The work,in depth.
Six offerings, each scoped around the outcome your leadership is accountable for. Most engagements combine two or three — strategy paired with the build that makes it real.
Retention strategy
A retention model your leadership can defend — built from how customers actually behave, not how a template says they should.
Leadership teams responsible for net revenue retention who need a clear, evidence-based plan instead of another framework.
- Churn and expansion analysis grounded in your own data
- A prioritised retention model with owner and sequence for each move
- Board-ready narrative that ties retention work to revenue
Retention is decided long before the renewal.
Most retention plans start at the renewal date and work backwards to a save play. By then the outcome is already set. I treat retention as the sum of every promise a company keeps after the contract is signed, so the strategy starts where value is first promised: in the sale, the handoff and the first ninety days. The work is to find the few moments that actually decide whether a customer stays, and to give each one an owner.
- 01.1
Evidence before opinion
The plan comes from how your customers actually behave, cohort by cohort, not from a benchmark someone else published.
- 01.2
Few moves, clearly owned
Three changes with named owners beat twenty initiatives nobody is accountable for.
- 01.3
Tied to revenue
Every move connects to net revenue retention, so the board conversation is about money, not activity.
Lifecycle & onboarding
The first ninety days decide the next three years. We design the journey from signature to first realised value.
Teams whose onboarding is improvised, inconsistent, or measured by activity rather than the customer's first win.
- A stage-by-stage lifecycle map with entry and exit criteria
- Onboarding playbooks your team can actually run at volume
- Value milestones defined with the customer, not for them
The first win is the whole game.
Customers rarely churn in year two. They stop believing in month two, and it surfaces later. I design the lifecycle around the moment a customer first sees real value on their own terms, and work backwards from it. Onboarding is not a list of trainings delivered. It is the shortest honest path from signature to that first win, with a definition of done the customer has agreed to.
- 02.1
Value defined with the customer
Milestones are agreed at kickoff, so success means the same thing on both sides of the table.
- 02.2
Stages with exit criteria
Every stage has a clear way in and a clear way out, so nothing drifts and nothing stalls unseen.
- 02.3
Built for volume
A playbook only counts if a new CSM can run it on their fortieth account as well as their first.
CS operations
Segmentation, health scoring, and renewal motions that match how your team works — and hold up when the account count doubles.
CS leaders scaling past the point where one person can hold the whole book in their head.
- Segmentation and coverage model sized to your team
- Health scoring built on leading signals, not lagging sentiment
- Renewal and expansion motions with clear ownership
Scale is designed, not hired.
When a CS team answers every problem with more headcount, cost grows faster than retention. I build the operating model that lets a team scale without that: segmentation that matches coverage to value, health scores built on signals that move before the customer does, and renewal motions with one clear owner. The result is one operating model for the whole post-sale organization, not a patchwork of individual habits.
- 03.1
Coverage matches value
Segmentation decides where time goes, so time goes where it changes outcomes.
- 03.2
Leading signals only
Health scores rest on behaviour that predicts churn, not on how a call felt.
- 03.3
One owner per motion
Renewal and expansion each have a named owner and a rhythm, so nothing depends on memory.
Data & dashboards
One version of the truth. We define it, model it, and put it in front of the people who make decisions with it.
Organisations where every team reports a different number and nobody trusts the dashboard.
- Source-of-truth definitions for the metrics that matter
- A governed data model for CS, finance, and product to share
- Executive and operational views suited to each decision
A dashboard is only as true as its definitions.
When three teams report three churn numbers, a new dashboard will not fix it. The disagreement lives in the definitions. I start by agreeing what each metric means and who owns it, then build the model, then the views. The aim is one version of the truth that CS, finance and product all trust, with every view built around a decision someone actually makes.
- 04.1
Definitions first
Each core metric is written down, agreed and owned before anything is built on top of it.
- 04.2
Built for decisions
Every view answers a question someone acts on. If nobody acts on it, it does not ship.
- 04.3
Shared, not siloed
One governed model serves CS, finance and product, so the numbers match in every meeting.
Custom workflows
Automation that removes the manual handoffs between CS, support, and data — so the process runs whether or not someone remembers to.
Teams doing by hand what a well-designed workflow should do on its own.
- Mapping of the current process and its real bottlenecks
- Automations across your existing stack, not a rip-and-replace
- Documentation and ownership so it keeps running after handover
If it depends on someone remembering, it will break.
Most post-sale processes run on goodwill: a CSM who remembers to flag a risk, a manager who rebuilds the same report every Monday. That holds until the team grows or someone leaves. I map how work really moves between CS, support, sales and data, find the handoffs that fail, and automate them inside the tools you already use. The goal is a process that runs whether or not anyone remembers it.
- 05.1
Map the real process
Design starts from how work actually moves, workarounds included, not from the org chart.
- 05.2
Use the stack you have
Automations live in your existing CRM and tools. No rip and replace.
- 05.3
Documented and owned
Every workflow has an owner and a runbook, so it keeps running after handover.
Custom AI agents
Purpose-built agents embedded in your tools — for triage, insight, and drafting — with a human still holding the decision.
Organisations that want AI doing real work in customer operations without handing it the wheel.
- Use cases chosen for measurable operational relief, not novelty
- Agents grounded in your data, tools, and tone
- Guardrails, evaluation, and a clear line for human review
AI should give time back, not take the decision away.
In the teams I have led and coached, most of a CSM’s day went to operational work: reporting, inbox triage and shifting priorities. That is where AI earns its place. I build agents that carry this load, grounded in your data, tools and tone, so your people spend their time with customers. The line I hold is simple: agents surface, recommend and draft, and people decide anything that touches a relationship.
- 06.1
Start from the work
Use cases are chosen for hours saved on real tasks, not for how good the demo looks.
- 06.2
Grounded and guarded
Agents work from your own data and know when to say they do not know.
- 06.3
A human holds the pen
Drafts and recommendations are automated. Decisions that carry a relationship stay with people.
Let’s talk aboutwhat’s next.
Tell us where customer success, data, or operations is holding your organisation back. We'll tell you honestly if we can help.
Based in India · Working globally