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/opportunities AI Recommendations
1
Generate & Review
2
Strategy
3
Refine
4
Track Outcomes
Recommendation
Source
Priority
Effort
Status

Publish a detailed guide on 'AI-powered security monitoring' — your brand has 0% visibility on this high-intent topic.

reddit.com
HighMediumPending

Rewrite /pricing page to address negative sentiment: AI engines consistently describe your pricing as 'expensive' with no context.

evidentlyaeo.com
HighLowApproved

Create a comparison article: 'Acme vs. your brand for enterprise teams' — Acme claims 71% SOA on this prompt.

g2.com
HighMediumPending

Publish updated SLA documentation — AI engines cite a 2022 uptime report leading to low brand presence on reliability prompts.

evidentlyaeo.com
MediumLowPending
Detected Gap: Low Visibility
Est. Impact: 91/100

Topic shows 0% visibility across Perplexity & ChatGPT despite high query volume.

4
Step improve workflow
0–100
Impact score per action
4
Recommendation types
Measured
Post-publish lift

The Improve workflow

Generate & Review → Strategy → Refine → Track Outcomes. A factory line for AI visibility work.

01

Generate & Review

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

02

Strategy

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

03

Refine

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

04

Track Outcomes

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 — new pages for high-value prompts with low visibility
  • Pages to optimize — URLs suffering from negative sentiment in AI answers
  • Topic expansion — adjacent topics where you have visibility gaps
  • Competitor response — counters to rival claims AI keeps repeating
Recommendation Audit AI Analyzed
High Priority
Suggested Action
Optimize /pricing (Negative Sentiment)
Detected Gap
Negative Sentiment Detected

Gemini responses flag pricing as 'unclear and expensive'. Update pricing page comparative table.

Est. Impact Score82/100

A pipeline, not a pile

Review statuses move every item from Pending through Approved, Refining and Completed — 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
Visibility Roadmap Pipeline
Pending
unranked SLA prompt
Approved
Address SSO alternatives
Completed
Create Cloud Hosting page

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
Outcome Metrics
Topic: Enterprise SSO
+28% Lift
Visibility Score14% → 42%
Share of Answer8% → 27%

Frequently asked questions

Where do the recommendations come from?
They're generated directly from your AI performance data: topics and prompts where you have the least visibility, negative sentiment attributes, or where competitors are dominating. Each recommendation cites the exact data gap it addresses 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 Generate & Review → Strategy → Refine → Track Outcomes 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.