The road to successful marketing analytics starts with MART: Measurable, accessible, reliable and timely data. Not all marketing data is created equal and having data alone doesn’t make it a strategic marketing asset.
In my last post, I discussed the importance of understanding the difference between the concepts of “better-informed” and “better” marketing decisions. Successful marketing analytics platforms (regardless of their size and scope) provide a foundation for better-informed decisions and rely on some of the same core principles of any analytics program.
During my consulting days, I had numerous opportunities to present to marketing professionals on how to drive insight from data. Keep in mind that this was before the days of big data, mobile, digital and social media. My audience was neither tech-savvy nor familiar with business intelligence (BI), but they knew marketing inside out.
I love the field of marketing! So, I decided to put together something new for my presentations. I took some of the key principles we use in BI initiatives and turned them into a simple model that marketing professionals can easily leverage and called it “MART“ to give it an easy to remember name. After more than a decade, I still rely on it.
Let’s briefly review each element and how it applies to successful marketing analytics platforms.
M Stands for Measurable Data
Ultimately, our goal must be to employ data-based analysis to measure the success of our marketing strategy. At a tactical level, the analysis may be measuring effectiveness of our campaigns or our overall implementation.
The simple fact is that if we can’t measure, how can we monitor? If we can’t monitor, how can we uncover issues and make the necessary adjustments? And most important of all: How can we gauge our success?
The pace of business today demands execution with a higher velocity, forcing us to be agile and flexible with our approach. This means constantly changing our assumptions and making adjustments to our models. Without measurable data elements, our criteria for success remain debatable.
A Stands for Accessible
Just capturing and storing data will not get us far because hidden data has no value. It needs to be accessible by people who depend on these data sets to make critical business decisions.
Accessible means two things at minimum. First is the access by the right role. If we have all the data but we cannot deliver it for the right role, it is like finding treasure while stranded on an island but not being able to obtain water, which is more important for our survival.
Second is the way we make these data sets accessible for consumption. How we deliver business value is directly related to how simple we make it to find and consume these data sets, hence the user interface and the overall user experience.
R Stand for Reliable
Data has to be reliable and complete. The lack of trust breeds a lack of conformity and standards that are required for robust data-driven decision engines that people can count on and use. Otherwise it becomes “garbage in/garbage out.”
If you ever worked closely with your IT colleagues, you might have heard them use the term ETL, which stands for “extract, transform and load.” It refers to all of the stages that raw data needs to go through before it can be presented to or consumed by its users.
Data quality plays a key role because when it is consistently excellent, then it becomes trustworthy. It’s true that as quantity increases, we can achieve greater depth and perspective. But by the same token, data for the sake of data doesn’t help us either. Data quality (a field on its own) is fundamental for driving consistency and relevancy when it comes to making better-informed decisions.
T Stand for Timely
Finally, it doesn’t do much good to have all the data we need if it’s not timely. Businesses can no longer afford to wait for traditional transformation cycles that last for days. New technologies such as cloud, mobile and in-memory are fueling this paradigm of demanding more data points faster.
If it is not timely, it’s simply too late. Here is how I see it:
- To compete effectively, you need to be faster and smarter than your competition.
- To manage risk efficiently, you need to remove it before it becomes a liability.
- To grow faster, you need to find opportunities before they are ripe.
- To contribute to profitability, you need to constantly adjust so you can manage at optimal levels.
Today, these principles apply equally to marketing and how we leverage business data.
MART is not a magical formula for marketing analytics. But what it does is highlight the key elements that every successful data platform should have. Coupled with the right technology, design and implementation, these principles extend beyond traditional marketing practices and can be applied to all forms of marketing: digital, content and social media.
As I always maintain, if leadership is not keen to promote the culture of data-driven decision making, even the best implementations of marketing analytics solutions can neither change nor prevent uninformed or less-informed decisions, resulting in the perception that marketing is a cost center and not a driver for growth.
Where do you see the biggest challenges with your marketing analytics platform?