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Video Marketing  |   Reporting & Performance  |   Marketing Strategy

3 Signs Your Marketing Team is Focusing on the Wrong Data (And How to Fix It!)

Kaitlyn Petro

By Kaitlyn Petro

Mar 23, 2018

3 Signs Your Marketing Team is Focusing on the Wrong Data (And How to Fix It!)

Originally written by Kaitlyn Petro. Updated by Bob Ruffolo with support from the IMPACT editorial team.
Last updated: November 2, 2026

As a fellow marketer, I’m sure you’ll agree that it’s hard to do good work without the right information. Having data isn’t enough, though. It has to be relevant to your company and to the goals you’re trying to reach. Without good data, it’s hard to set marketing goals tied to your business goals, and just as hard to tell whether you’re reaching them.

Data should guide the decisions your marketing team makes as it plans and runs campaigns. When you focus on the right data, you understand how your audience interacts with your company, and you can see which efforts are working. When you focus on the wrong data, you’ll usually notice one or more of these three warning signs.

1. Your team isn’t aligned on goals

Without clear, shared goals, everyone on your team can end up working toward different outcomes. Your definition of success as a marketer may be completely different from a designer’s, which may be different again from a copywriter’s.

And if you don’t have the right data, or don’t know which data to focus on, your goals and strategy turn into a big assumption. Assumptions rarely lead to effective outcomes.

When everyone knows the goal, why the work matters, and how their contribution affects the result, it’s much easier to connect what the team does to what actually happens, and to keep everyone aligned from one project to the next.

2. You’re not seeing improvement in your metrics

Data is everywhere, and that’s both good and bad. It’s great to have hard numbers on your performance, but the volume can quickly become overwhelming, and it isn’t always clear which numbers deserve your attention or what to do with them.

If your team is working toward different goals or working from the wrong data, your metrics won’t improve. Start by deciding what you need to track, and let your goals make that decision. If your metrics don’t reflect your goals, you’re unlikely to improve the ones that matter. Website traffic, for example, is easy to measure, but on its own it doesn’t tell you whether marketing is producing sales conversations and customers. For a closer look at what to track instead, listen to our podcast episode on the marketing metrics that matter more than website traffic.

3. Your company looks just like your competitors

If you don’t have or follow the right data, you’ll probably look to your competitors for guidance. But a competitor doing something doesn’t mean it works. They may not have everything figured out either, and you want to stand out, not blend in.

Base your marketing decisions on how your prospects and customers interact with you, not on what your competitors or others in your industry are doing. Once you collect the right customer-centered data, you can make better-informed changes to your marketing and give buyers a clearer reason to choose you.

How can your team focus on the right data?

With so many types of data available, the challenge is narrowing it down to what will actually improve a campaign or page. One useful approach is the Data-Driven Design (3D) framework developed by Unbounce co-founder Oli Gardner, who explains the framework in his own words on the Unbounce blog.

Despite the name, it isn’t only for designers. It gives marketers, designers, and copywriters a shared process for choosing the right data for a decision, reviewing it together, and measuring whether a change worked. The steps below summarize the version Oli presented in 2018. His own write-up describes a longer, eight-step version, but the core ideas are the same.

Step 1: Narrow down the data you need

Start with the page element you want to improve, such as a form, your navigation, or a headline, and decide which data sources will actually tell you something about it. Oli built a lookup spreadsheet called the 3D Playbook for this step: you choose a page element, and it points you to the types of data worth reviewing.

Step 2: Collect the data

Gather the data you identified, and make sure your sample is large enough to support a sound decision before you draw any conclusions.

Step 3: Make observations as a team

Review the data together, whether that’s analytics, heatmaps, session recordings, survey results, or usability tests. Looking at it as a team helps everyone develop empathy for the customer and builds agreement about what needs to change. Record each observation and rate how severe the problem is. Oli’s worksheets use a scale of 1 to 5, with 5 being the most severe.

Step 4: Assign micro metrics

Every problem you observe needs a way to measure whether you’ve fixed it. Conversion rate alone won’t tell you much about what changed on the page, so assign micro metrics that measure specific on-page behavior instead.

For example, if you’re improving a form on a landing page, don’t just count submissions. Track the percentage of form errors, form abandons, fake email addresses, and business email addresses, so you can see exactly which behavior a change affects.

Step 5: Sketch solutions together

With your observations and micro metrics in hand, have each team member sketch four quick solutions, spending about a minute on each. Then discuss the reasoning behind each sketch, and give the strongest ideas to your designer to develop into a more complete solution.

Step 6: Test and measure

Make the changes and test them. Then check your micro metrics to see whether your design decisions changed how visitors behave on the page, for better or worse.

Now what?

Start with the warning sign that sounds most familiar. If your team disagrees about what success looks like, agree on goals first. If your metrics aren’t moving, check whether you’re tracking the numbers that reflect those goals. Before your next page or campaign change, try running it through the process above so everyone is working from the same data.

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