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Treat Data Like a Team Member to Succeed in Marketing Communications

Leo Integrate

It's an understatement to suggest that data is critical to an organization's sales and marketing work. It's vital. That said, I'm here to discuss what your relationship with data needs to look like in order for you to be successful using data to make decisions.

Simply put, salespeople and marketers need to  treat data as a member of the team. Assuming, of course, you provide members of your team with respect, kindness, emotional intelligence, and mentorship.

You also need to remember that data is not the same as analytics — data is the raw metrics, and analytics is the analysis or the interpretation of data. They should work together and inform one another, but they are different things. But these two words are often used interchangeably. I’ve seen this seemly small mistake negatively impact research projects, purchasing of enterprise SaaS technology, and so on.

Insight from a marketing communications professional:

My marketing and sales work has always included the collection, analysis, and presentation of data. But my understanding is limited when you compare it to what a marketing analytics professional tackles every day. So, for the overview below, I’ve tapped into the extensive knowledge and deep experience of  Michael Lynch. Michael has over 20 years of experience in marketing and business analytics and is a professor of the  Data Marketing Communications at WVU's Reed College of Media.

Here's what he had to say about treating data like a team member.

"Like a team member that makes valuable contributions to your team, data need to be guided and developed. Like a good team member, one should always make sure that you have the right person for the job. For example, are you capturing relevant data that will lead you to valuable conclusions? Often, the right person is hired, but, without proper training, that person ends up not doing the intended work. A company with which I worked did an excellent job of gathering birthdays and were very effective at delivering birthday messages and rewards. The data collected did not include a year of birth, so no useful demographic analysis could be done.

Speaking of birthdays, when the contact people were forced to enter years of birth, I ended up with a disproportional number of customers who were born in 1999 or 2000. I ignored these records until I started having customers who were born in 1999 and 2000. I could not distinguish one from the other, and my data and results were again flawed.

Nothing is worse than “dirty data.” Not having an employee is better than having a counterproductive employee, and no data are better than dirty data. Do not fill a position, and I will figure out how to get the job done. Leave fields blank, and I will ask the customer for the information or I might contract with an outside company to get the information for me. (You would be shocked to know how much information is available about people.) If you are sloppy and do data entry incorrectly, I will assume that the data are correct and will not try to fix the problem. 

Data tells a story. Sometimes trying to understand the story from your data is like listening to a three-year-old tell you about their trip to the zoo. Unless you can keep your data-focused, you could get caught up in minutia and miss the part about the boy who fell into the gorilla cage and had to be rescued. Sometimes essential details are lost or omitted unless you know how to identify the important stuff. The other side, though, is that you do not want to guide your data toward predetermined outcomes or assumptions. Again, if you keep focusing on and asking about the lions and tigers, you will miss the essential details about the boy in the gorilla cage.

Your data limit must be accessible. If you could only interact with a team member once every other day during a period, that team member would not be as valuable to you. Your data must also be accessible by the right people. Too often, the rudimentary running of data queries is left to people with computer science backgrounds. They might technically be excellent, but like an expert running a steam shovel, they will not recognize the chunks of gold that are being displaced with all of the gravel and dirt."

A team is only as effective as the sum of its parts, including the individual roles of data and analytics in your marketing team. Data must be focused and fulfill all of its duties to allow for analysis to take place and do its job. Organized, focused analysis of collected data allows for a story to be revealed. This story, rooted in fact, can drive the collective decisions of the rest of your team members for streamlined decision making and cohesive outcomes.

Are you ready to harness the power of data?

West Virginia University’s  Data Marketing Communications program is the nation’s first online master’s degree explicitly focused on the impact of data on marketing communications. To succeed in our Data Marketing Communications program,  you  need the ambition and the analytical skills to interpret data to assess metrics, measure productivity, increase ROI, and develop integrated marketing strategies. 

Ready to get started on your Data Marketing Communications journey?  Contact us today to learn more about how you can begin to make a difference in your marketing career!

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