WhailyWhaily

Action Plan

From insight to shipped — the execution layer for AI visibility

Dashboards are easy. Shipping the work is hard. Whaily turns every visibility gap, source opportunity and audit failure into a prioritised, assignable action — and tracks it until the visibility metric moves.

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ChatGPTChatGPT
ClaudeClaude
GeminiGemini
PerplexityPerplexity
DeepSeekDeepSeek

The problem

Insights without a workflow stay as screenshots.

Every AI visibility tool in the category can surface a gap. Few of them help you close it. The result: Monday sees the dashboard, agrees something should happen, and by Friday nothing has. Without a workflow layer, AI visibility programs stall exactly when they should be compounding.

How it works

From sign-up to signal in minutes.

1

Whaily generates recommendations from your own data

Every visibility gap, missing brand-audit check, high-NCI source you are absent from, and competitor-favoured criterion becomes a recommendation. Each one is explained — why it matters, which metric it moves, which competitor already does it.

2

Review, accept, dismiss

Recommendations land in a review queue. Accept the ones that fit your strategy. Dismiss the ones that do not, with a reason so Whaily stops suggesting them. Accepted recommendations become tracked action items with full context.

3

Assign, ship, attribute

Assign each action to a teammate with a due date. When it is marked done, Whaily re-runs the relevant check or prompt and links the movement back to the action. You see which work actually moved the needle.

What you get

Everything you need, in one place.

Recommendations from every feature

Brand audit, citation sources, market intelligence, competitor intelligence — all push into one unified action queue.

Backlog → In progress → Done

A simple, familiar workflow. No over-engineered project management, just enough structure to ship.

Team assignments & due dates

Every action has an owner. Every owner has a queue. Nothing orphaned.

Filter by impact and effort

Sort actions by expected NCI impact, effort estimate and priority. Ship the high-impact, low-effort ones first.

Closed-loop attribution

Completed actions are linked to the metrics they moved. The team sees the return on the work they shipped.

Auto-recheck on completion

Mark a brand-audit fix done and Whaily re-runs the check. No manual verification step, no stale statuses.

Every visibility insight as a clean, assignable task.

Recommendations, accepted actions, in-progress work and completed wins — all in one view. Filterable by owner, impact and source feature.

Screenshot slot

Action items list — statuses, owners, priority and source-feature tags. Include a mix of recommendations and active tasks.

/app/todo

Why it matters

AI visibility is a team sport. The backlog is where teams win.

The real unlock of a visibility tool is not the dashboard, it is the follow-through. Insight that does not translate into work is entertainment. Whaily is designed so the path from "we should do something about this" to "that is now shipping on Tuesday" is one button click.

Every feature in the product pushes recommendations into the same queue. That matters — it means a marketer, a PR lead and an engineer all look at the same backlog, each filtered to their slice. The G2 claim and the schema fix and the partner outreach all live together, prioritised by the impact they are expected to have on visibility, not by who shouted loudest in the last meeting.

When the work ships, the loop closes automatically. Mark the action done, Whaily re-runs the relevant check or prompt, and attributes the change to the person who shipped it. Over a quarter you end up with something rare in marketing: a receipts-backed history of what moved the metric. That is the kind of record that makes budget conversations easy.

Every action comes with the "why" attached.

Open any action to see the recommendation it came from, the data that triggered it, the metric it is expected to move, and the competitor already doing it. No missing context.

Screenshot slot

Action item detail — reasoning, linked data, assignee, due date and expected metric impact.

/app/todo (action detail)

Questions

The short answers.

Where do recommendations come from?+
Every feature — brand audit, citation sources, market intelligence, competitor intelligence, partner network — generates recommendations from the data it sees. They all flow into one unified action queue.
Can I dismiss recommendations I do not want?+
Yes. Dismissals capture a reason so Whaily stops suggesting similar things. The more you use the system, the better the recommendations get.
Does Whaily replace Linear or Jira?+
No. Whaily is the source of truth for AI-visibility-specific work. Export an action to an external ticketing system if your team prefers to track it there — future integrations will sync this automatically.
Can I see which actions actually moved my visibility?+
Yes. Completed actions are attributed to the metric movements that followed — a new citation, a passed brand-audit check, an NCI score uplift. The retrospective view is always available.
Can I assign actions to people outside Whaily?+
Actions can be assigned to any teammate in your organisation. External contributors can be captured in notes; native collaborator seats are on the roadmap.
Is there a "priority" or "effort" score?+
Yes. Whaily suggests priority and an effort estimate on every action, based on expected NCI impact and the kind of work involved. You can override both.

Pairs well with

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