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What We Build - Revenue Operations Services

Most companies do not have a RevOps strategy problem. They have a RevOps implementation problem: someone has already written down what the process should be, and there is no capacity to make the systems enforce it.

We build that layer. CRM architecture that matches how you actually sell, definitions enforced through validation rather than training, automated data quality, and reporting that survives a pipeline redesign.

4 min read5 sectionsWhat We Build

What you'll take away

  • We implement rather than advise. The output is working systems, not a deck.
  • Definitions become validation rules, so process stops being optional.
  • Reporting is built on a warehouse, so last year's numbers still make sense next year.
  • Fixed scope, code in your accounts, documented handover.

What the engagement covers

CRM architecture and data model
Object model matched to how you actually sell — subscriptions, multi-product, partner-sourced, land-and-expand — with required fields, validation rules and picklist standardisation.
Definitions made enforceable
Stage exit criteria, qualification thresholds and lifecycle transitions implemented as system rules rather than documented as guidance nobody rereads.
Data quality automation
Normalisation, deduplication with a review queue, stale record management and validation monitoring — running on a schedule with dry-run safety and audit logging.
Forecasting infrastructure
Stage transition history, pipeline snapshots and automated accuracy measurement. The prerequisites for a forecast anyone can defend.
Warehouse and reporting layer
Metric definitions in version control, warehouse models joining CRM, product and billing data, and dashboards that do not break when a field is renamed.
Territory, quota and comp modelling
Automated calculation from CRM data rather than a spreadsheet at month end, removing a recurring source of disputes.

How we work

  1. Audit the current state

    We document existing definitions, stages, tools, reports and manual processes exactly as they are, and quantify the manual hours being consumed. Uncomfortable to read and the most useful artefact of the engagement.

  2. Agree the target model

    Definitions, stages, exit criteria and handoff SLAs, signed off by marketing, sales and customer success leadership. We facilitate; you decide. Nothing gets built on an unresolved disagreement.

  3. Rebuild the data model

    Object model, required fields, validation rules and ownership logic implemented in your CRM, with existing records migrated and reconciled.

  4. Automate enforcement and hygiene

    Routing, enrichment, normalisation, deduplication and stale record jobs deployed with monitoring, so the process holds without anyone policing it.

  5. Build the reporting layer

    Warehouse models, metric definitions in version control, snapshot history and the dashboards your leadership actually uses.

  6. Hand over with documentation

    Runbooks, a data dictionary, architecture notes and a working session with whoever owns it next. Plus a quarterly review checklist, because RevOps output decays without maintenance.

What you get

A documented data dictionary
Every field, its owner, its definition and what depends on it. The artefact most revenue organisations have never had.
Enforced process in the CRM
Validation rules, required fields and lifecycle logic so the agreed process is what the system actually permits.
Automated hygiene jobs
Running on a schedule with monitoring, dry-run capability and audit logging on every change.
Warehouse and reporting infrastructure
Models, metric definitions in version control and snapshot history that makes cohort and trend analysis possible.
A measured baseline and result
Forecast accuracy, data quality rate and manual hours measured before and after, so the value is demonstrable.

When teams call us

Table 01
The situations that most often start a RevOps engagement.
SymptomUnderlying causeWhat we build
Three people, three different win ratesDefinitions live in three placesData dictionary, validation rules, single reporting layer
Forecast accuracy below 80%Stages advance without evidenceExit criteria as required fields, snapshot history, accuracy tracking
A quarterly data cleanup that never holdsHygiene is manualScheduled normalisation, deduplication and stale record automation
Reports break after every process changeBI built directly on the CRMWarehouse models with versioned metric definitions
Commission disputes every monthComp calculated in a spreadsheetAutomated calculation from CRM data with an audit trail
New CRM, same problemsMigration without model redesignObject model rebuild matched to the actual sales motion

Why teams choose us for this

We build, not just advise
Most RevOps consulting ends with a recommendation. The gap between a recommendation and a working system is where the value is, and that gap is engineering work.
Engineering practice, not tool configuration
Logic in version control with tests and monitoring. This is what makes the difference between something that works now and something still working in two years.
We work with your existing stack
No platform migration unless you want one. We build against what you have and tell you honestly if something needs replacing.
Fixed scope
Defined deliverables and a fixed price agreed before work starts. RevOps projects have a reputation for expanding indefinitely; ours end.

Frequently asked questions

What do RevOps services actually include?

CRM architecture and data model design, definitions implemented as validation rules, automated data quality jobs, forecasting infrastructure including stage history and pipeline snapshots, warehouse-based reporting, and territory and compensation modelling. Delivered as implementation, not as recommendations.

Do we need RevOps if we already have a RevOps manager?

Often yes, and for a specific reason: RevOps managers can design but usually cannot build. The most common gap we fill is between a good RevOps roadmap and the engineering capacity to ship it.

How long does a RevOps implementation take?

A focused engagement — data model rebuild, enforcement automation and reporting layer — typically runs eight to fourteen weeks. The audit and definition-agreement phase is usually two to three weeks of that and is the part most often underestimated.

Will this require changing our CRM?

Usually not. Most problems we see are data model and enforcement problems rather than platform problems, and a migration typically costs three to five times the licence saving that motivated it. If a change is genuinely warranted, we will say so and explain why.

What happens to the systems after handover?

They are documented, monitored and run in your infrastructure. We include a quarterly review checklist because RevOps output decays by default — definitions drift, the business changes, and scheduled maintenance is far cheaper than a rebuild.
Implementation, not advice

Your RevOps plan is probably fine. It needs building.

We turn RevOps design into working systems: enforced definitions, automated hygiene, forecasting infrastructure and reporting your leadership can actually trust.