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Product workflows

From marketing data to reviewed action.

Follow supported evidence through Growomo’s three engines, an explicit human review, and a documented next step. Start with the marketing job your team needs to solve now.

The operating spine

One connected path, with review built in.

Each use case begins at a different point, but the operating boundary stays visible.

  1. SourcesAuthorized provider evidence
  2. Marketing Data HubSource and sync context
  3. AI Decision EngineRationale and constraints
  4. Human reviewExplicit decision boundary
  5. Experiment EngineHypothesis and review record
  6. Measure and learnDocumented follow-up

Scenario explorer

Inspect where the evidence, review and next step meet.

Choose a marketing job, then inspect each stage. Selection stays local to this page.

Choose a scenario

AI Decision Engine

Choose the next marketing action with reviewed evidence.

Turn competing observations into a reviewable backlog with rationale and approval status.

Demo data — not customer results.
reviewHuman review

Add business context that data cannot supply

Inputs
Freshness checks · Channel anomalies · Recommendation context · Business constraints
Decision output
Approved, rejected or experiment backlog
Approval boundary
A responsible marketer adds business context and explicitly approves, rejects or converts each recommendation into an experiment.
Open this use case

Prioritize selected, Human review stage shown.

Workflow library

Six starting points, one source of product truth.

01

Unify data

Bring supported marketing sources into one review layer.

Create a source-aware evidence layer before the team starts interpreting performance.

02

Prioritize

Choose the next marketing action with reviewed evidence.

Turn competing observations into a reviewable backlog with rationale and approval status.

03

Reduce waste

Investigate paid-media spend before changing a campaign.

Separate spend patterns that deserve investigation from decisions that still need tracking and business context.

04

Experiments

Run a documented marketing experiment from hypothesis to review.

Keep a hypothesis, variants, review evidence and the resulting learning in one durable workflow.

05

Reporting

Create a repeatable marketing reporting and review cadence.

Reduce repeated report assembly while keeping source coverage, sync status and interpretation limits visible.

06

Local visibility

Prioritize controllable local visibility work.

Turn supported profile and search evidence into owned local actions without treating rankings as controllable.

Capabilities and limitations

Keep product support, constraints and trust evidence together.

Review what the workflow supports, what it does not claim, and how its evidence layer is defined.

What the workflow supports

  • Source and latest-successful-sync context
  • Reviewable recommendation rationale and limits
  • Documented hypotheses, decisions and follow-up
  • Explicit approval status for supported actions

What the workflow does not claim

  • Provider data is limited by authorized access and source quality.
  • Recommendations are decision support, not guaranteed answers.
  • Experiment evidence still needs an appropriate human review.
  • Management-capable actions require explicit approval.

Methodology and trust

Inspect how the evidence layer is defined.

Review the methodology, integration boundaries and documentation behind the visible workflow.

Product workflow FAQ

Questions about the decision workflow

The same approval and evidence boundaries apply across all six examples.

Does Growomo act on every recommendation automatically?

No. Growomo organizes supported evidence and a proposed next step for review. Management-capable actions retain an explicit approval boundary.

Are the workflow examples customer results?

No. Every example is clearly identified as demo data and illustrates the product workflow rather than customer performance.

Can a team begin with only one workflow?

Yes. Start with the immediate marketing job, connect only the supported sources it needs, and add other workflows when the operating process requires them.

Where does human review happen?

Human review happens before a recommendation becomes an approved action or experiment. The team adds business context, checks limitations and records the decision.