... every day? We tracked the top 10% of accounts by engagement. Their most-used feature was the Workflow Engine. Not because they requested it. Because it saved them time. They built automation for content publishing, citation alerts, and competitor tracking. That told us more than any sales call. 2. Support ticket clusters What problems keep coming up? We used RAISA to cluster 1,200 support tickets. The largest cluster (34%) was "automation rules are confusing." Not "add app store tracking ... ... usage in the 30 days before cancellation. Users who stopped using RAIVE were 4.2x more likely to churn. Users who never touched the Workflow Engine were 3.7x more likely to churn. Users who used RASE had no correlation

... hole. Product Hunt launches are every founder's obsession. Everyone wants to know the secret formula. So I used Rankfender to analyze 1,000 Product Hunt launches from 2025-2026 tracking their AI visibility, citation rates, and what actually correlated with success. Here's what the top 10% did that everyone else missed. The Dataset Parameter Value Launches analyzed 1,000 Time period 2025 2026 Platforms tracked ChatGPT, Perplexity, Gemini Metrics measured AI citations, share of voice, content structure, launch ... ... rates collapse to 3.32% and 8.29% respectively. That's a 30-to-1 gap. What this means: Your Product Hunt launch gets you known . But it doesn't get you found . Finding #2: What Actually Predicted AI Visibility We correlated

... answer first. If they find it immediately, they cite it. The structure makes extraction easy. Step 2: The Comparison Page Template Comparison pages drove 40% of our citation growth. Here's our exact template: Title: [Brand X] vs [Brand Y]: Which is better for [use case]? Quick verdict (100 words) Who wins and why One sentence summary Feature comparison table Feature Brand X Brand Y Feature A Feature B Feature C Price XX YY Detailed breakdown (by feature) How each ... ... margin of error. Result: This block was cited verbatim by Perplexity within two weeks. Step 5: The 90-Day Update Cycle We analyzed citation decay across 500 pages. The drop-off is steep: Months Since Update Citations (vs

... search landscape and that number is growing fast. Part 2: Who's winning AI citations? We tracked 2,500 brands across SaaS, e-commerce, B2B services, and publishing. The good news: Being cited in AI answers correlates strongly with: 34% higher branded search volume 28% more direct traffic over 6 months 19% better traditional SEO rankings The bad news: Only 22% of brands appear in AI answers for their core keywords. The other 78%? Completely invisible. What the winners ... ... schema 71% 19% Cite data sources 68% 27% Part 3: What content wins AI citations? This is the question everyone asks. Here's the data: Top 5 content types by citation rate: Comparison pages (X vs

... According to @RevenueCat 's State of Subscription Apps 2026 report, " hard paywalls convert 5x better than freemium, but with significantly wider variance." Day 35 download-to-paid, freemium vs. hard paywall Does access method impact download-to-paid conversion within 35 days? Quoting the report: Median D35 conversion sits at 10.7% for hard paywalls. Freemium is 2.1%. That gap alone should make you pause. But the more revealing part is the distribution. Hard paywall top decile apps approach 40% conversion ... ... free tier is doing its job building the habit. The paywall is working by staying out of the way. Comment from Andrew Stewart(@andrew_g_stewart): hard paywalls convert 5x better than freemium Is this correlation

... update has been submitted to Apple. This updates sees the integration of Apple Health and iCloud. This will allow you to write caffeine data directly to apple and read your HRV and RHR in the 'trends' tab and make correlations between higher caffeine intakes and changes to your heart activity! The new SleepView provide objective visuals to your sleep stages and total and what your caffeine level was at the point you fell asleep. You will now be able ... ... make direct correlations

... compile its results and share its findings with us every morning over a quick Slack message. Here s an example of a message we got earlier this week: As you can see, the AI discovered a clear correlation between organizations that create multi-chart dashboards early on and long-term product usage. It backed its findings up with stats and gave us an actionable product suggestion to tweak our onboarding flow. We ve been getting these messages from ... ... small team doesn t include any dedicated data analysts or PMs, and I honestly don t think we ll need to hire for those roles any time soon. Our AI agent has so much context and can make correlations

... last 4 days, I built a complete multi-agent cyber battleground that simulates: Red Team (simulated): CVE-inspired attack chains Polymorphic behavior patterns Synthetic SHA256 IOCs MITRE ATT&CK mapping Blue Team: UEBA threat hunting C2 blocking IOC correlation Detection rule generation 8-Model Ensemble Consensus: 4/8 agreement determines truth during attacks. 100+ documented scenarios: MOVEit, 3CX, Ivanti, Log4Shell patterns NEW: Live Breach Control Panel - powered by Perplexity AI Real-time incident summaries Correlated