Case Study
From Spreadsheet Chaos to a Pipeline You Can Trust
Leads were coming in from five different channels, tracked in three different spreadsheets — and no one could say with confidence which one actually drove revenue.
The Situation
A steady flow of leads, but no shared system to tell which channel actually turned into revenue.
The Challenge
Leads landed in a mix of inboxes, spreadsheets and a half-used CRM, each updated by a different person on their own schedule. By the time anyone tried to connect a booked client back to the channel that brought them in, the trail had already gone cold. Marketing spend decisions kept getting made on gut feel, because the data to make them any other way didn't exist in one place.
The Goal
Build one connected system that could track a lead from first touch to booked revenue — so budget decisions could be made on evidence instead of instinct.
Strategy & Approach
What we actually did
STEP 1
Lead Source Audit
STEP 2
Unified CRM Setup
STEP 3
Revenue Attribution Model
STEP 4
Pipeline Reporting Cadence
We mapped every place a lead could enter — forms, calls, referrals, paid — and how each one was, or wasn't, currently being recorded.
Every channel was routed into one CRM instead of three disconnected tools, with consistent fields so nothing got logged differently depending on who entered it.
We built a simple model connecting each booked client back to the exact channel and campaign that brought them in, not just the last click.
A recurring report replaced ad hoc spreadsheet checks, giving leadership one dashboard tied to revenue, refreshed on a set schedule.
The Result
Budget decisions finally had evidence behind them.
With every lead tracked through to a booked outcome, the business could finally see which channels were actually paying for themselves — and which ones had just been assumed to be working. Budget started shifting toward the channels the data actually supported, not the ones that felt the most active.
Since The Attribution Model Went Live
Metrics reflect anonymized client data pulled from tools including Google Analytics, CRM records and internal BI dashboards.