Monitor customer health in real-time and catch issues before customers leave. Get alerts when engagement drops, usage declines, or satisfaction scores fall so you can save accounts that matter.
AI가 지속적으로 추적·예측·알림하므로 데이터에 쫓기지 않고 중요한 일에 집중할 수 있습니다
AI monitors product usage, support interactions, and engagement patterns to identify customers likely to churn. Get alerts 30-60 days before renewal with specific risk factors and recovery strategies.
Stop guessing about account health based on gut feel. Get objective health scores combining usage data, support history, engagement metrics, and sentiment analysis refreshed daily.
Identify accounts ready for upsells based on feature usage, team growth, and engagement signals. Get recommendations on which products to pitch and when to start the conversation.
명확한 지표가 없으면 일정과 예산이 손실됩니다. 이 지표들을 추적하면 어떻게 앞서갈 수 있는지 확인하세요.
You find out customers are unhappy during renewal calls when it's already over. CSMs are surprised by cancellations from accounts they thought were healthy.
해결 방법:
Continuous health monitoring tracks usage, engagement, and sentiment daily. Alert CSMs immediately when metrics drop so they intervene weeks before renewal with time to recover the account.
Your team manages 100+ accounts but has no systematic way to prioritize. High-value customers slip through the cracks while CSMs waste time on happy accounts that don't need help.
해결 방법:
Health scores and risk rankings tell CSMs exactly which accounts need attention and why. Auto-assign tasks and playbooks so team members always know their priorities.
Customers are growing, adding team members, and using your product heavily but nobody notices the upsell opportunity until the account manager asks randomly.
해결 방법:
Expansion signals automatically identify accounts ready to upgrade based on usage patterns, team growth, and feature adoption. Get recommendations on what to propose and timing for outreach.
You don't know if customers are happy until NPS surveys months later. Support tickets and email responses contain sentiment data but nobody analyzes it systematically.
해결 방법:
Sentiment analysis processes every support ticket, email, and survey response to gauge customer mood. Track sentiment trends over time and get alerts when satisfaction drops.
지표를 클릭해 업계 벤치마크, 추적 방식, 해결 과제, 기대 성과를 확인하세요
Keep the customers you worked hard to win
Track retention trends before they impact recurring revenue
Losing customers faster than you can replace them
Measure true account growth
See if existing customers are expanding or contracting
Growing customer count but shrinking average account value
Monitor customer satisfaction continuously
Get early warnings before customers become unhappy
Customers churning without ever expressing dissatisfaction
Track how fast customers adopt your product
Identify slow adopters before they churn during onboarding
New customers staying dormant and never realizing value
Measure support effectiveness
Ensure support interactions actually solve problems
High support volume but customers still frustrated
Know how customers really feel
Aggregate satisfaction signals before quarterly business reviews
Assuming customers are happy until they tell you they're leaving
See which features customers actually use
Identify unused features before pitching expansions
Customers paying for features they don't know exist
Get customers to success faster
Reduce onboarding time before customers lose patience
New customers taking months to see value and churning early
Measure product engagement breadth
Identify power users and feature champions
Customers using only basic features and missing advanced value
Make your product easier to use
Identify friction points before they cause abandonment
Customers struggling with your product but not reporting it
12개 중 10개 표시
Everything you need to know about tracking customer success metrics.
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