Operational thinking for teams running CS as a revenue function.
Written by the person who builds this for clients. Frameworks, sequences and the arguments behind them, without the vendor marketing.
Planhat implementation: cost, timeline and how to choose a partner
The full reference: what an implementation costs and what drives the number, how long each scenario takes, when to do it yourself, when Planhat is the wrong platform, the eight questions to ask any partner, and the signals that an existing instance needs rescuing.
Read the guideWhy most Planhat rollouts stall, and the order of operations that fixes it
The tool is rarely the problem. Teams configure the instance before they design the operating model it is supposed to carry, and dashboards get built first when they should be built last.
Your health score is probably a mood ring. Here is how to make it predict something.
Red, yellow, green driven by CSM sentiment was never designed to forecast outcomes. A model built from your own churn history and validated on a holdout set is a different instrument entirely.
What customer success contributes to revenue, in numbers a CFO will accept
Retained ARR attribution, expansion influenced, cost to serve and revenue at risk managed, on one slide, refreshed quarterly.
Where a CSM's week actually goes, and the twelve workflows to automate first
Internal updates, data entry, meeting prep, manual follow-ups and status reports do not move accounts forward, and they eat a large share of the week. A time audit and a ranked automation list fix more than a headcount request does.
Agentic workflows in customer success: what is real, what to build first, and what has to be true underneath
Not chatbots, not copilots. Software that takes a goal, works across systems and comes back with a result. The teams getting value are the ones with a clean data layer underneath.
Stop measuring NRR as one number. Break it down by product.
A company running 108% NRR can have one product line expanding at 130% while another contracts at 85%. Product-level NRR in Planhat is the metric that shows where growth comes from and where it leaks.
Your CS team is not ready for AI. Your data architecture is the problem.
The models are capable. What they cannot do is synthesise data that is fragmented across five systems with no shared identity. The six things that have to be true before AI in CS produces anything trustworthy.
Your health scores are colour coding, not prediction. Here is how to fix that.
Rule-based thresholds describe the present. A predictive score built from your own churn history, with trajectory and multi-variate patterns, tells you what is about to happen.
Build this: an AI morning briefing that tells your CSMs where to focus
A worked build. Every account in the book scanned overnight, ranked with the reasoning behind each rank, delivered before the laptop opens. Data model, prompt design and the guardrails that keep it trustworthy.
Your CRM cannot forecast renewals. Here is what can.
The CRM knows the renewal date and the ARR. It does not know usage trajectory, stakeholder engagement, support sentiment or product adoption depth. A renewal forecast built from those signals in Planhat.
Reading is cheaper than rebuilding. Talking is cheaper than both.
Thirty minutes on your instance, a specific read, and an order of operations you can act on whether or not we work together.