Marketing data strategy overload: Why more data isn't making us smarter (According to our research)

If you're reading this, we're probably not telling you anything new. You've sat in those meetings, sweating while trying to prove your campaigns actually worked. You've hoped they'd ask about the metrics you have ready and not the dozen others you have no idea how to find.

Here's what we found when we dug into how 6000 companies actually use their data: teams are pulling 230% more data than they did in 2020. But most barely glance at it, let alone turn it into anything useful.

Marketing teams are collecting more data than they can handle

• Between 2020 and 2024, we saw a dramatic increase in data usage shift. Marketers are: Getting data more often: We see from our platform that the average query count—meaning how many searches for marketing data marketers perform— grew by 50%
• Dealing with significantly more data: The average rows returned—meaning how much data they get from each search—grew by 230%

It doesn’t necessarily mean that teams are using more marketing channels. Rather, they're going deeper on everything—think more metrics, more breakdowns, longer date ranges.

However, you can have too much of a good thing when it comes to marketing data. Here’s what’s happening: this extra data isn't making teams smarter. It's creating the opposite effect—more confusion, stress, and unproductivity.

Nobody has time to look at all this stuff

• We asked marketers how they're actually dealing with all this data: 56% can't find time to analyze their data properly
• 38% don't have the right tools to make sense of it all
• Only 7% feel like they have enough time to work with their data
• 32% check their marketing reports once a month (or less)

So teams are collecting mountains of data, but can't answer simple questions like "which channel works best?" It's like having a library but no time to read.

When data collection becomes counterproductive

Zach Bricker, our Lead Solutions Engineer, sees this challenge regularly.

"It's easy to end up with too much data. You lose sight of the big picture and spend hours examining details that don't move the needle. You're focusing on individual trees instead of understanding the forest. When you can't clearly explain what drives your performance, you've likely collected too much."— Zach Bricker, Lead Solutions Engineer, Supermetrics

If you're gathering every available data point, you might be working against yourself because:

• The data becomes too granular to provide a clear direction
• You can't aggregate it effectively
• You end up with numbers that don't accurately reflect performance

What "good enough" data looks like

Bartosz Schneider, our Principal Data Strategist, has a great way to think about this. He compares it to being a doctor. When someone comes in sick, you don't run every test possible. Instead, you focus on what matters for the diagnosis.

"If I just take someone's temperature every 10 minutes and pile up data but never define what's good or bad, the data is useless. I'll drown in it. The same thing happens in marketing. Data without context doesn't help."—Bartosz Schneider, Principal Data Strategist, Supermetrics

Instead of trying to track everything, most teams would be better off going back to basics. Pick the core numbers you need for your main KPIs and actually use them.

Good data should be:

• Accurate — No errors or old information
• Complete — You're not missing key pieces (for the questions you're trying to answer)
• Relevant — Actually connects to your goals
• Valid — You can trust it
• Fresh — Updated when you need it

Maintaining data quality requires ongoing monitoring and validation. Processes in place to regularly check your data sources, identify inconsistencies, and address quality issues ensure that your marketing decisions are based on reliable information.

Learn more about marketing data quality best practices to establish monitoring systems.

Using Supermetrics you can build an automated dashboard to monitor your marketing data quality.

You don't need real-time data for everything

When it comes to how often marketers check their reports, our research shows:

• 46% of marketers review reports weekly
• 25% check monthly
• and 21% look daily

There’s no one-size-fits-all answer. In fact, you need data refreshed at the speed you make decisions. If you're making weekly strategy adjustments, daily data works well. If you're optimizing campaigns throughout the day, then real-time updates make sense. But most marketers aren't operating at that pace.

Additional resources: Data-driven marketing decisions: Improve the quality and speed of decision-making

How to build a better marketing data collection approach

The key is working backwards from the questions you need answers to. Here's how to escape the data trap:

Focus on being data-informed, not data-driven

There’s an important distinction here.

Being data-driven means letting data make your decisions automatically, i.e., following numbers blindly without context. Being data-informed means combining data insights with your marketing expertise and intuition to make strategic decisions.

Don't follow data blindly. Your gut feeling and experience should still be the driver. Figure out what you really need to know before you start collecting information.

You’ll always need experienced marketers to interpret results and make strategic decisions based on data and market understanding.

Start with your questions, then identify the data you need

You're more likely to have too much data than too little. The right amount is what you have time to understand and act on. Instead of collecting everything available, work backwards:

1. What business questions do you need to answer?
2. What measurements are needed to answer those questions?
3. What specific data points are required for those measurements?

While it’s an approach that limits your data collection, it also helps you identify what’s actually useful for your core KPIs. Beyond that, additional data creates noise instead of clarity.

Get team alignment on what matters

Many teams struggle to agree on their core metrics and KPIs. Before you worry about the technical details, define what you're measuring and why. Having clear consensus on success metrics prevents teams from chasing vanity metrics or getting lost in data that doesn’t drive decisions.

Accept "good enough" over perfect

Perfect data doesn't exist. Focus on getting your team to consistently use reliable data before adding complexity. You’re better off with 80% accurate data that gets used daily than 99% perfect data that sits ignored because it’s too complex to access or understand.

After all, individual data points can fluctuate daily. But the underlying trends remain consistent. It’s better to focus on the patterns and not the variations.

The path forward

The solution to your measurement challenges isn't more data. You need the right data, delivered when you need it, in a format that enables clear decision-making.

You don't need to become a data scientist to use marketing data effectively. Sometimes, confirming your strategic instincts with solid data is enough to move forward confidently and secure leadership buy-in.

Ready to optimize your data approach? Focus on the metrics that directly impact your business goals, and resist the temptation to track everything simply because you can.