“Our data quality is terrible.”
I hear this sentence all the time.
Data teams complain about:
- broken tracking
- inconsistent schemas
- missing events
- messy pipelines
And they’re often right.
But here’s the thing:
Business executives don’t care about data quality.
Not because they’re ignorant.
But because data quality alone creates zero business value.
Let me show you what I mean.
The Day Measurement Changed Everything
Some time ago, I worked with an insurance company that was struggling with high customer acquisition costs.
Marketing performance looked mediocre.
- Customer Acquisition Cost (CAC) was high.
- Budgets were tight.
- Growth was slower than expected.
- The competition was outspending them.
So naturally, the marketing team started looking at the usual suspects:
- campaign creatives
- bidding strategies
- channel mix
- landing pages
You know the drill.
But something felt off.
Insurance customer journeys are very complex.
And they often move between online and offline channels.
A typical journey might look like this:
Someone clicks a search ad. They browse products on their phone. Later they continue research on their laptop. Then they call a sales agent. And finally they sign the contract offline.
The problem?
The measurement system couldn’t connect those steps.
From the analytics perspective, the journey looked like this:
Click → browse → disappear.
And then somewhere else in the system:
Offline sale → unknown origin.
Two separate worlds. And a very common problem.
The Invisible Half of the Customer Journey
So instead of optimizing campaigns, we looked at the measurement layer.
What we knew was:
- Customer journeys were long
- Customers switched devices frequently
- And many journeys moved from online to offline
Which meant that a big part of the journey was simply invisible.
The obvious solution was to create a soft sign-in early in the funnel.
Something simple like:
“Save your progress”
“Get your quote via email”
That would generate a stable first-party identifier (e.g. an email address) early in the journey and allow us to connect sessions, devices, and backend conversions.
But there were two problems.
- First, the business felt this would be too invasive early in the funnel
- Second, implementing it would take months of product work.
So we kept digging.
Until we struck gold.
While analyzing the funnel, we realized something interesting.
Users were already leaving a specific combination of data points voluntarily as part of the normal insurance quote process.
Individually, these data points weren’t unique.
But combined, they became extremely powerful.
It turned out that this combination could be used to match:
- abandoned online sessions
- with completed contracts in the backend
With over 99% accuracy!
→ No login required.
→ No new tracking mechanism.
→ No invasive changes to the user experience.
We were simply using existing first-party data more intelligently.
So we rebuilt the measurement logic to stitch these pieces together.
Suddenly we could reconstruct large parts of the customer journey that had previously been invisible.
And what happened next was… surprising.
When Reality Becomes Visible
Once the journeys were connected, something became immediately clear.
A huge share of customers who started their journey online were actually finishing it offline.
The marketing channel hadn’t changed.
Reality hadn’t changed.
We had simply started measuring it correctly.
And the impact?
Attributed sales for Google Ads almost doubled overnight.
Which meant something else.
Customer acquisition costs were suddenly almost half of what we thought they were.
- Same campaigns.
- Same creatives.
- Same budgets.
Just better measurement.
The Real Growth Lever
The growth lever wasn’t better marketing.
The growth lever was better visibility into reality.
And this is where most data teams get something fundamentally wrong.
They frame their work like this:
“We need better data quality.”
But that’s an output, not an outcome.
No executive wakes up in the morning thinking:
“We really need better event schemas today.”
They care about:
- revenue
- efficiency
- growth
- margins
- And, in this case, CAC
If data quality improvements don’t clearly connect to those outcomes, they will always feel like technical housekeeping.
The Problem With “Data Quality Projects”
I’ve seen this many times.
Data teams launch initiatives like:
- Data governance programs
- Data quality frameworks
- Tracking overhauls
And then they wonder why the business isn't excited.
Because the value proposition sounds like this:
“Our dashboards will be more accurate.”
That’s not a business outcome.
That’s a technical improvement.
But when you frame the same work like this:
“We are currently underestimating the performance of our biggest growth channel. If we improve data quality, we can better allocate marketing budgets, outspend our competition on Google Ads and grow faster than everyone else in our industry.”
Now people start paying attention.
The Question Data Teams Should Ask
Instead of asking:
“How can we improve data quality?”
Ask this:
“Which decisions are currently based on incomplete reality?”
Because those are the real opportunities.
Measurement gaps distort how companies behave.
They cause companies to:
- underinvest in profitable channels
- overinvest in weak initiatives
- optimize the wrong parts of the funnel
- misdiagnose performance problems
Bad measurement doesn’t just create bad dashboards.
It creates bad strategy.
The Mindset Shift
So here’s the shift I want more data teams to make.
Stop selling data quality.
Start selling decision improvement.
Instead of saying:
“We need cross-device tracking.”
Say:
“We’re currently making budget decisions based on incomplete customer journeys and we are overestimating CAC by up to 2x.”
Instead of saying:
“Our identity resolution is weak.”
Say:
“We are underestimating the lifetime value of entire customer segments.”
Instead of saying:
“Our data quality is poor.”
Say:
“We might be making million-dollar decisions on distorted signals.”
Now the conversation changes.
Bottom Line
Data quality is important.
But data quality alone doesn’t create value.
The value appears when better data changes a decision.
When better measurement reveals hidden opportunities.
When the business suddenly sees reality more clearly.
Because sometimes the biggest growth lever isn’t:
- better campaigns
- better products
- better strategies
And sometimes the biggest growth lever is simply this:
Getting the business to buy into initiatives that help us understand what’s actually happening.
Until next week!
Cheers,
Sebastian
