How Marketing Operations Chooses Wisely Between Bright, Shiny Objects

This month we make a right turn on the journey and finally discuss marketing operations and technology. This is the 15th blog in the Revenue Marketing journey series, and we finally get to a discussion on technology. Hopefully that tells you something about how important people, process, data and content are, in that they all preceded this post.

Last month on our Revenue Marketing journey, we discussed how to formulate your 2018 content marketing strategy. This month we make a right turn on the journey and finally discuss marketing operations and technology. This is the 15th blog in the Revenue Marketing journey series, and we finally get to a discussion on technology. Hopefully that tells you something about how important people, process, data and content are, in that they all preceded this post.

Gartner recently released their CMO Spend Survey 2017 to 2018. In 2018 the survey suggests that marketing spending on technology will drop to 22 percent of the total budget. In addition, the technology landscape as plotted by Scott Brinker and team at Chiefmartec.com exceeded 5000 logos in 2017. So great, marketing operations has all this budget to spend on technology and more choices than we can possibly evaluate. What are we to do? Let’s start with the end in mind.

What Outcomes Do You Expect From the Technology?

We deploy technology largely because it fulfills one or more of the following criteria:

  1. To gather, analyze and disseminate information to make better business decisions
  2. To automate some previously labor-intensive processes to gain efficiencies and increase profits
  3. To enable innovation in the products and services we provide to win market share

So, the question becomes, where in 2018 will you get the highest ROI from technology investments? If you are early in your Revenue Marketing journey, you may opt to invest in a customer relationship management (CRM), a content management system (CMS) and a marketing automation platform (MAP) as these tend to be technology hubs at the center of a typical martech stack as shown below:

Revenue Marketing Architecture for Marketing Operations
Revenue Marketing Architecture

As an example, a MAP enables you to gather and analyze behavior data about your prospects and customers so you can make better decisions about how to engage with them to optimize the customer experience. A MAP can also automate responses to prospects when they perform certain actions, thereby reducing the need for human intervention. And a MAP can be configured to move individuals from one campaign to another depending on where they are in their customer journey, adapting the nature of the outreach to match the circumstances of the prospect. An example might be opting new customers into welcome campaigns automatically. So the MAP could meet all three of the criteria listed above for justifying a new technology acquisition.

The Great Marketing Data Revolution

I think it’s safe to say that “Big Data” is enjoying its 15 minutes of fame. It’s a topic we’ve covered in this blog, as well. In case you missed it, I briefly touched on this topic in a post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey,” which I published a few weeks back. For those of you who don’t know what it is, Big Data refers to the massive quantities of information, much of it marketing-related, that firms are currently collecting as they do business.

I think it’s safe to say that “Big Data” is enjoying its 15 minutes of fame. It’s a topic we’ve covered in this blog, as well. In case you missed it, I briefly touched on this topic in a post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey,” which I published a few weeks back.

For those of you who don’t know what it is, Big Data refers to the massive quantities of information, much of it marketing-related, that firms are currently collecting as they do business. Since the data are being stored in different places and many varying formats, for the most part the state they’re in is what we refer to as “unstructured.” Additionally, because Big Data is also stored in different silos within the organization, it’s generally managed by various teams or divisions. With the recent advent of Web 2.0, the volume of data firms are confronted with has quite literally exploded, and many are struggling to store, manage and make sense out of it.

The breadth of data is simply staggering. In fact, according to Teradata, more data have been created in the last three years than in all past 40,000 years of human history combined! And the pace of data is only predicted to continue growing. You see, proliferating channels are providing us with an unprecedented amount of information—too much even to store! In a marketing sense, the term Big Data essentially refers to the collection of unstructured data from across different segments, and the drive to make sense of it all. And it’s not an easy task.

Think about it. How do you compare email opens, clicks and unsubscribes to Facebook “Likes” or Twitter followers, tweets or mentions? How does traffic your main website is receiving relate to the data stored in your CRM? How can you possibly compare the valuable business intelligence you’re tracking in your marketing automation platform you’re using for demand generation, against the detailed customer records you’re storing in your ERP you use for billing and customer service? Now throw in call center data, point of sale (POS) stats … information provided by Value Added Retailers (VARs), distributors and third-party data providers. More importantly, how do they ALL compare and relate together? You get the picture.

Now this begs the next question; which is, namely, what does this mean to marketers and marketing departments. This is where it gets very interesting. You see, unbeknownst to many, there’s an amazing transformation that is just now taking place within many firms as they deal with the endless volumes of unstructured data they are tracking and storing every day across their organization.

What’s happening is firms are rethinking the way they store, manage data and channel data throughout their entire companies. I call it the Great Marketing Data Revolution. It’s essentially a complete repurposing and reprocessing of the tools they use and how they’re used. This wholesale repurposing aims not only to make sense out of this trove of data, but also to break down the walls separating the various silos where the information is stored. As we speak, pioneering companies are just now leading the charge … and will be the first to reap the immense benefits down the road when the revolution is complete.

Ultimately, success in this crucial endeavor demands a holistic approach. This is the case because this drive essentially requires hammering out a better way of doing business by reprocessing across these four major steps: Process Workflow, Human Capital, Technology, and Supply Chain Management. In other words, doing this right way may require a complete rethinking of the direction that data flows within an organization, who manages it, where the information is stored, and what third-party suppliers need to be engaged with to assist in the process. We’re talking a completely new way of looking at marketing process management.

With so many moving parts, not surprisingly there are many obstacles in the way. Those obstacles include legacy IT infrastructure, disparate marketing structure scattered across various departments, limited IT budgets and, of course, sheer inertia. But out of all the obstacles companies face, the most important may be the dearth of data-savvy staff and marketing talent that firms have on staff.

Firms are having a difficult time staffing up in this area because this transformation is actually a hybrid marketing and IT process. Think about it. The data are being created by the firm’s marketing department. As such, only marketing truly understands not only how the data are being generated, but more importantly why they’re important and how this information can be put to actionable use in the future. At the same time, the data are stored within IT’s domain, sitting on servers or stacks, or else stored in the cloud. And because the process involves a complete rethinking and reprocessing, it really needs a new type of talent—basically a hybrid marketer/technologist—to make it happen.

Many are deeming this new role that of a Data Scientist. Not surprisingly, because this is a new role, employees with these skills aren’t exactly a dime a dozen. You can read about that here in this article that appeared on AOL Jobs titled “Data Scientist: The Hottest Job You Haven’t Heard Of.” The article reports that, because they’re in such high demand, Data Scientists can expect to earn decent salaries—ranging from $60,000 to $115,000.

Know any Data Scientists? Are you involved in a similar reprocessing transformation for your firm? If so, I’d love to know in your comments.