Content Factory

From gap to published, in four steps.

Every recommendation arrives with a reason, an impact score and a workflow — so AI visibility gaps turn into shipped content and measured lift, not another backlog.

evidentlyaeo.com/improve/discover AI Recommendations
Discover
Action Plan
Execute
Impact
New contentSuggested

Create comparison page: You vs Acme

Impact 87/100High AI-generated
Queue · 3 more
Measured impact
+13.3% SOA
3 recommendations shipped
0
Step improve workflow
0–100
Impact score per action
0
Recommendation types
Measured
Post-publish lift

The Improve workflow

Discover → Action Plan → Execute → Impact. A factory line for AI visibility work.

01

Discover

The engine analyzes your visibility gaps and competitor strengths, then generates prioritized recommendations — each with an action, a reason and an impact score.

02

Action Plan

Approve, reject or edit each recommendation, add your own, and shape the approved set into a strategy with owners and timelines.

03

Execute

Track every approved item from draft to published. Statuses keep the whole team honest about what's actually shipped.

04

Impact

Once work ships, the platform measures what changed — visibility, Share of Answer and sentiment on the topics each recommendation targeted.

Recommendations with receipts

Not generic SEO advice — specific actions tied to specific gaps in your AI visibility data.

Every recommendation explains itself

Each card carries the action, the reason it matters, an estimated impact score and a priority — so you can defend every hour of content work.

  • Content to create — pages and posts for queries you currently lose
  • Pages to optimize — existing URLs that underperform in AI answers
  • Topic expansion — adjacent segments worth claiming
  • Competitor response — counters to rival claims AI keeps repeating

A pipeline, not a pile

Review statuses move every item from Suggested through Approved, In draft and Published — your AI visibility roadmap stays a living pipeline instead of a stale audit doc.

  • One-click approve / reject on every suggestion
  • Add custom recommendations alongside AI-generated ones
  • Filter by priority, impact score and status

Proof the work moved the needle

The Impact step closes the loop: for every shipped recommendation, see the change in visibility and Share of Answer on the topics it targeted.

  • Before/after metrics per recommendation
  • Topic-level SOA lift attribution
  • A track record that justifies the next quarter's plan

Explore the rest of the platform

One platform for the full AEO loop — measure, analyze, optimize.

Frequently asked questions

Where do the recommendations come from?
They're generated from your own tracking data: visibility gaps on queries you lose, competitor strengths, citation gaps and sentiment weak spots. Each recommendation cites the reason it was generated and carries an estimated impact score from 0–100.
What types of recommendations does the engine produce?
Four types: new content to create, existing pages to optimize for AI crawlers, topics to expand into, and responses to competitor claims that AI engines keep repeating.
Can I add my own recommendations?
Yes. Custom recommendations sit alongside AI-generated ones and flow through the same Action Plan → Execute → Impact workflow with statuses and priorities.
How is impact measured after publishing?
Each recommendation is linked to target topics and queries. After the work ships, the platform compares visibility, Share of Answer and sentiment on those targets against the pre-publish baseline.
Does this replace my content team?
No — it points them at the highest-leverage work. The factory decides what to build and proves what it was worth; your team still owns the craft.

Stop auditing. Start shipping.

Turn your AI visibility gaps into a prioritized, measurable content pipeline.