# Mapping the SaaS data landscape: sources, systems, and owners
A single free-trial signup at a mid-size SaaS company can trigger data writes to six different systems in under ten seconds: a product analytics event, a CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.Voir la définition complète → lead record, a billing account shell, a marketing attributionmarketing attributionA framework for assigning credit to the touchpoints that contributed to a conversion, so you can measure which channels and interactions actually drive results.Voir la définition complète → touch, a support ticket eligibility flag, and a data warehousedata warehouseA central repository that consolidates data from many source systems into a structured, query-optimized store designed for analytics, reporting, and business intelligence.Voir la définition complète → sync job. None of these systems agree on what to call the customer. This is the SaaS data landscape, and mapping it is the first job of anyone doing analytics, finance, or ops in the sector.
Most SaaS "data problems" are not analytics problems. They are ownership problems. A churn number looks wrong not because the SQLSQLSales Qualified Lead: a prospect the sales team has validated as ready for direct outreach and a proposal, having passed clear qualification criteria.Voir la définition complète → is bad, but because billing defines "customer" as an active subscription while product defines it as a logged-in workspace.
A source map is a simple artifact: for each dataset, who owns it, where it lives, what it's used for, and what breaks it. Before building metrics, build this mapmapUsing software to automate repetitive marketing tasks and campaigns, enabling personalisation at scale across channels like email, web, and social.Voir la définition complète →. It prevents the single most common failure mode in SaaS analytics: two teams presenting different numbers for "the same" metric in the same board meeting.
This is event-level data: logins, clicks, feature adoption, APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète → calls, session length. Captured via instrumentation tools like Amplitude, Mixpanel, or Segment (a customer data platformcustomer data platformA Customer Data Platform unifies customer data from all sources into persistent, actionable profiles that other systems can use.Voir la définition complète →, CDPCDPA Customer Data Platform unifies customer data from all sources into persistent, actionable profiles that other systems can use.Voir la définition complète →, that routes events to multiple destinations).
Lives in systems like Stripe, Chargebee, or Zuora. This is the system of record for MRRMRRMonthly Recurring Revenue: the predictable, normalized monthly revenue from active subscriptions, the baseline metric for SaaS and subscription businesses.Voir la définition complète → (monthly recurring revenuemonthly recurring revenueMonthly Recurring Revenue: the predictable, normalized monthly revenue from active subscriptions, the baseline metric for SaaS and subscription businesses.Voir la définition complète →), plan tier, seat count, discounts, and payment status.
Salesforce or HubSpot records: leads, opportunities, deal stages, contract terms, renewal dates. This is the sales-side narrative of the customer.
Zendesk, Intercom, or Gainsight tickets, NPSNPSNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.Voir la définition complète → (Net Promoter ScoreNet Promoter ScoreNet Promoter Score (NPS) measures customer loyalty by asking how likely customers are to recommend a brand, then subtracting detractors from promoters.Voir la définition complète →) surveys, health scores. This captures customer sentiment and friction.
Ad platforms (Google Ads, LinkedIn), web analytics (GA4), and attributionattributionA framework for assigning credit to the touchpoints that contributed to a conversion, so you can measure which channels and interactions actually drive results.Voir la définition complète → tools. Captures CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.Voir la définition complète → (customer acquisition costcustomer acquisition costCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.Voir la définition complète →) inputs: spend, channel, campaign, conversion.
A usable source mapmapUsing software to automate repetitive marketing tasks and campaigns, enabling personalisation at scale across channels like email, web, and social.Voir la définition complète → has five columns. Here's a compressed example:
| Dataset | System | Owner | Grain | Common failure |
|---|---|---|---|---|
| Product events | Amplitude/Segment | Product Eng | Event-level | Renamed/untracked events |
| Subscriptions | Stripe/Chargebee | Finance | Account-level | ID mismatch with CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.Voir la définition complète → |
| Deals/accounts | Salesforce | RevOps | Account-level | Manual entry, duplicates |
| Tickets/health | Zendesk/Gainsight | CS | Ticket-level | Stale scores, sentiment conflation |
| Campaigns/spend | GA4/Ad platforms | Marketing | Session/campaign | Attribution modelAttribution modelA framework for assigning credit to the touchpoints that contributed to a conversion, so you can measure which channels and interactions actually drive results.Voir la définition complète → conflict, consent gaps |
The critical column most teams skip is "common failure." Naming the failure mode in advance is what lets you build monitoring for it, rather than discovering it during a board review.
The reason these five systems don't naturally agree: each uses a different key.
Reconciling these is called identity resolution, and it's usually done through a customer ID mapping table maintained in the data warehousedata warehouseA central repository that consolidates data from many source systems into a structured, query-optimized store designed for analytics, reporting, and business intelligence.Voir la définition complète → (Snowflake, BigQuery, Databricks are the common platforms in 2026).
A simplified mapping query looks like this:
-- Simplified identity resolution: join product usage to billing account
SELECT
p.user_id,
p.account_id AS product_account_id,
b.subscription_id,
b.crm_account_id,
c.salesforce_account_name
FROM product_events p
LEFT JOIN billing_accounts b
ON p.account_id = b.external_account_id
LEFT JOIN crm_accounts c
ON b.crm_account_id = c.account_id
WHERE p.event_date >= CURRENT_DATE - INTERVAL '30 days';If product_account_id and crm_account_id don't reliably mapmapUsing software to automate repetitive marketing tasks and campaigns, enabling personalisation at scale across channels like email, web, and social.Voir la définition complète → 1:1, every usage-based churn or expansion metric downstream is suspect. This join failing silently is one of the most common root causes of "the dashboard numbers don't match" incidents in SaaS companies.
For a deeper technical reference on building this kind of pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète → discipline, the dbt Labs glossary is a solid, free primer on analytics engineering concepts referenced throughout this module.
Vérification des acquis
1. A churn metric looks different between the billing team and the product team. According to the lesson, what is the most likely root cause?
2. Why should a team build a source map before building metrics or dashboards?
3. A developer renames the event 'signup_complete' to 'user_created' in the product analytics tool, and no error is thrown. What does this scenario illustrate?
4. Select ALL correct answers about a 'source map' as described in the lesson.
Sélectionnez toutes les réponses correctes.
5. Select ALL correct answers about product telemetry (usage data) in SaaS companies.
Sélectionnez toutes les réponses correctes.
Ownership disputes are the norm, not the exception, in SaaS data. A few patterns worth knowing:
Governance frameworks worth knowing by name: the DAMA-DMBOKDAMA-DMBOKData Management Body of Knowledge, référentiel de l'association DAMA définissant les 11 domaines de gestion des données (gouvernance, qualité, architecture, sécurité, etc.). (Data Management Body of Knowledge) is the standard reference framework for data governancedata governanceData governance is the set of policies, roles, and processes that ensure data is accurate, secure, well-defined, and used responsibly across an organization.Voir la définition complète → roles and responsibilities, useful if you want a formal vocabulary for these ownership conversations.
🎬 [VIDEO: "Data GovernanceData GovernanceData governance is the set of policies, roles, and processes that ensure data is accurate, secure, well-defined, and used responsibly across an organization.Voir la définition complète → Explained" - youtube.com - search for recent DAMA or Data Council talks explaining stewardship and ownership models in modern SaaS data stacks]
1. The renamed event. Engineering ships a refactor, renames trial_started to trial_activated. Growth's activation dashboard flatlines. Nobody notices for two weeks because no alert was tied to that event's volume.
2. The billing/CRM identity drift. A customer is acquired by another company, renamed in Salesforce, but the Stripe account still shows the old legal name. Revenue reporting by "customer" undercounts the true logo count.
3. The attribution war. Marketing reports CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.Voir la définition complète → using last-touch attributionattributionA framework for assigning credit to the touchpoints that contributed to a conversion, so you can measure which channels and interactions actually drive results.Voir la définition complète →; Finance reports CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.Voir la définition complète → using fully-loaded spend divided by new logos. Both are "correct" by their own definition. Without a documented source mapmapUsing software to automate repetitive marketing tasks and campaigns, enabling personalisation at scale across channels like email, web, and social.Voir la définition complète →, this becomes a recurring, unproductive argument rather than a five-minute reconciliation.