Your campaign didn’t fail because you picked the wrong channel. It failed because the person who could change it couldn’t read the numbers, and the person who could read the numbers couldn’t change it.
- Most marketing teams know they’re weak on data
- Hiring an marketing analyst next to your digital marketer doesn’t automatically fix it
- Real money can hide in that gap
- So, does every marketer need to become an marketing analyst?
- Can one person actually have both skill sets?
- What should teams actually do?
- Check your own setup
- The short version
That is the disconnect.
Modern marketing produces more data than ever, but having the data and being able to act on it are two different things. The real advantage comes when marketing execution and analytics are close enough that an insight can quickly become a decision.
Highly Related
Most marketing teams know they’re weak on data
The industry is well aware of the gap.
In Marketing Week’s Career & Salary 2024 survey of more than 3,000 brand-side marketers, 36.9% identified data and analytics as the biggest skills gap in their team. Marketing Week described this as the second year running that data and analytics had topped the list.
A 2021 CMO Council study found an even broader problem: 85% of marketing teams had data-literacy gaps, with respondents also reporting difficulty using analytics for customer insight and acting on what it told them.
Now imagine your cost per lead doubles in March.
A digital marketer might say, “The algorithm changed.”
That might even be true, but it isn’t a diagnosis.
Was it one audience? One creative? A landing page problem? Higher competition? A change in conversion rate?
The numbers can help answer those questions, but someone still needs to understand both the marketing context and the data.
Hiring an marketing analyst next to your digital marketer doesn’t automatically fix it
Pairing a digital marketer with an marketing analyst can work well.
The problem starts when every important decision has to pass through a handoff.
Say your PPC campaign starts getting more expensive on Tuesday.
The marketer sees the change and knows something needs attention. The analyst can dig into the data and find where it is happening.
But if the marketer can’t interpret the numbers independently, or the analyst doesn’t understand the campaign well enough to recommend the right fix, the insight still has to travel between two people before anything changes.
That delay may be small on its own. Repeated across hundreds of decisions, it becomes a process problem.
It fails the other way too.
An analyst can build a clean dashboard showing a landing page with a 90% bounce rate, without the dashboard ever explaining why.
Slow page? Mismatched traffic? Wrong keyword intent? Weak copy?
Answering that takes marketing context, not just a number on a dashboard.
That is why the goal should not be to eliminate specialists. It should be to reduce the distance between analysis and action.
Real money can hide in that gap
This isn’t only an efficiency problem. It can be a financial one.
McKinsey analyzed roughly 400 marketing ROI engagements and reported that, in a typical range, 15% to 20% of marketing budgets could be reallocated to other activities or returned to the bottom line without reducing marketing ROI. The research was published in 2013, so it should be treated as an established example of what better analytics can uncover, not as a current benchmark.
The point isn’t that a fifth of every marketing budget is wasted.
It’s that better analysis can reveal where money is being misallocated.
Attribution is a good example of why this matters.
Email and paid social can both receive credit for the same conversion, not necessarily because either platform is wrong, but because attribution systems use different models, rules, channels, and lookback windows to assign credit. Google Analytics, for example, can use data-driven attribution or last-click models depending on the reporting setup.
The problem starts when a business reads each report separately and never reconciles the numbers against the wider customer journey.
Budget can then follow whichever report gets the most attention, rather than a more complete view of how customers actually converted.
This is where marketing analytics becomes more than reporting. The goal is to connect the numbers across the marketing system so decisions are based on a clearer picture.
So, does every marketer need to become an marketing analyst?
No.
A digital marketer doesn’t need to become a data scientist or a statistician.
But anyone responsible for making and optimizing marketing decisions should be comfortable with the fundamentals:
- Understanding the KPIs that matter
- Investigating why a metric changed
- Spotting potential tracking or data-quality problems
- Understanding the limitations of attribution
- Comparing campaigns, audiences, channels, or segments
- Interpreting a test result
- Explaining why a change was made
- Measuring what happened after the change
That’s data literacy.
And it’s a different, smaller thing than being a specialist analyst.
Can one person actually have both skill sets?
Yes.
A digital marketer who understands campaign strategy, targeting, landing pages, SEO, paid media, and creative testing, while also understanding tracking, KPI design, segmentation, dashboards, and basic experimentation, can see a problem, investigate the data, understand the marketing context, make a change, and measure what happened next.
Without necessarily needing a handoff at every step.
That doesn’t mean one person replaces every specialist.
Larger and more complex organizations can still benefit from dedicated marketing analysts, data engineers, media specialists, SEO experts, and other specialists.
What changes is that the person making the marketing decision has enough grounding in the numbers to question them, while the specialist has a clearer marketing context when deeper analysis is needed.
What should teams actually do?
1. Build analytical literacy into marketing roles
You don’t need SQL or Python in every marketing job.
You do need people who can ask:
What changed? Why? What’s the evidence? What should we do next?
Someone responsible for optimizing a campaign should be able to understand the core numbers behind that campaign.
2. Cross-train marketing and analytics teams
Instead of treating analytics as a reporting function, have both sides examine real campaigns together.
Take one campaign and walk through:
Objective → Data → Change → Cause → Decision → Result
The goal isn’t to make everyone an expert in everything.
It’s to give both sides enough understanding to collaborate without constantly translating the problem for each other.
3. Give both sides one shared business outcome
If the digital marketer optimizes for lead volume while the marketing analyst optimizes for data accuracy, they can end up solving different problems.
Anchor both to a shared business outcome.
That could be:
- Qualified leads
- Pipeline value
- Customer acquisition cost
- Revenue
- Retention
The exact KPI depends on the business.
Check your own setup
Ask yourself three questions.
Can whoever runs your campaigns explain last month’s result with a number?
If the answer starts with “it feels like,” that’s a data-literacy gap worth investigating.
Does an optimization decision regularly wait on someone else’s report?
If those questions can only be answered after a handoff, there may be an opportunity to bring marketing and analytics closer together.
Can your digital marketer explain why a change was made, not just what changed?
What evidence supported the change?
What happened after it?
If those questions can only be answered by bringing in another person, look at whether the roles, data, or reporting process could be better connected.
The short version
A digital marketer who can’t read the data guesses with confidence.
An marketing analyst who doesn’t understand the marketing context can describe problems without knowing what action makes sense.
Neither skill replaces the other.
But when they’re connected, the path from data → insight → decision → action → measurement gets much shorter.
That’s what modern marketing actually needs.
Not every marketer turned into an marketing analyst.
Not every analyst turned into a marketer.
Marketing decisions made by people who understand both what the numbers say and what the business can do about them.
You can’t fix what you can’t see.
If you want to understand where your marketing spend may be going and how attribution affects the picture, try the ROI and Attribution Calculator.
And if the numbers don’t line up with how your business actually performed, that’s a signal worth investigating.
You can also explore my case studies to see how marketing and analytics can work together in practice.
