Relentless Pursuit of Growth: The Three Roles of an Effective Analytics Department.
Updated: Nov 21, 2019
When I talk to marketers who are looking to buy my team's services, or they're looking to build out their own analytics group - I frequently tell them that a proper analytics team is all about installing intelligence in their marketing organization. It's not meant for every marketing department - some are small and may do a fine job of analyzing their data without a specialist - but once a company is at the size that they need analytics specialization you have a few directions to go in. In this post, we'll explore the three main areas where marketers can improve their marketing intelligence capability.
Intelligence: An evolution, not a revolution.
Intelligence is an interesting word. It's beautiful and controversial. Intelligence is the tool of choice that's guided humans to dominate the food chain, protect our families, develop civilizations and create places where we thrive to do what stimulates our minds. (writer's note: I'm focusing on the positive aspects of intelligence in this blog post.)
So what is intelligence, and why is it so important to sustainable, achievable business growth? Intelligence is the ability to use data to gain knowledge about the marketing environment and use that knowledge to adapt. It's action driving; it leads to adaptation; and it's a basic function that any business MUST do in order to maintain competitive advantage. It's also not something we (as decision makers) can turn on overnight. Intelligence relies on accurate information in order to be intelligent. A marketing department that acts on bad information, will eventually get burned by their lack of real knowledge about the consumers, competitors and their industry.
Intelligence is the ability to use data to acquire and apply knowledge. Something every business needs to maintain competitive advantage.
A strong intelligence capability begins with clean data. Data we can trust and data that captures the important aspects of the marketing environment. For groups I lead, clean and useful data comes from planning, coordination and engineering. This is a practice I call data operations.
A strong intelligence capability begins with clean data.
Data Operations: Acquiring clean data.
The journey to marketing intelligence begins with a sound data operations practice. Data ops is a combination or data engineers, product managers and representatives from information technology groups. If the marketing organization is small, it can also be as simple as having the right tools and infrastructure in place - no assembly required!
The goal of sound data operations is to identify the data an organization has, the data we need and create a plan to build a trusted source of truth about the company, customers and the marketing environment the business operates in.
To assess if you need to invest in data operations, ask yourself this: If the data I'm using in my organization today contradicts my thoughts and decisions I'm making, would I change my mind? Do I have faith that the data is good? If the answer is no, then let's start the intelligence evolution by taking a look at data operations.
Analytics and Statistics: the Science of Changing my Mind Under Uncertainty
If data operations are in order, the next major investment is in analysts and statisticians who can use methodologies to create useful insights about the data we've collected. These folks come in all sorts of flavors, so let me offend most of them by putting them into two buckets.
Bucket 1: Data Mining Experts / the Storytellers / the Inspirers.
Bucket 2: Statisticians / the Brainiacs / the Risk-Slayers.
This oversimplification is useful because it gives us a useful heuristic on when to leverage their unique skill sets.
Bucket 1 - The Data Mining, Inspiration Team: Data mining experts are exploring the data to help inspire marketing decision makers. They find insight when we have NO DECISION THAT NEEDS TO BE MADE. You may be asking yourself, "Why would I need insight when I have no decision to make?" Well, the answer is inspiration... You need to be inspired to begin questioning your marketing operations. The data mining team is responsible for asking questions of the data and our processes - shining a light on the dark, hidden corners of the data you're capturing.
Their tools are performance reporting, data visualization and descriptive statistics. This flavor of analyst is curious and a great story teller. They have excellent business acumen that is only eclipsed by their careful process of insight development. This is one of the first roles you'll work with when monitoring marketing performance.
Bucket 2 - The Braniac, Risk Slayers: Statisticians are related to but are not focused on inspiration like our data miners. They're focused on using stats to help you make decisions. The statistician is a useful person to consult when you have choices to make like:
Marketing budget
Deploying the right creative
Understanding the importance of product features when estimating product demand.
These math pros are best leveraged when you need to understand the risk of decision making and you have excellent data. So, grab your neighborhood math super-hero, let her/him look at your situation, and feel awesome knowing that you're reducing the amount of gut decisions you make.
Data Scientists and Technologists: Building Cognitive Solutions
Once you have a handle on data mining and are minimizing risk with statistics, it's now time to create business solutions that tap into the power of the data you're collecting. Data Science is where you turn to when when you have MANY DECISIONS you need to make in a very short amount of time - like in milliseconds or even faster...
<record scratch>
What? When would you ever need to make decisions in milliseconds? I'll give you a few examples:
What products should I recommend in an email?
When should I pay more for a digital advertisement?
What users are more likely to convert on my website?
How can I classify images uploaded by users of my services?
Enter the data scientist and the software engineer - two roles that can help you build data driven solutions.
Cognitive solutions are business solutions that can create and apply knowledge. These solutions are best used to make many decisions in a relatively short time.
The data scientist / software engineer combo is powerful. If you can put these two roles together in the same room - backed by sound data operations - then you have a business solution powerhouse in the making.
Still need some guidance on how to evolve your marketing intelligence. Give me a shout in the comments section below; or check out one of my other blogs for some inspiration.