3 Common Traps Marketers Fall into with Data

I’ve had the opportunity of working with many marketers from various industries and enterprises.

I can tell you that all marketers are aware that data is an integral part of data-driven marketing in the current day in age.

However, I’ve learned that many marketers fall into at least one of three traps when it comes to data.

1. Expecting analytics tool to be a magic fix
2. Distrust in data – not tracking good data
3. Not working with data outside of marketing

This article discusses how these three common mistakes can hurt your business and potentially your marketing career.

Expecting analytics tool to be a magic fix

Marketers are often guilty of starting the wrong approach. They usually begin with the tools of the trade rather than determining what they want to accomplish and then finding ways to measure these outcomes.

This approach is a grave mistake that can lead you down a path that is less than effective.

Marketers have many options for tracking data, but the trick is being smart about which data you track and how.

Begin by asking yourself what your goals are as a marketer. These goals should be measurable and specific to your business goals as well as marketing goals. Once you have those nailed down, it will be easier to figure out.

Many marketers struggle to identify and integrate the right mix of technologies for their marketing teams. One common mistake is over-reliance on new tools, which may not solve the core problems at all.

Marketing technologies are interdependent. No single platform does it all, and the success of a technology you use to measure ROI hinges on whether or not they can make integrations with other marketing systems to be fully effective.

Example marketing technologies include BI solutions, attribution software, marketing automation tools that enhance your brand’s digital presence across multiple channels based upon customer behavior patterns.

Any one of these is great when used alone but difficult if there aren’t good integration points between each system.

While it’s natural to want to improve your programs with technology, we’ve seen that it can lead down a slippery slope as you seek out additional tools because they might be “the answer” or just another option in an already full toolbox.

So instead, keep working away at progress by staying focused on listening closely and communicating clearly within your team about what works best for them to do their jobs.

Distrust in data – not tracking good data

A new study by Vanson Bourne found that most IT Decision Makers distrust data because the data analytics process is not effective or flawed.

82% of organizations think that data analytics are important, but in 84% of cases, data projects are delayed because the data is in the wrong format.

And in 82% of cases, poor quality data makes it difficult to do any work with it.

Because of these data issues, 76% of people said that they missed revenue opportunities.

There are also 72% of people who believe this distrust has impacted that customer engagement and satisfaction.

In addition, 68% think that the organization is slower than competitors to react to market changes because of this distrust.

Improving data quality for analysis can be done by making it easier to access, cleaning and standardizing the data, modernizing infrastructure that stores the information, and integrating all of these siloes.

According to the study, when asked “what was needed to improve data quality for analysis,” respondents noted some key areas that need better data cleaning and standardization.

However, they also added on even more important things such as modernization of infrastructures or integration with other sources, which are called out in particular because over half (53%) call them outgrowing problems behind their lack of trust.

The distrust in data will continue to grow as changes in iOS, and third-party cookie blockers continue to impact data and measurement.

As a result, marketers will need to find best practices and use the tools to work with these emerging technical challenges.

Marketers will need to know what works best for your company to obtain your desired results.

Therefore, it may be a great idea for you to learn how marketing data collection technologies work.

Not working with data outside of marketing.

In some businesses, they only measure the ROI of a marketing campaign. But this can be a mistake. You can focus on one side of the equation and forget to deal with the other part.

They may not know how much their investments are costing them or if their marketing is working well.

If you do not know your investments, there is no way to tell if your campaign is going well.

Marketers need to have a good relationship with Finance. Marketing needs to work closely with people who are in charge of the money.

Relationship with Finance is important because they need to ensure that their data is accurate, has all the information it needs, and is structured to use it. If you want to measure ROI, do this early on and make sure Finance agrees with your plan every step of the way.

Sales also have many data that are in the best interest of marketers. Often, marketers are trying to drive leads or engage prospects, and it ends there. But sales can tell you more.

For example, most sales organizations are working with warm leads and have experiences sharing what opportunities or client profiles are great. You can then use this feedback to do better marketing, and it will help you build great campaigns overall.

Data siloes are very common as companies grow. So it is not surprising that marketing and other teams do not see things eye to eye.

Great marketing integration with other departments prevents bad decisions that can cause lost revenue or opportunities. Marketers need to build good relationships with Finance or sales to know what works and the reasoning behind certain numbers, which will help them get actionable insights.

In Summary

Marketing with data is a process that requires patience and dedication. Too often, marketers fall into the trap of expecting analytics tools to be a magic fix for their marketing woes or not trusting in their own company’s data because it feels like they don’t have enough time to track everything.

But suppose you work hard with your team to identify what good data looks like, analyze this information together, and partner up outside of marketing teams with other departments. In that case, you can start seeing success.

The truth is, data can be a valuable tool for your business. But it requires much work to get the results you want, and this starts by knowing what kind of information you need and what tools will work best for you.

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