Hook
Your Domo dashboards surface the insight — but someone still has to copy-paste it into an email, chase down an approval, and manually trigger the next step. Domo Workflows is built to close that gap.
Why It Matters
Without automation, data-driven processes stall at the handoff: a report flags an issue, but acting on it still requires human coordination through email threads, spreadsheets, and Slack messages. Workflows embeds that coordination logic directly into Domo, so your data can trigger real actions — not just alerts. For teams already living in Domo, this means you can build end-to-end processes without stitching together external tools like Zapier or Make. The question shifts from "who do I email?" to "what should happen automatically?"
What You'll Learn
- Understand where Domo Workflows sits within the broader Domo platform and when to reach for it versus other automation options
- See a real campaign approval process built with user-in-the-loop steps using Domo's email and forms integration
- Explore how Workflows can serve as a low-latency automation toolkit for time-sensitive data operations
- Navigate the UI concepts that trip up new users — including what to click first and how data passes between tasks
- Identify quick wins for your own organization through a lightning-round of practical use cases
From Approval Bottlenecks to Automated Pipelines
The session opens with a candid acknowledgment: the Workflows UI isn't immediately intuitive, especially if you're coming from tools like Zapier. The first 10 clicks are the steepest part of the learning curve — understanding the canvas, how tasks connect, and how data flows between steps. Once that mental model clicks, the rest follows familiar integration logic.
Dan Hendriksen walks through a campaign approval workflow that replaces a back-and-forth email chain with a structured, trackable process. A Domo form captures the approval request, an automated email routes it to the right stakeholder, and the workflow pauses — waiting for a human decision before proceeding. This "user in the loop" pattern is one of the most practical entry points for analyst teams: it keeps humans in control while eliminating the coordination overhead.
Nate Bear takes a different angle, using Workflows as a low-latency automation layer — triggering downstream processes the moment data conditions are met, rather than waiting for a scheduled pipeline or manual intervention. This is particularly valuable for operational use cases where minutes matter: inventory alerts, SLA breaches, or time-sensitive reporting handoffs.
A recurring theme in the community discussion: teams already comfortable with iPaaS tools have the right mental model, they just need to map it onto Domo's interface. If you've built a flow in Make or Zapier before, the concepts transfer — triggers, actions, conditional branching, and data mapping are all present. The difference is that your Domo datasets and cards are first-class objects in the workflow, no API wrangling required.
The best starting point for most teams is a process you already run manually — a recurring approval, a data-triggered notification, a weekly report handoff — and rebuilding it inside Workflows step by step.
