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.
AIが継続的に追跡・予測・通知するため、データ追いではなく重要なことに集中できます
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.
明確な指標がないと、納期や予算に影響が出ます。これらの指標を追跡することで先回りできる理由を紹介します。
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.
解決アプローチ:
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.
解決アプローチ:
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.
解決アプローチ:
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.
解決アプローチ:
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.
任意の指標をクリックすると、業界ベンチマーク、追跡方法、解決できる課題、得られる成果を確認できます
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
12件中10件を表示
Everything you need to know about tracking customer success metrics.
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