Eclipse AI

Paid

Eclipse AI is a customer feedback platform for research and CX teams. It pulls together reviews, surveys, calls, chats, and tickets into one place for analysis.

The AI scores sentiment and spots themes across all that text. You get a dashboard you can slice by location, channel, or customer group.

It is built for teams managing voice-of-customer data across many sources. It is not a general BI tool or a basic survey builder.

Open it if you need one view of scattered customer feedback. Skip it if you want deep self-serve analytics or cheap per-seat pricing.

It fits when your job is listening to customers across channels.

• CX and operations teams at mid-market companies: You have feedback everywhere and no time to read it all. This gives you one live rollup instead.
• Marketing teams: You need quick reads on review and survey trends. The AI surfaces patterns without manual digging.
• Organizations adding AI to CRM and survey tools: You already have data sitting there. This turns it into scored, searchable insights.
• Teams wanting dedicated feedback analytics: You tried BI tools and they asked too much of you. This one is built for CX data only.
• Customer success teams: You need churn flags before customers leave. The platform ranks risk from what customers already said.
• Multi-location businesses and franchise groups: You manage CX across sites or brands. You can filter by location and catch local issues fast.
• Teams with omnichannel data to merge: Your feedback lives in five tools. This brings them into one sentiment score.
• Organizations prioritizing sentiment rollup: You want the big picture more than deep drill-downs. The dashboard gives you that.

These are what you notice after you start using it.

• Unified feedback view: Reviews, surveys, calls, chat logs, and tickets land in one dashboard. You stop tab-hopping to check each source.
• Segmentable analytics: You can cut the data by brand, country, franchisee, or channel. Multi-location teams see exactly where the pain is.
• Real-time sentiment and themes: The AI reads new feedback as it arrives. You catch a problem while customers are still talking about it.
• Kanban-style follow-up board: Insights turn into tasks you can track. The loop from "this is broken" to "we fixed it" stays visible.

Getting in is straightforward.

1. Connect your feedback sources: review sites, survey tools, support tickets, call recordings.
2. Wait for the first sync and AI scoring to run.
3. Filter the dashboard by location, channel, or segment to see what matters to you.
4. Watch real-time sentiment shifts and set alerts for drops.
5. Route findings to the task board and assign fixes.

Skip it when these limits hit your setup.

• Per-user licensing: You pay for each seat. Larger teams feel the cost stack up fast.
• Survey upload friction: Self-serve CSV upload does not work. You route files through a contact person first.
• Thin public review base: Only two verified reviews on major directories. Hard to triangulate what real long-term use feels like.