an audit, or building out a proactive data governance program, the steps below will help you move from chaos to clarity.

What Are Collaboration App Collections?

Collaboration app collections refer to the structured process of identifying, preserving, and extracting data from workplace collaboration and communication platforms, such as Slack, Microsoft Teams, Google Workspace, Zoom, and similar tools, for use in legal, compliance, or investigative matters. A collaboration data platform (or data collection platform) centralizes this process, enabling organizations to collect data across multiple sources in a consistent, auditable way.

According to a 2023 Gartner report on digital workplace trends, over 80% of enterprise communications now occur in digital collaboration tools rather than traditional email, significantly expanding the data landscape for legal and compliance teams. Yet most legacy eDiscovery workflows were built around email, leaving organizations poorly equipped to handle the volume and variety of collaboration data.

Before You Begin: Prerequisites

Before auditing data from collaboration apps, confirm you have the following in place:

• Admin-level access: You will need system administrator credentials or a delegated admin role for each platform you intend to collect from.
• Legal hold authority: Ensure legal holds or preservation notices have been issued before any collection begins, to avoid spoliation (the unintentional destruction of relevant data).
• A defined scope: Know which custodians (people), date ranges, platforms, and keywords are relevant to your matter.
• A data collection platform: A purpose-built tool, such as the Onna platform, that connects to your collaboration apps via API and collects data in a forensically sound manner.
• Chain of custody documentation: A process for logging every action taken on the data, from collection through review.

Step-by-Step: How to Audit Data from Collaboration Apps

Step 1: Define the Scope of the Audit

Start by documenting the parameters of your audit. Answer these questions before touching any data:

• Which collaboration platforms are in scope (e.g., Slack, Teams, Google Chat, Zoom)?
• Who are the relevant custodians, the individuals whose data you need to collect?
• What is the relevant date range?
• Are there specific keywords, topics, or channels that narrow the scope?

Modern scoping is not a guessing game. Review Onna's guidance on modern scoping for internal investigations in collaboration platforms to understand how to use platform-native search and metadata filtering to scope more precisely before collection begins.

Step 2: Issue and Confirm Legal Holds

Once scope is defined, issue legal hold notices to all relevant custodians. These notices instruct individuals to preserve potentially relevant data and stop any auto-deletion policies from removing it. Confirm that custodians have acknowledged the hold and that any automated deletion rules within your collaboration platforms have been suspended for those accounts.

Step 3: Map Your Data Sources

Not all collaboration data lives in one place. Conduct a data source inventory to identify every platform that might hold relevant information. This includes primary platforms (Slack, Teams), cloud storage (Google Drive, Box, SharePoint), video conferencing tools (Zoom), and any third-party integrations those platforms connect to.

Cross-team matters often involve multiple data sources managed by different business units. Onna's resource on data collection platform requirements for cross-team matters outlines what to look for in a platform that can handle this complexity without creating silos.

Step 4: Connect Your Collection Platform to Each App

Using a purpose-built collaboration data platform, authenticate and connect to each in-scope data source. The best platforms use native API connections, which collect data without disrupting active users, maintain original metadata (timestamps, sender information, thread context), and produce forensically sound outputs.

Avoid manual export methods (such as downloading files directly from a platform's admin console) wherever possible. Manual exports often strip metadata, create version control issues, and introduce gaps in the chain of custody.

See how the Onna eDiscovery collections workflow handles API-based collection from major collaboration platforms.

Step 5: Run the Collection and Validate Completeness

Execute the collection according to your defined scope. Once complete, validate the results:

• Confirm that the expected number of custodians, channels, and date ranges are represented.
• Cross-reference collected message counts against platform-native admin reports where available.
• Verify that attachments, reactions, edited messages, and deleted-but-preserved content have been captured.

A 2022 EDRM State of the Industry survey found that incomplete data collection is the most common source of defensibility challenges in eDiscovery matters. Validation at this stage prevents costly re-collections later.

Step 6: Process and Normalize the Data

Raw collaboration data is rarely in a format ready for review. Messages need to be threaded and contextualized, files need to be converted to reviewable formats, and data from different platforms needs to be normalized into a consistent structure. A data collection platform with built-in processing capabilities will handle this automatically, tagging metadata, deduplicating records, and organizing content for downstream review.

Step 7: Document and Audit Your Process

Every action taken on the data, from initial connection to final export, should be logged and documented. This audit trail is your defense if the collection methodology is ever challenged. Good documentation includes collection dates and times, the specific filters and parameters applied, the identity of the person who ran the collection, any errors or anomalies encountered, and the hash values of collected files (to prove data integrity).

Common Mistakes and How to Avoid Them

Scoping too broadly or too narrowly: Over-collecting wastes time and money in review. Under-collecting creates defensibility risk. Invest time in precise scoping before collection starts.

Relying on custodian self-collection: Asking employees to export and submit their own data introduces authenticity and completeness risks. Use a centralized platform instead.

Ignoring ephemeral and edited content: Collaboration platforms allow users to delete and edit messages. Make sure your collection method captures this content where legally required.

Missing third-party integrations: Data shared via bots, integrations, or external workspaces may not be captured in a standard export. Map all integrations during Step 3.

Skipping chain of custody documentation: Without a clear audit trail, the defensibility of your collection is at risk.

Best Practices for Ongoing Collaboration Data Governance

• Run quarterly data source inventories to identify new platforms adopted by business units.
• Establish a standing data governance policy that covers retention and legal hold procedures for all collaboration tools.
• Work with IT to ensure API access credentials for your collection platform are maintained and up to date.
• Train legal and compliance teams on the specific data structures of your primary collaboration tools (for example, how Slack threads differ from email chains).
• Use a single data collection platform across all matters to maintain process consistency and reduce per-matter setup time.

Audit Checklist

The Outcome: A Defensible, Repeatable Process

Auditing data from collaboration apps does not have to mean weeks of manual effort, inconsistent exports, or defensibility gaps. With a clear scope, the right data collection platform, and a documented process, legal and compliance teams can move faster, reduce risk, and spend less time managing data and more time resolving matters.

The organizations that handle collaboration app collections most effectively are those that treat it as an operational capability, not a one-off project. That means the right tools, trained people, and a process that scales as new platforms enter the enterprise environment.

Ready to bring order to your collaboration data? Onna helps legal, compliance, and IT teams collect, process, and review data from over 20 collaboration platforms, all in one place, with a full audit trail. Request a consultation with the Onna team to see how a unified collaboration data platform can simplify your next audit, investigation, or eDiscovery matter.