Featured insight
Diagnose before automating support
Automation works best when the operational problem is understood first. Otherwise, it can make poor workflows faster, more complex and harder to see.
Insights
Operational thinking for post-sale leaders.
Practical analysis for Customer Support and Customer Success leaders: what the numbers mean, where operational risk is building and what to do about it.
Point of view
Practical, not generic.
Signals Ops focuses on the operating decisions behind performance: what is changing, why it is happening, what the evidence supports and what teams should do next.
Expect practical analysis of real operational problems rather than generic management advice or trend commentary.
Topics
Topics we write about.
Customer Support Operations
Backlogs, service performance, workflows, capacity and quality.
Customer Success Operations
Health, risk, lifecycle design and operational consistency.
AI & Automation
Where automation helps, where it creates risk and how to measure it.
Zendesk & Service Technology
Workflow design, reporting, governance and platform improvement.
Metrics & Reporting
What measures actually tell you and where they can mislead.
Operating Models
Ownership, structure, processes and how post-sale teams work together.
Latest
Latest insights.
Customer Support Operations
How to Tell Whether Your Support Team Is Understaffed
Learn how to tell whether your support team is understaffed by checking demand, completion, effective capacity and hidden workflow constraints.
Read article →Knowledge Management
Knowledge Base Gap Analysis: How to Use Support Ticket Data
Learn how to use support tickets, searches, reopens and escalations to find knowledge base gaps and turn them into a prioritised action queue.
Read article →AI in Customer Support
Customer Support Automation: What to Automate, What to Assist and What to Leave Alone
Decide which support tasks to automate, assist with AI or keep human-owned using risk, knowledge quality and fallback criteria.
Read article →Insights
More from Signals Ops
Practical writing on Customer Support, Customer Success, AI, service performance and operational improvement.
Customer Success Operations
Backlog Health Scoring: Why One Score Is Not Enough
Learn how to assess backlog health across volume, age, severity, ownership, flow and outcome impact, without hiding critical risk inside one overall score.
Read article →AI in Customer Success
How AI Is Changing Customer Success: Practical Uses, Limits and Risks
Learn how AI is changing Customer Success, where it helps, where it fails, and how SaaS teams can govern AI-assisted workflows.
Read article →Customer Intelligence
What Is Customer Intelligence? A Practical Guide for SaaS Teams
Learn what customer intelligence means for SaaS teams, which customer data sources matter, and how to turn customer signals into better decisions.
Read article →Customer Onboarding
How to Improve SaaS Customer Onboarding
Learn how to improve SaaS customer onboarding with clearer milestones, ownership, customer readiness checks, friction diagnosis and journey reviews.
Read article →Customer Retention
Customer Retention Metrics Every SaaS Company Should Track
Learn which customer retention metrics SaaS teams should track, how to calculate them, and why NRR alone can hide churn and weak segments.
Read article →Customer Success Software
Customer Success Software: What to Look For Before You Buy
Learn how to evaluate Customer Success software by testing data quality, workflows, AI claims, implementation risk and buying fit before you choose a tool.
Read article →Dealing with a similar operational problem?
If something in your Support or Success operation is not working as it should, Signals Ops can help diagnose the cause and work through what to change.
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