As a business executive, my marketing operations team can only effectively deliver marketing data and information to me based on the goals and guidelines that I establish.
In particular, the goals I establish in my marketing and sales are what drives my company’s marketing and sales performance. As the captain of the ship, only I can establish those objectives and how I measure them – nobody else.
Those parameters are the very basis by which I make the necessary decisions for my business, and ultimately are the noose by which my shareholders and investors will hang me if I bet on the wrong pony in the end.
A business enterprise is an ecosystem. Everything relates to, or impacts everything else down stream in some way.
For example: in manufacturing, when someone attempts to resolve a quality control issue, the kaizen approach of the “five whys” asks a series of iterative questions. This is explicitly to explore the cause-effect relationships underlying that particular problem.
Like dominos falling, everything cascades and compounds downstream. So a problem manifesting itself somewhere in a process can invariably be traced to some other upstream root cause. If sales isn’t getting the right kinds of leads, I have to look upstream to understand why that is happening.
The Context Of Marketing Data Is A Quality Management Issue
Any business data itself is only meaningful when you look at it within a specific context.
For example, a single number stored in a database somewhere isn’t meaningful at all. The number “20” by itself isn’t really anything at all. It’s a numeric representation of some volume of SOMETHING: dollars, number of items in inventory, days since the last OSHA violation, percent of increase in sales over last year, etc… The business data itself is only meaningful when viewed within a specific context. It’s this context that gives our business data some meaningful value. In the era of “big data” (I hate the term), we store everything.
We’ve got marketing tools to capture infinitely expanding volumes of marketing metrics. But all of this business data we’re amassing about every aspect of our marketing operation is virtually meaningless without some understanding of how the context defines the value of the data itself. Dashboards and reporting processes must be constructed so my marketing data provides an accurate representation of how my marketing performance is affecting my overall sales.
This also means organization policies and processes surrounding the marketing data should take into consideration the holistic view of how the data is eventually used in some decision support process. Making the leap between marketing and IT isn’t always easy… especially when it comes to data governance.
We have the data itself: raw information about the specific objects relating to the functional process of the business enterprise.
Then we have the context within which the business data is used.
And this brings us to the concept of metadata.
And Then There Was Metadata
Metadata is essentially data about data, most often it’s the information about the relationship between a specific data object, and how that data object exists within a specific context. This can be direct adjective modifiers which enhance the data itself… ‘purple’ sweater, ‘brown’ cow, ‘2004 North American’ sales.
But it also be a state of “being” (reminds me of the Clinton sex scandal court case, what is, “is” anyway?). This is a bit more elusive of a concept, but can be simplified into business terms as “data in motion” or “data at rest”.
How do I use all of this marketing data to make daily decision about what I am doing as a business to help makes sales easier?
Marketing data by itself sitting in some database means nothing at all. It’s a bunch of ones and zeros at the binary level. It only has meaning once the context itself is applied. Then the data is either at rest, or it inherits context as a result of being in motion (used as part of a functional business process).
Most business operations come down to a handful of KPI (key performance indicators) metrics at each functional layer – and at the top as well. This has gotten a lot easier in marketing and sales because of technology enablement. I have a host of various platforms at my disposal to create marketing intelligence and sales performance dashboards.
As a business executive, I really only need a few simple statistics about my business – and in particular, the relation to my marketing and sales processes.
When I accurately defining this marketing data, I am putting my marketing budget and the dollars I spend into a context that’s usable for me as a business executive. I want to make intelligent, strategic decisions about where to apply my limited resources (capital, skilled talent, etc…).
By understanding the nature of marketing data within my organization, I can better define the contextual views of the metrics – and hopefully minimize the potential for those skewed statistical results that paint the wrong picture.
I want a true and accurate view of my marketing data on a real-time basis, and it is my own responsibility to create the contextual definitions of what that means. Only then can I really help my team understand the measurement of marketing performance in the overall marketing and sales processes, and how those numbers relate to overall sales and profitability.
Organizations can’t continue planning and budgeting marketing as a random percentage of sales or some other disconnected, subjective decision around various traditional activities. Hyper competitive organizations will evolve, and make financial decisions based on hard numbers – not the “big idea” in a silo.
How are you defining your marketing data and sales performance measurements?