AI Insights is the review-intelligence side of the platform. Instead of manually reading through large volumes of reviews to understand what customers are really saying, the platform analyzes them for you and turns them into structured signals.
That means the agency can move from reacting to individual reviews toward understanding patterns, weak spots, and opportunities across the whole review set.
What AI Insights is
AI Insights is an AI-powered dashboard that analyzes customer reviews and produces structured intelligence from them. The goal is not just to summarize reviews, but to extract useful operational signals from them.
- Review score beyond simple star averages
- Sentiment analysis with trends
- Category scoring for business-relevant themes
- Keyword extraction across positive and negative language
- Recommendations with action priority
- Source-level review breakdowns
- Alert detection for meaningful change
Who can use it
From the agency side, AI Insights is available when the platform has a valid default AI provider configured. For customers, access is controlled through the custom plan feature settings like other higher-value features.
- Enabled gives the customer full access
- Upgrade keeps the feature visible but gated
- Hidden removes it from the customer experience entirely
Provider requirement
AI Insights works with either OpenAI or OpenRouter. The platform simply needs one default AI provider that is ready and working.
That makes it easier to adopt than Search AI, which specifically needs OpenRouter.
- OpenAI works
- OpenRouter works
- One default AI provider is enough
Minimum review requirement
AI Insights needs at least 5 text reviews to produce a useful analysis. Star-only reviews are not enough on their own because the feature depends on written content to detect themes and sentiment patterns.
How analysis is triggered
There are three practical ways AI Insights gets created: manual generation, generating for all locations, and the automatic weekly run.
- Manual generation when you click the generate action
- Generate all locations for multi-location organizations
- Weekly automatic generation for organizations with enough text reviews
What happens during analysis
The system first gathers the relevant text reviews, computes the baseline metrics such as ratings and response rates, then sends the review set through the configured AI model to classify sentiment, identify categories, extract keywords, and generate recommendations.
If the review volume is large, the reviews are handled in batches and then merged into one final analysis.
- Review collection
- Sampling where necessary
- Baseline statistical calculation
- AI analysis and recommendation generation
- Alert detection after the analysis is complete
How to read the dashboard
The dashboard is organized to move from top-line summary into deeper explanation. The review score is the quickest directional number, but the real value comes from category scoring, source differences, and recommendation quality.
- Review score for the top-line view
- Sentiment chart for positive, neutral, and negative distribution
- Score trend over time
- Quick stats for review count, average star rating, and response rate
Categories, keywords, and recommendation quality
AI Insights turns review text into business-relevant themes such as friendliness, cleanliness, wait time, or quality of work. This is where the analysis becomes actionable instead of merely descriptive.
The recommendation layer then converts those patterns into immediate actions, shorter-term improvements, and longer-term strategic ideas.
Source and location analysis
The feature can break insights down by review source and by location. This matters because one platform may skew more negative than another, and one branch may be performing much worse than the rest of the business.
That makes AI Insights especially useful for agencies managing multi-location clients or clients with review activity spread across several platforms.
Historical insights and reporting
Previous analyses are stored so you can compare trends over time. AI Insights can also feed scheduled reporting, which makes it easier to show progress instead of only presenting one isolated snapshot.
Alerting and what it watches for
AI Insights automatically checks for meaningful issues after each analysis, such as declining sentiment, urgent negative themes, low satisfaction, or large review-response gaps.
When important issues are detected, the platform can send notifications with severity-based messaging so agencies know where to focus first.
AI Insights vs Search AI
| Area | AI Insights | Search AI |
|---|---|---|
| Primary purpose | Analyze your actual review data | Monitor visibility across AI search platforms |
| Data source | Your customer reviews | AI-generated search responses |
| Provider requirement | OpenAI or OpenRouter | OpenRouter only |
| Best for | Service quality, reputation patterns, and review strategy | External discoverability and AI recommendation visibility |