Quivly Blog
Hold The Churn
Insights and thought leadership on building high-growth revenue engines — and stories from leaders who've scaled teams in B2B SaaS.
Quivly Blog
Insights and thought leadership on building high-growth revenue engines — and stories from leaders who've scaled teams in B2B SaaS.

You have a sharp finance team, a modern CRM, and a billing system that handles millions in recurring revenue.

You watch a six-figure account go dark. The renewal date passes, and the logo disappears from your dashboard.

Your dashboard is a liar. It shows a field of green dots and steady login graphs, yet the renewal forecast keeps missing by a painful margin.

Your dashboard is green. Login frequency is steady, feature adoption is climbing, and the health score glows a confident emerald.

Your largest enterprise customer signed the contract eight weeks ago. The ink is dry. Your product sits in a staging environment while the customer's data

Your dashboard says the account is healthy, but their usage tells a different story. They shipped a product integration, logged into the dashboard daily

Your largest customer just announced a $50 million Series B and a new VP of Sales. You learn about it from a LinkedIn post that has been sitting there for three

Your support team just flagged a seventh ticket from the same account this quarter. Your CRM shows the contract is up for renewal in 60 days

Your sales team closed a six-figure deal last quarter. Today, the account is silent. Usage is flatlining, the champion went dark on Slack

The Slack message lands like a small bomb. Your customer health score for a major account just dropped 22 points in an hour, triggering a red-alert escalation.

Your VP of Customer Success is pitching three new CSM hires, while your Head of Revenue Operations is pushing for a new health-scoring platform.

Sixty days into a six-figure enterprise software deployment, the customer’s champion stops returning calls.

Your quarterly board deck shows net revenue retention stalling at 106% while your best competitor just printed 122%.

Your dashboard tells you an account is red, but it cannot tell you why the champion went silent.

Your CS team is scaling a static problem. The old math of hiring linearly to cover a growing book of business collapses the moment you see the data

Your customer success team is drowning in data but starved for insight. A CSM's morning starts by manually stitching together a CRM record that hasn't been

Your most valuable accounts churn without filing a ticket. By the time your CRM shows red, the decision is already made.

Your most reliable churn model told you an account was doomed two weeks after they stopped logging in. The data was unbalanced

Your customer success team is prepping for a QBR, and they are in three different systems just to find the last support ticket.

Your VP of Sales lives in the CRM. Your marketing team swears by a marketing automation platform they refuse to let sales touch.

Your highest-value account stopped using a core feature on Tuesday. They opened two support tickets on Wednesday

The champagne pops when the deal closes. Then everybody moves on to the next quarter's pipeline while the value of that hard-won signature quietly erodes.

Your finance team asks about the Q4 forecast, and three enterprise accounts you assumed were safe are suddenly negotiating discounts, reducing seats

Your quarterly board deck shows net revenue retention stalling at 106% while your best competitor just printed 122%. The diagnosis is familiar

Your board just approved a capital spending plan for aggressive account growth. The logic is linear: more accounts, more revenue, more people to service them.

Your CS team carries 40 accounts per rep. The board wants 120% net revenue retention this fiscal year. Headcount is flat.

AI-native customer intelligence unifies CRM, support, product, and billing data into real-time health scores that trigger playbooks before accounts churn.

July product updates — Agent Builder, Actions, Skills, and new Slack, HubSpot, and Granola integrations — plus Cook with Quivly.

Your best month often plants the churn you'll pay for in Q3.

Quivly open-sourced 21 free Agent Skills for post-sales on GitHub — meeting prep, QBR, churn saves, and more. Load them into Claude, or ChatGPT with one prompt.

Automated workflow management replaces manual post-sales work with cross-system orchestration. Learn how to build health scores, playbooks, and rescue plays.

A six-step system for post-sales workflow automation that protects revenue, from mapping lifecycle stages to measuring renewal and expansion.

Most customer success teams are drowning in data but starved for action. You can spot the churn risk account, but the hours between detection and human opening

Your customer success team is trapped fighting yesterday's fires while your competitor's AI is booking next quarter's expansion. The math is brutal. A 5% monthl

Stop stitching spreadsheets together. Automate customer intelligence by unifying CRM, usage, support, and billing data into live, churn-aware profiles.

How to measure ROI from AI agents in post-sales: track efficiency gains, revenue impact, and signal quality with concrete instrumentation steps.

Post-sales automation shifts CSM coverage from 10–30 to 40–60+ accounts per rep without added headcount—here's how AI changes the ratio.

Automation gives 1:many account coverage at a fraction of CSM hiring cost. See the unit economics, predictive playbooks, and scoring behind it.
AI agents in post-sales fail without clean data and defined processes. Learn the 3 things that must be true before you automate renewals.

How AI agents build one live profile per account—streaming CRM, support, and usage data with entity resolution and citation-backed outputs, no warehouse needed.

The six signal categories post-sales agents monitor: product usage, engagement, support behavior, expansion readiness, churn risk, and workflow triggers.

Mycroft CEO Mike Kim on scaling agentic security to 100+ customers — sell before you build, virtual CISO retention, and why silence signals churn.

Four Spring Shipping drops in June — MCP, Ask Quivly, Agent Builder, and Data Models — plus Hold The Churn with Mycroft CEO Mike Kim.

AI agents handle signal detection and draft generation in post-sales, expanding viable account coverage from 50-100 to 100-150 per rep without adding headcount.

AI agents execute playbooks autonomously—drafting emails, triggering workflows in real time—while CS dashboards only surface data for manual CSM review.

Customer engineering turns post-sales into a technical, build-focused role. Learn what customer engineers do, the skills they need, and why the title is rising.

Revenue from existing customers falls when post-sales teams lack the real-time signals to catch churn before renewal. Here's how to close the gap.

Spot at-risk customers months before renewal. Learn the five churn signals post-sales teams should track daily, from usage decline to stakeholder turnover.

Post-sales is being rewritten. See how the team of the future runs every account in real time, catches risk early, and grows the whole book at once.

Strong acquisition can't offset churn you can't see. How signal blindness, manual delays, and reactive workflows drain existing-customer revenue.

Reduce time to value after the sale by automating adoption-stall detection, triggering rescue playbooks, and escalating only when signals warrant it.

AI agents for post-sales teams run account management and growth on autopilot, so the same team covers 3x the accounts without adding headcount.

How we ship fast: sort every product decision into hats (reversible), haircuts (medium-term), or tattoos (permanent), and only debate the tattoos.

B2B SaaS churn prediction starts at onboarding, not renewal. Learn the 5 leading indicators, build an explainable health score, and automate rescue playbooks.

Billing gaps, expired discounts, and disengaged accounts cost SaaS companies up to 5% of ARR. Here's how to catch and stop revenue leaks before renewal.










Forward Deployed Engineers - who they are and why they are gaining popularity in modern SaaS and AI companies.

