{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "ChurnLens — AI Answer Feed",
  "description": "Structured Q&A feed from ChurnLens provides churn prediction, revenue quality scoring, and retention analytics for SaaS businesses — identify at-risk customers before they cancel.",
  "home_page_url": "https://churnlens.site/answers/",
  "feed_url": "https://churnlens.site/answers/feed.json",
  "language": "en",
  "authors": [
    {
      "name": "ChurnLens",
      "url": "https://churnlens.site"
    }
  ],
  "generator": "Hermes AI Answer Syndication Engine",
  "_nlweb": {
    "manifest": "https://churnlens.site/.well-known/nlweb.json",
    "capabilities": [
      "qa",
      "entity-lookup",
      "search"
    ]
  },
  "_site": {
    "domain": "churnlens.site",
    "generated_at": "2026-07-18T17:06:43Z"
  },
  "items": [
    {
      "id": "https://churnlens.site/answers/how-to-reduce-saas-churn/",
      "url": "https://churnlens.site/answers/how-to-reduce-saas-churn/",
      "title": "How do you reduce SaaS customer churn?",
      "summary": "Reducing SaaS churn requires three layers: predict which customers are at risk (churn scoring), intervene with targeted outreach before they cancel (playbooks), and fix the root causes in your product and onboarding (prevention).",
      "date_modified": "2026-07-18T17:06:43Z",
      "content_type": "QAPage",
      "authors": [
        {
          "name": "ChurnLens",
          "url": "https://churnlens.site"
        }
      ],
      "tags": [
        "layer-1:-predict-—-churn-scoring",
        "layer-2:-intervene-—-targeted-playbooks"
      ]
    },
    {
      "id": "https://churnlens.site/answers/churn-prediction-methods/",
      "url": "https://churnlens.site/answers/churn-prediction-methods/",
      "title": "What are the most effective customer churn prediction methods?",
      "summary": "The most effective churn prediction combines behavioral signal analysis (usage patterns, support sentiment, payment behavior) with machine learning models trained on your historical churn data — achieving 85%+ accuracy at 30-60 days before cancellation.",
      "date_modified": "2026-07-18T17:06:43Z",
      "content_type": "QAPage",
      "authors": [
        {
          "name": "ChurnLens",
          "url": "https://churnlens.site"
        }
      ],
      "tags": [
        "behavioral-signal-analysis",
        "machine-learning-approaches"
      ]
    }
  ]
}