Recommendations

The Recommendations page surfaces specific actions GrackerAI suggests based on your monitoring data. connecting what you see in your scores and responses to concrete next steps.

How to use it: Review weekly. Validate against real response data before acting. Mark complete only when you see a measurable score improvement.

Four Recommendation Categories

GrackerAI generates recommendations across four areas, each sourced from a different signal in your monitoring data:

1. Visibility Drops

Prompts where your score has fallen significantly since the previous period.

What GrackerAI shows you:

• Which prompts dropped and by how much
• Which AI surfaces drove the drop
• What content was cited instead of yours

What to do:

1. Read the actual responses on the affected prompts
2. Identify what replaced you. a competitor's new content, a third-party source, a model update
3. Determine whether this is a content gap (create new content) or a positioning gap (update existing content)
4. Re-check in 4–6 weeks after acting

2. Competitor Alerts

A tracked competitor is appearing significantly more often in your monitored responses.

What GrackerAI shows you:

• Which competitor is spiking
• Which prompts and surfaces they're gaining on
• The magnitude of the change

What to do:

1. Filter Responses to that competitor's group and read their recent appearances
2. Identify what content or sources are driving their increased citations
3. Assess whether you need to create equivalent content or earn placements on the same citation sources
4. Monitor their trajectory weekly until it stabilises

Don't overreact to a single-week competitor spike. AI models update frequently and can temporarily shift citation patterns. Look for trends over 2–4 weeks before making major content decisions.

3. Sentiment Issues

AI responses are consistently describing your brand with neutral or negative language on specific prompts.

What GrackerAI shows you:

• Which prompts have declining or negative sentiment
• Which AI surfaces are generating the negative framing
• The sentiment trend over time

What to do:

1. Read the full responses on affected prompts. identify the exact language AI is using
2. Trace the language back to its source: a specific review, a comparison page, a forum thread
3. If factually wrong. request a correction at the source
4. If accurate but unflattering. address the underlying issue (product, pricing, support) and create new authoritative content that reframes it

4. Offsite Distribution

Third-party platforms that should be carrying your brand's narrative aren't. leaving citation opportunities unclaimed.

What GrackerAI shows you:

• High-citation domains in your category where your brand doesn't appear
• Source types (community, news, directories) where competitors are cited but you aren't
• Platforms with the highest citation frequency that you're absent from

What to do:

1. Prioritise the highest-occurrence domains first
2. Check what content from those domains is being cited. understand the format and tone
3. Reach out to publications, request to be included in listicles, or engage authentically in communities
4. For directories (G2, Capterra). ensure your profile is complete and actively collecting reviews

The Right Workflow

Follow this order for every recommendation:

Warning: The most common mistake is acting on a recommendation without first reading the actual responses it's based on. The recommendation shows you what to fix. the response shows you why.

Priority Tiers

Next Steps