Become a Marketing Analytics Superhero (Part Two)

Welcome back, my fellow marketing analytic superheroes. As we discussed in Part One, there are many obstacles that can stand in the way of marketing analytic supremacy. I previously touched on one main obstacle: getting started. The following obstacles may not be as obvious, but are just as important to keep in your superhero tool belt. Obstacle Two: What metrics do we measure?
In today’s business environment, there are research studies or articles claiming they have all the answers regarding which metrics give significant, actionable substance to marketers. Data and technology expert Mark Jeffery recently conducted a survey of CMOs and CEOs from Fortune 500 companies about marketing automation expenses and how they track the effectiveness of campaigns. The companies surveyed had a combined annual marketing expenditure of $53 billion. The study showed that over half of marketing budgets are spent on demand generation campaigns.

Given the amount of money spent on demand-generating marketing activities, it’s absurd to think marketing measurement is not structured more scientifically. The first step towards implementing actionable measurement mentality is organizing your key metrics. Given the vast amount of data being collected, it can be overwhelming for marketers to determine where they should spend their time in order to maximize efforts. Everyone has a different agenda, which only adds to the failing efforts of organizing marketing metrics that are actionable. Each specific individual has specific analytic needs; there is no cookie cutter answer as to what beneficial metrics should be measured. The best possible superhero move to make is to organize a solution with your entire team. Organizing then entire superhero team from the beginning is the easiest best practice to implement. It’s important to concentrate on the needs of the entire team. From this vantage point, you are able to see everyone’s needs, narrow down actionable metrics and conquer the overwhelming metrics as a team.

How can you accomplish this?

Organization. The most important first step towards choosing correct metrics is to organize what needs measuring, not what you have available to measure. At Relationship One, we go through an extensive discovery project process where we assist clients with metric organization. Our best practices help clients build actionable metrics. Not all cases are the same, but a majority of companies face similar issues that can be solved with a simple conversation. A discovery project starts with the big picture. Clients are asked to list what metrics they would want to see if there were no limits to their data. All team members are considered in this conversation in order to obtain an entire company synopsis. The directive is to optimize organization. For the first step, companies are asked to fill in the following statement:

As a… I want to see… so that…

An example of this would be, “As a Sales Manager, I want to see who is most highly engaged in our campaigns so that my sales team may prioritize how they concentrate calls.” Or “As a Product Manager, I want to see campaign success so that I may determine future content for my audience.” When a team of superheroes walk themselves through this thought process, analysts can pin point what is important and organize a gap analysis to give actionable metrics.

Obstacle Three: Visualization
Now you have a list of great outcomes you’re looking to measure for your analytic success! But, how the heck are you suppose to analyze these metrics for everyone to visualize in a convenient manner? Great question, marketing superhero.

There are so many business intelligence tools available to your team that it’s sometimes hard to figure out where to start. Begin your search by looking at your list of outcomes you created in Obstacle Two. Which tools are going to be able to easily provide you with data visualizations that provide answers to the problems you’re trying to solve. Once you narrow it down to two or three platforms ask the vendor some hard questions: How easy is it to create new visualizations or edit existing ones? How are you accessing the data? Are you working with raw data or data that’s been preprocessed? How do I share visualizations with my team and people outside the organization? What if I get stuck…who will help me? What if our organization grows massively, how does this platform scale? Who are the other companies in my industry/vertical/size who currently use your platform? Do these render well on any device? Etc.

Narrowing down the tool will take some work but once you do, you can start building out the visualizations that tell actionable stories your internal teams needs to know. This includes: What type of graph or chart best conveys what’s really going on? How do I calculate the metrics I need to know? Where do I get all my data sources and how do I organize a place where I can slice and dice the data? What unique identifiers do I need to capture so I’m able to match data coming from different sources?

This might seem overwhelming, even for a superhero like you, but the greatest investment you can make for your team is to do it correctly from the start. However, if you are overwhelmed just thinking about all this, there are great analytic sidekicks who can help you along this journey. Relationship One has an outstanding Performance Analytics team who, much like the X-Men or Super Friends, can collectively walk along side you as you tackle your data visualization goals so you don’t have to go it alone. Check out some of these examples.

Wow! Look at you sporting a new superhero cape of marketing analytics knowledge! Applied holistically, marketing analytics allows for better, more successful marketing by enabling you to close the loop as it relates to your marketing efforts and investments. Marketing analytics will lead to better lead nurturing and management, which leads to more revenue and greater profitability. By more effectively conquering marketing analytics, you can see which specific marketing initiatives are contributing to your bottom line. What marketing analytics superhero doesn’t want that?