GTM Engineering · RevOps Systems · Analytics · Governance
The GTM Data Reliability Playbook (Definitions, Governance, Trust)
A practical framework to move from scattered dashboards to trusted GTM data systems.
Great GTM decisions start with data people actually trust. The fastest way to lose trust is a metric that changes definition depending on who asks. The goal of a reliability playbook is to make data dependable, discoverable, and explainable.
1. Establish the metric spine
Create a short list of non-negotiable definitions and make them the root of every report.
pipeline:
definition: "Qualified pipeline created in a period"
source: "salesforce.opportunity"
owner: "RevOps"
fields:
- stage
- created_date
- amount
2. Build a governed warehouse layer
Centralize your GTM sources and make the warehouse the system of record.
create or replace view mart_pipeline as
select
opportunity_id,
created_date,
amount,
stage,
owner_id,
region
from raw_salesforce_opportunity
where is_deleted = false;
3. Create data contracts with the business
Data contracts are written agreements about what a field means and when it changes. They prevent quiet breakage.
const contract = {
metric: 'pipeline_created',
definition: 'Opportunity created_date in period and stage >= SQL',
owner: 'RevOps',
upstreamDependencies: ['salesforce.opportunity.stage', 'salesforce.opportunity.created_date'],
changeProcess: 'Announce in #revops-data, document, release weekly'
};
4. Monitor reliability, not just freshness
Reliability means the data matches the reality of GTM. Check for drift, duplicates, and missing fields.
def validate_pipeline(df):
assert df['amount'].notna().all()
assert df['stage'].isin(['SQL', 'SAL', 'Discovery', 'Proposal']).all()
5. Close the loop with enablement
A metric that is technically correct but poorly explained still loses trust. Pair every release with enablement.
Checklist
- Definition doc is updated
- Stakeholders see the change before it ships
- Dashboards show the “why” behind the number
Final takeaway
Reliability is a product. Treat your GTM data system like one: clear definitions, strong governance, and continuous feedback.