Steps For A Solid Marketing Data Strategy Part 1: What Problems It Solves

Steps For A Solid Marketing Data Strategy Part 1: What Problems It Solves

Despite conferences and videos on how data will affect the future, digital marketing employees are having a hard time knowing how to implement a marketing data strategy or get buy-in from upper management.

This 4 step marketing data strategy will help in planning how to approach this problem from scratch and gaining clarity on how exactly a good strategy can help with concrete reasons. 

We’ll go over value-adding reasons why your company should have a marketing data strategy, what problem a good data strategy solves, and why it’s time to stop putting it behind your priority list. Next, we’ll go over the last step: exactly how to approach building a marketing data strategy from the ground up.

Table Of Contents


  • Why Your Company Should Have A Marketing Data Strategy (3 Reasons)
  • What Problems A Good Data Strategy Solves
  • Why It Needs To Be At The Top Of Your Priority List
  • How To Approach Implementation

1. Why Your Company Should Have A Marketing Data Strategy

Data is a big topic these days and it touches nearly all industries. Most companies have had some sort of a lecture that says data is the currency of the future, which is true. However, the problem most marketing employees have is figuring out how it applies to them, and what they personally can do with marketing data to help the business. 

Figuring this out is crucial to getting buy-in from upper management, so preparing an air-tight plan is very important. These reasons below will help you get started with brainstorming so you can see exactly how a marketing data strategy can add value. 

 

Time 

Time is money, and that’s definitely true in the marketing and business world. In businesses today, there’s so many projects going on at one time and so many data sources needed. Without a proper form of organization, so much time is wasted in creating unnecessary data sources that don’t add value, are irrelevant, or just plain, slow, and cumbersome to use.

 With confusion over which data source is the right one or the main one, it takes such a long time for everyone to be on the same page. This means that projects are done late, people get mad, and there are late meetings with marketing VPs to figure out exactly what went wrong. 

You don’t want to be there. Nobody wants to be there. The best way to avoid it altogether is to spend time coming up with a long term data solution so data organization is seamless and easy. No confusion = no mess. 

Action Item: One way to convince upper management for a buy-in is to highlight a couple scenarios you’ve had where projects could’ve been done faster if a solid marketing data strategy was in place. Address exactly what went wrong and what data systems need to be in place for a quicker turnaround time.

 

Cohesiveness

The best organizations are the ones who work together like a well -oiled machine. In terms of data management, this means that everyone should know what data sources are being used for the project, where they are located, and how reliable they are. Ideally, there should also be limited access to the data sources so everyone is not always changing the data. If the data source is open to everyone, there should be a log to document each data change, who did it and at what time. 

Cohesiveness is what makes marketing teams work together and complete projects on time. It makes rapid changes simple to deal with and protects the company from any massive missteps such as accidentally deleting data. Having a backup plan that employees are aware of reduces the risk of such problems happening. 

Action Item: This will be explained more in Step 4 (in data storage), but write out a backup plan for your data. If something happens to it, or someone erases it, what should be the next step? Who should that person contact? Would it be someone in the company who is handling your data, or someone outside the organization? Mistakes happen, it’s how we react to them that’s important and having a plan in place is a good first step. 

 

Inconsistencies 

There’s a very good chance that data sources in your organization are not looked at daily in fine detail. No worries, this is how most companies are. Especially in marketing when there is so much focus on campaigns and results for the quarter, it’s very easy to just assume the data given is always correct. 

This is a big assumption to make and it can cost businesses dearly. One of the biggest ways it can be harmful is if an important data source is thought to be clean and correct and then duplicated across departments for others to use. 

The data is used in various individual reports and by the time the mistake is found, there’s no telling how in how many documents its been duplicated in. 

Oops! Who will tell the management? 

Another way inconsistencies can show up is if data sources are stored across various applications, and the names and formatting are different. It can get confusing to figure out what data the columns are referring to. 

Action Item: This will be addressed more in Step 3 (in data cleaning) but a good way to understand if it’s a problem in your company is to see how often data is updated. How often are filters applied on Google Analytics web data? Is there someone in charge of sifting through the data as it comes in? What would be the indicators if performance metrics aren’t correct? 

Not enough time to work with data thoroughly

2. What Problems A Good Data Strategy Solves 

Every company has some daily data challenges in their life: very few companies are perfect and on top of their data. 

Even most software out there for data analysis is at least a little cumbersome and usually has a learning curve (think Salesforce or Excel). 

Here are some problems companies have faced in their data management: 

 

  • Excel becomes too disorganized to use and slow to open after putting in lots of data. 
  • No dedicated data backups in case of emergency. 
  • Raw data that’s downloaded from different sources is not cleaned and cleaning and formatting is time-consuming. 
  • Data exists in different silos and software: when that software becomes irrelevant, so does the data in it. Silos prevent blending data together and seeing deeper insights. 
  • Data exists separately in different departments and data procedures differ for each department. This leads to less cohesiveness in the organization. 
  • There is little to no communication about data strategy between the teams.

 

Without a solid data strategy that all employees are aware of and use daily, it really becomes difficult to know what the standard is. For all the hand-wringing about data being a part of the future, most companies don’t have a dedicated, long-term plan about their data. 

Building a marketing data strategy can be compared to branding. When Google launched their now famous logo in 2015, there was an overhaul across the entire company. The Google colors were put on all Google Products including Search, Mail, Calendar, Drive and more. Everyone was aware of what the most up to date logo was and how it had to be used. 

Similarly, building a marketing data strategy should absolutely be a department strategy but also relate to the company data strategy as well. If the two are completely different then there’s been a miscommunication somewhere about what data is for and how it should be used. 

Action Item: Take a look at your own company’s data strategy and if there even is one. The people that have information about this should be in Information Technology or Business Intelligence. It’s better to see how the original data strategy is formulated and then create the marketing data strategy based off of its procedures and rules. 

By having a data strategy like this, many of the problems above can be avoided in the first place. Let’s look in some more detail about why this should be a priority. 

3. Why A Marketing Data Strategy Should Be At The Top Of Your Priority List

Building a marketing data strategy from scratch is something that takes patience, cross-team communication and time. Additionally, most of the effects are not clearly seen since a good data strategy is invisible and blends in perfectly. Most problems crop up when a solid data strategy is not in place. 

This is the reason why most companies don’t see it as much of a priority and it gets pushed back on the to-do list and progress is very slow. That is, until a data breach or unfortunate incident happens to change minds. Or they just get tired of the disorganization and want a process put in place once and for all. 

Action Item: It’s best not to bring this up when your team is involved with other priorities and stressed or busy. Changing minds takes time. You can start by showing a demo dashboard on Google Data Studio and seeing what the reaction of management is. If they think it’s useful and provides value, of course you can upgrade to a more advanced software and really dive deep into the capabilities. 

Experience shows that companies who have a data plan in place are more successful than the ones who don’t, because they are early adopters. Obviously, being an early adopter doesn’t mean implementing every new system, being aware of trends and how they would help your company works well. 

In Part 2 of this series, we’ll go over practical steps for integrating a marketing data strategy into your organization. Be sure to read along!

At PenPath, we specialize in marketing intelligence software for data-driven marketers. If your team is ready to learn more about these advanced capabilities and how technology can really change the marketing data you already have, schedule a demo here!

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Rucha Shukla

Rucha Shukla is an avid analyst who loves using data to answer big questions in business. You can tweet her @ruchashu.