ToolStack
Migration Guide

Migrating from Loom to Datadog

Loom scores 4.7/5 on G2 — 0.2 points ahead of Datadog (4.5/5). If you're making the switch, here's how to migrate your team from Loom to Datadog step by step.

At a Glance

Loom
4.7/5 · 2,600 G2 reviews
  • Fastest way to communicate complex ideas asynchronously — record screen + camera in seconds with zero setup
  • Loom AI automatically generates titles, summaries, chapters, and action items, saving significant post-recording effort
  • Extremely low learning curve — even non-technical stakeholders adopt it instantly, making it ideal for cross-functional PM communication
Datadog
4.5/5 · 600 G2 reviews
  • Unified observability platform — infrastructure monitoring, APM, logs, RUM, synthetics, and security all in one place, reducing tool sprawl
  • 750+ out-of-the-box integrations covering virtually every cloud service, database, framework, and DevOps tool in modern stacks
  • Watchdog AI automatically detects anomalies and correlates issues across the entire stack, significantly reducing mean time to resolution
Full side-by-side comparison: Loom vs Datadog

You gain with Datadog

  • +workflow automations
  • +custom fields

Migration Steps

1

Audit and export your current workspace

Before touching Datadog, document what lives in Loom: projects and tasks, custom fields, automations, integrations, and team permissions. Export a full CSV backup — most tools support this from Settings → Export. Pay particular attention to any workflow automations that your team relies on daily.

2

Set up your Datadog workspace

Create your Datadog workspace and replicate your project structure using tasks and projects. Start with the free tier — it covers the core workflow before you commit to a paid plan. Run with a single pilot team before migrating everyone.

3

Map your workflow equivalents

Find the closest Datadog equivalent for each Loom feature your team relies on. projects and tasks in Loom maps to tasks and projects in Datadog. Datadog supports custom fields — recreate your Loom field schema here first. Prioritise the critical path: task creation, status tracking, and assignment.

4

Import your data

Datadog supports CSV import for tasks and projects and has 20+ native integrations. After importing, rebuild your key automations — Datadog's automation engine can replicate most rules you had in Loom. Start with your most active project rather than importing everything at once.

5

Onboard your team

Run a 30-minute walkthrough covering the daily workflow: how to create tasks and projects, update status, and find your board. Datadog has a steeper learning curve. Budget 2–3 weeks for full adoption and schedule follow-up sessions after week one.

6

Run Loom in parallel for two weeks

Keep Loom read-only while your team works primarily in Datadog. This reduces risk and lets people reference historical context — old decisions, archived tickets, past sprint data — without slowing the migration. After two weeks with no new work going into Loom, archive the workspace and make Datadog the official home.

Ready to switch?

Read the full Datadog review for pricing, integrations, and team fit details.

Read Datadog Review →Compare Loom vs Datadog