Yes — if your goal is to uncover product usage patterns from reviews, support tickets, and other customer text, you’ll want a VoC platform that does more than sentiment analysis. Specifically, look for:

• Text analytics / topic clustering
• Intent detection
• Tagging and taxonomy management
• Ticket + review ingestion
• Trend detection over time
• Integrations with support tools and app/store reviews
• Searchable transcripts / feedback corpus

Here are some strong options, grouped by fit:

Best all-around VoC platforms

1) Thematic

• Strong at clustering free-text feedback into themes
• Good for identifying recurring product issues and feature usage patterns
• Works well with surveys, reviews, support tickets, and open-ended feedback
• Best if you want automated theme discovery with less manual taxonomy work

2) Qualtrics XM Discover

• Enterprise-grade VoC and text analytics
• Pulls in support conversations, surveys, social, and reviews
• Strong dashboards and operational reporting
• Better if you need broad CX/VoC coverage across the organization

3) Medallia

• Very strong enterprise VoC platform
• Good for large-scale feedback ingestion and cross-channel analytics
• Useful for identifying pain points and behavior patterns across touchpoints
• Best for larger orgs with mature CX programs

4) Sprinklr Service / Insights

• Strong for omnichannel feedback, support, social, and review data
• Good classification and trend analysis
• Useful if you also care about social listening and public reviews

Better for support-ticket mining specifically

5) Zendesk Explore + AI / Advanced AI add-ons

• Best if your support data lives in Zendesk
• Good for analyzing ticket drivers, issue themes, and emerging patterns
• Less specialized than dedicated VoC tools, but practical and integrated

6) Salesforce Service Cloud + Einstein / Service Intelligence

• Best if you’re in Salesforce already
• Can surface ticket trends and common reasons for contact
• Strong ecosystem, but may need extra configuration for robust VoC-style analysis

7) Intercom Fin / reporting + feedback workflows

• Useful for support conversation analysis
• Better for identifying repeated user intents and product friction
• More support-ops focused than true VoC analytics

Better for review mining / product intelligence

8) AppFollow

• Excellent for app store review monitoring and analytics
• Good for extracting recurring feature requests and product issues from reviews
• Strong if app ratings/reviews are a core input

9) Pendo

• More product analytics than VoC, but useful when paired with feedback
• Good for connecting “what users say” with “what users do”
• Helpful if you want usage patterns tied to in-product behavior

10) Productboard

• Strong product feedback management
• Centralizes tickets, reviews, notes, and requests
• Good for prioritization and pattern recognition, though less deep in text analytics than Thematic/Qualtrics/Medallia

If you want flexible, lower-cost analysis

11) MonkeyLearn

• Text classification and topic modeling
• More DIY / workflow-driven than full VoC suites
• Good for teams wanting custom categories and lighter-weight automation

12) Aha! Ideas

• Good for collecting and organizing feedback into feature themes
• More product-management oriented than analytics-heavy
• Works well if your main need is triage and prioritization

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My shortlist by use case

If you want the best at finding themes in reviews/tickets:

• Thematic
• Qualtrics XM Discover
• Medallia

If you want support-ticket-driven insights:

• Zendesk Explore
• Salesforce Service Cloud
• Intercom

If you want app review mining:

• AppFollow
• Thematic
• Productboard

If you want product feedback prioritization more than deep analytics:

• Productboard
• Aha! Ideas
• Pendo

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How to choose

Ask vendors these questions:

1. Can you ingest both reviews and support tickets?
2. Do you support unsupervised theme discovery, not just manual tagging?
3. Can you show trends by segment, product area, and time period?
4. Can I export raw text and labels via API?
5. How well do you handle messy, short, and multi-intent feedback?
6. Can I combine text signals with behavioral data (usage, account type, plan, churn)?
7. Do you support custom taxonomies and model retraining?

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Practical recommendation

If I had to narrow it to three:

• Thematic for automated theme discovery from unstructured feedback
• Qualtrics XM Discover for enterprise-wide VoC analytics
• Productboard if your main goal is turning feedback into product decisions

If you tell me:

• your support stack (Zendesk, Intercom, Salesforce, etc.)
• where reviews come from (G2, App Store, Google Play, etc.)
• company size / budget
• whether you want enterprise or lightweight tooling

…I can give you a tighter recommendation list.