Marketing acquisition
Campaigns generate leads, but reporting stops at the click.
Interactive demo: Multinational consumer education company
Chapter 01
The same customer lived in roughly ten systems that never agreed
The first question was not which dashboard to build. It was whether marketing, sales, payments, and product could share one accepted customer history.
Requests entering separately
Sales touches
The CRM records conversations, amounts, and dates that payment records sometimes contradict.
Payment records
The commercial side collects money, but the product side cannot see who paid.
Product usage
Product analytics has a clean customer ID the commercial side cannot reach.
Systems detected & mapped
- ConnectedHubSpotCRM
Sales touches and deal records
- ConnectedSkypeMessaging
Conversations and webinar records
- ConnectedGoogle AnalyticsAnalytics
Acquisition and product behavior events
- ConnectedPostgreSQLProduct DB
Product usage and customer IDs
What consolidation changed
Before Platform
- The same customer appeared under different identifiers in every system
- Campaign reporting stopped long before revenue and retention
- Sales and payment records disagreed on amounts and dates
- No one trusted any joined view because no one had reviewed the matches
With Platform
- One accepted customer history joins acquisition, sales, payment, and usage
- Acquisition paths are traced through to retained revenue
- Uncertain matches route to a person with both records side by side
- Every entry carries its source trace
- ~10
- systems joined
- 90%+
- revenue matched to product usage
- 100%
- uncertain matches human-reviewed
- 2
- operating units on one record
Chapter 02
One accepted history, traced back to every source
The Revenue Intelligence layer reads the systems both units already use and produces one customer history both can trust.
Shared across the platform
Record normalization
Names, contacts, amounts, and timestamps are normalized into comparable shapes.
Identity matching
Confirmed identifiers match automatically. Uncertain matches route to a person.
Accepted history
One timeline per customer carries acquisition, sales, payment, and usage with source traces.
Revenue attribution
Acquisition paths are joined to payments and retention.
Configured for each audience
Commercial unit
Marketing and sales see which channels produce customers who stay.
Product unit
Product sees the acquisition path and revenue tied to usage behavior.
Leadership
Founders see one joined view of channel performance and customer lifetime.
Prepared outputs
- Channel performance view
- Customer lifetime timeline
- Revenue-to-usage match report
- Uncertain-match review queue
Chapter 03
One customer history, three operating views
Each unit reads the same history from its own angle, and every number can be walked back to its source.
The data steward reviews uncertain matches, corrects identifiers, and keeps the accepted history clean.
This role sees
- Matches waiting for review
- Source health and sync status
- Accepted history timeline
- Match confidence scores
This role can do
- Confirm or reject a match
- Flag a source record for reprocessing
- Add a manual link with a note
- Export the audit trail
Decision this view supports
Is this match safe to accept, or does it need more evidence?
Chapter 04
One sanitized customer, traced from acquisition to usage
This walkthrough uses a sanitized sample. It shows the working sequence without publishing real customers, transactions, or source configuration.
Sanitized sample request
A customer pays for a program. Which acquisition path produced them, and do they actually use the product?
Working sequence
- 01
Ingest
Read the agreed commercial and product records for the customer.
Every record enters with its source identifier and timestamp. - 02
Normalize
Normalize names, contacts, amounts, and timestamps into comparable shapes.
Different source formats now share one schema. - 03
Match
Match confirmed identifiers automatically and route uncertain matches to a person.
Nothing enters the accepted history on a guess. - 04
Accept
Add the verified customer to the accepted history with source traces.
Every entry can be walked back to its origin. - 05
Attribute
Join the acquisition path to payment and product usage.
Leadership sees which channels produce customers who stay. - 06
View
Render the same history for commercial, product, and leadership views.
One version of the customer, read from the right angle.
Chapter 05
What changed when revenue and usage shared one history
The documented design facts and what they meant for the company.
Before and after
ChangeBeforeAfter
Customer viewTen systems, ten versions of the same personOne accepted customer history with source traces
Campaign reportingStopped at clicks and leadsTraced through to revenue and retention
TrustNo record of which matches were checkedUncertain matches always reviewed by a person
Decision speedQuarterly spreadsheet projectsDaily joined view of channel performance
- ~10
- systems joined into one history
- 90%+
- revenue matched to product usage
- 100%
- uncertain matches human-reviewed
- 2
- operating units on one record
What the team received
Accepted customer history
One timeline per customer with acquisition, sales, payment, and usage source traces.
Matching rules
Documented rules for confirmed and uncertain matches.
Review workflow
A queue that routes uncertain matches to a person with both records side by side.
Attribution views
Views joining acquisition to retained revenue for both operating units.