Revenue operations and churn prevention
Renewals forecast 120 days out and churn risk worked before it is urgent
Net revenue retention had slipped below 100 percent and nobody could say which accounts were at risk until the cancellation email arrived. We rebuilt the renewal process around usage data, an AI risk model and an automated playbook, so customer success works the right accounts four months before the date.
- Client
- B2B analytics platform
- Region
- United Kingdom and Ireland
- Scale
- 150 to 220 employees
- Timeline
- 8 weeks to first forecast, playbooks tuned over one quarter
Representative engagement. Client details are anonymised and figures reflect typical outcomes from comparable deployments.
What the client got
0%
Net revenue retention
Up from 94 percent over four quarters.
0 days
Average lead time on at-risk accounts
CS works risk when it is still fixable.
0%
Increase in expansion revenue
Healthy accounts with headroom get a structured upsell motion.
The bottlenecks
Bottleneck 1
Renewal dates were a spreadsheet
Contract end dates lived in the CRM but were often wrong. Finance, CS and sales each kept their own list.
Bottleneck 2
Usage data never reached the account owner
The product team had dashboards showing declining logins and abandoned features. CS managers did not have access and worked from gut feel.
Bottleneck 3
Everyone discovered churn at the same time
Cancellations arrived 30 days before renewal, when the customer had already chosen a replacement.
What we built
Step 1
Single renewal record
Contract terms were reconciled from billing, CRM and signed documents into one renewal object per account, with automated checks when any source changes.
Step 2
Risk model with explanations
A scoring model combines usage trend, seat utilisation, support sentiment, champion changes and payment behaviour. An LLM writes a two-sentence explanation for each score so a CS manager knows why, not just what.
Step 3
Playbooks that trigger themselves
At 120 days out, every account enters a playbook matched to its risk tier: executive business review for high-risk, value recap for medium, upsell motion for healthy accounts with headroom. Tasks, drafted emails and decks are generated automatically.
Step 4
Forecast the board trusts
A weekly forecast rolls up renewal likelihood and expansion by segment, with the movement since last week explained in a short AI-written narrative.
The automation workflow
Renewal risk to action
From usage signal to CS playbook
Questions clients ask about this engagement
Is the risk score a black box?
No. Each score shows its contributing factors and a plain-language explanation. CS managers can override with a reason, and overrides feed back into calibration.
How accurate was the forecast?
Within three percent of actual renewal revenue in each of the first four quarters.
More in IT & Enterprise Software
Industry overview
B2B lead generation and appointment setting
An outbound engine that books meetings for a B2B AI software vendor
A software vendor with a strong product and no outbound motion needed qualified meetings with buyers in the US and Europe. We built the targeting, messaging and qualification system and delivered appointments on a pay-per-meeting basis before moving to a retainer.
10 to 30
Qualified meetings per month
AI agent development
AI support triage that gives engineers their week back
Senior engineers were spending a third of their week on tier-one tickets. We built an AI support agent on top of the product documentation and ticket history that resolves routine questions, drafts answers for the rest, and escalates with full context.
45%
Tickets resolved without an engineer
Onboarding and implementation automation
Customer onboarding that runs itself for a vertical SaaS vendor
Every new customer took six weeks and twelve emails to go live. Data imports were done by hand, kickoff calls repeated the same setup, and churn in the first 90 days was the company’s biggest leak. We automated the onboarding path from signed contract to first value, with AI handling data mapping and progress nudges.
12 days
Median time to first value
B2B lead generation for cybersecurity
Filling a managed security provider’s pipeline with mid-market CISOs
A managed detection and response provider sold almost entirely through referrals and a handful of channel partners. Security buyers ignore cold email on principle. We built outbound around compliance deadlines, breach events and insurance renewals, and the provider booked more qualified first calls in a quarter than in the previous year.
58
Qualified first calls in the first quarter
Have a similar bottleneck?
Tell us how the work happens today. We will show you the workflow we would build and prototype it on your own process.