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Competitor intelligence
See what users really think about your competitors
RivalEye scans public conversations, reviews, communities, and competitor websites to uncover what users love, hate, want, and switch for then turns those signals into decisions for your product, marketing, and growth teams.
- Sources scanned
- 0
- Avg. complaints / scan
- 0
- Time to first report
- 0m
scan / notion.report
LIVE
01 > reddit.com / r/Notion · 4,827 parsed +312
02 > hackernews / notion · 892 parsed +48
03 > linkedin.com / notion · 2,945 parsed +138
04 > x.com / notion · 6,512 parsed +203
05 > producthunt.com / notion · 411 parsed +31
06 > apps.apple.com / notion · 12,204 parsed +247
07 > play.google.com / notion · 3,821 parsed
scanning
> clustering 684 complaints
▼ clusters detected · sorted by severity
Slow on large pages 247 mentions
Missing real offline mode 194 mentions
Permissions are confusing 156 mentions
AI features feel bolted-on 132 mentions
report.ready in 00:04:12
820 / 7 sources
↑ Live scan of a real competitor - no setup
Sources monitored · 7 platforms · 24/7
↗ Continuously updated
Hacker News discussions
live
Dev.to articles
live
Product Hunt launch threads
live
App Store reviews
live
Play Store reviews
live
Websites public discussion
live
Reddit r/* threads
live
Hacker News discussions
live
Dev.to articles
live
Product Hunt launch threads
live
App Store reviews
live
Play Store reviews
live
Websites public discussion
live
01
The problem
↓
You're building on a hunch.
Your team can study competitor websites, pricing, features, ads, and design. But that still does not answer the most important question: what do their users actually think?
Users already talk in public. They praise what works. They complain about what breaks. They ask for missing features. They compare tools. They look for alternatives.
Most teams find those signals too late or not at all.
Avg. user signals read before launching
0
▼ insufficient
Across 312 product teams we surveyed in 2025.
User signals available right now
0
per scan / avg
Real user signals on a typical SaaS competitor today.
02
How it works
Three steps. No integrations.
01
/ step 01
Drop in a competitor.
A name, a domain, an App Store URL - anything. RivalEye finds them across every relevant platform.
- no integrations
- no API keys
- no setup
rivaleye / new-scan
⌘ K
>
notion.so
↳ Identified Notion · SaaS · Workspace
↳ Domains found 11 across 8 platforms
↳ Ready to scan
yes
02
/ step 02
Scan public conversations.
RivalEye analyzes Reddit, Hacker News, Dev.to, Product Hunt, app reviews, and competitor websites concurrently. Most scans complete in under five minutes.
- 7 sources
- daily refresh
- historical data
rivaleye / scan in progress
live
reddit 100%
+312 complaints
hackernews 100%
+48 complaints
dev.to 100%
+21 complaints
producthunt 100%
+31 complaints
apple 100%
+247 complaints
play 100%
+94 complaints
website 67%
+67 complaints
03
/ step 03
Get your perception report.
User signals get organized into love, pain, gap, and switch signals plus pricing and positioning insights. Six lenses to understand different decisions. Every insight is sourced.
- 6 signal lenses
- severity ranked
- fully sourced evidence
notion.report.pain
ready · 04:12
Perception Report
v.01
Love signals
18 clusters
Pain signals
24 clusters
Gap signals
18 clusters
Switch signals
9 clusters
Pricing signals
11 clusters
Positioning signals
7 clusters
Total clusters
83
02
Pick a lens
Four lenses. One competitor.
View the same user signals through the lens that matters to your role: founder, product, marketing, or growth.
- 01
Founder lens
Market opening - wedge to attack
Users love your competitor for speed and reliability but increasingly complain about pricing that punishes growth, mobile limitations, and missing executive visibility. Find the clearest wedge and the team segment most ready to leave.
- 02
Product lens
Roadmap intelligence - gaps & evidence
Which features do users ask for? What workarounds do they build? Where is the evidence strongest across sources? Prioritize your roadmap with user-backed feature requests, ranked by frequency, severity, and cross-platform confidence.
- 03
Marketing lens
Positioning copy angles
What language do users actually use to describe your competitor? What praise sticks, what criticism do they repeat? What promise-reality gap exists? Use the exact words users choose to position and message your solution.
- 04
Growth lens
Switch intent - live conversations
Who is looking for alternatives? Where are they talking? What is their pain? What is their timeline? Find the pricing threads, the comparison requests, and the "I'm leaving" conversations then understand how to engage thoughtfully.
03
Report lenses
Six signal types.
Every report includes six lenses. Each one re-organizes the same user signals around a different decision you're trying to make.
- Lens / 01 ↗
Love signals
What users praise, value, choose, and stay for. Understanding competitor strengths helps you avoid attacking the wrong thing.
Slow on large pages 92Offline mode broken 78Permissions confusing 61 - Lens / 02 ↗
Pain signals
What users complain about, struggle with, or find frustrating. Severity-ranked by frequency, emotional weight, and recency.
✕ real offline mode 247 asks✕ AI workspace search 189 asks✕ native mobile editor 156 asks✕ self-hosting option 92 asks - Lens / 03 ↗
Gap signals
What users ask for, hack around, or say is missing. Real feature requests sourced from public conversations.
willingness to pay vs $18 / mo$0 $36 - Lens / 04 ↗
Switch signals
Where users show alternative-seeking, churn risk, or buying intent. Who is looking to leave and where they might go.
migration intent 142 mentions→ Obsidian38%→ Linear (docs)24%→ Apple Notes18%→ Self-hosted12% - Lens / 05 ↗
Pricing signals
How users talk about value, plans, limits, and upgrades. Willingness to pay and pain points in current pricing.
praise"infinitely flexible"criticism"death by features"+58% 14% −28% - Lens / 06 ↗
Positioning signals
The exact language users use to describe the product, category, and alternatives. What messaging actually resonates.
01 Offline-first Notion clone 9402 AI search built right 8103 Sub-second mobile editor 73
04
The deliverable
A competitor report your team can actually use.
Every report shows what users love and hate, what they ask for, who's ready to switch with evidence, sources, and a clear opportunity to attack.
Live · 04:12
Complaints analyzed
2,417
Clusters detected
83
Sources crossed
8 / 8
Scan duration
4m 12s
▼ Featured cluster · #01 of 83
Critical
Slow on large pages
severity score
92
/100
Mentions
247
Sources
7 / 7
Trend
↑ 18%
▼ evidence · sample of 247
-
“feels sluggish after 10k blocks. m1 max chokes.”
r/Notion · 412 upvotes 14d ago -
“pages take 8s to load on a fresh laptop. unusable for big teams.”
Reddit · 287 upvotes 6d ago -
“database with 5k rows = death. our wiki is held together by prayer.”
Product Hunt · 156 upvotes 3w ago -
“switched to obsidian. notion is just too slow at our scale.”
App Store · 341 upvotes 2d ago
Opportunity
A workspace that stays fast past 10,000 blocks. Performance is the wedge 247 users complaining, 18% growth week-over-week, no competitor solving it.
▼ all 83 clusters · severity grid
hover ↗
low critical
▼ signal index
- 01 / Love signals 18 clusters →
- 02 / Pain signals 24 clusters →
- 03 / Gap signals 18 clusters →
- 04 / Switch signals 9 clusters →
- 05 / Pricing signals 11 clusters →
- 06 / Positioning signals 7 clusters →
05
Questions
The honest answers.
Everything we get asked before a first scan. If something isn't here, ask us replies go to a real human.
Questions
8 / 8
Avg. reply
< 2h
Q.01 Is RivalEye just social listening?
A.01
No. Social listening usually tracks mentions and sentiment. RivalEye extracts decision-ready signals: what users love, what frustrates them, what they want next, and who may be ready to switch.
Q.02 Is this only for finding competitor complaints?
A.02
No. RivalEye is balanced. It shows what users love and why they stay, along with pain, gaps, pricing signals, and switch intent.
Q.03 Who is RivalEye built for?
A.03
RivalEye is built for B2B SaaS founders, product teams, marketers, and growth teams that compete in active categories.
Q.04 What sources does RivalEye analyze?
A.04
RivalEye starts with public sources like Reddit, Product Hunt, Hacker News, app reviews, Dev.to, and competitor websites. Source coverage will expand over time.
Q.05 How is this different from manually reading Reddit or reviews?
A.05
Manual research is slow and easy to miss. RivalEye clusters signals, shows evidence, and turns them into role-specific dashboards your team can act on.
Q.06 How long does a scan take?
A.06
Most scans complete in three to seven minutes. The first scan of a new competitor takes longest because we build out the historical archive. Subsequent refreshes are incremental and finish in under sixty seconds.
Q.07 Does RivalEye generate leads?
A.07
RivalEye can surface public switch-intent conversations, but it is not an auto-spam tool. It helps you understand context and engage thoughtfully.
Q.08 Do insights include evidence?
A.08
Yes. Every major insight points back to source quotes, links, signal types, and confidence scores. You can verify claims in two clicks.
06 / get started
Find out what users really think about your competitors.
Join early access and generate your first competitor perception report. No sales call required. Start with one competitor.
↳ Free first scan · no card required · 4-minute setup
- First scan Free, no card
- Setup time < 30 seconds
- Cancel anytime From settings
↳ 312 product teams scanning right now