Over the past few years business leaders have been throwing around phrases like big data and advanced analytics in internal reporting and analytic scrums and discussions. While those buzz words may sound smart during a meeting, there is one very key component, that is not as easy as it seems for businesses and their analysts to be conscious of; being data smart.

Your company probably has a lot of data coming from many internal and external sources that you hope can be managed in a way that can help improve your business. The data might be an email subscriber list or a website dashboard or a market research report, or a practically limitless list of other possibilities.

What’s good about having a ton of data?

Well, if it isn’t put together correctly the answer is absolutely nothing. One expert in the world of web and data analytics, Avinash Kaushik, often talks about the difference between web reporting and web analytics, and preaches the difference between what he calls data puke and critical thinking accompanied by meaningful observations. The data puke is a presentation, report, or spreadsheet that simply displays numbers and how they’ve changed without substantive observations or recommendations. The data puke won’t help those unfamiliar with the data understand any problems or solutions any better, so especially when you’re presenting to executive stakeholders and clients, it is crucial to turn the analysis level up a notch.

To follow Avinash’s wisdom, it’s important that your team is linking the correct data with important key performance indicators (KPIs) in order to generate the right metrics which can effectively inform meaningful observations and business decisions. To do that we have to start in the right place.

Beginning the Story

Many businesses start with Google Analytics to analyze their website visitor data. They begin tracking certain standard items like page views, bounce rate, landing pages, etc. A good starting point, perhaps, but it can be easy to select incorrect metrics without a structured approach. Without a goal in mind it can become very easy to begin down a data rabbit hole.

Enter: KPI identification and identifying analytic maturity. This is of utmost importance. A good analyst needs to have an understanding of your business. To take it a step further, having a hypothesis in regards to what should be expected will also contribute to what’s important to focus on.

Here’s a graphic that shows an example of goal setting in web analytics. You can see that the three distinct goals are Create Awareness, Generate Leads, and Highlight Events. Each one has unique KPIs, data sources and segments, and benchmark targets.

Created by: Avinash Kaushik http://www.kaushik.net/avinash/digital-marketing-and-measurement-model/

The point here: KNOW WHERE YOU’RE GOING. Deciding on these goals should be an open, and ongoing dialog between you and your analysis team. Not taking into account the end-goal will send you spinning – mining data for the sake of mining data is not where you want to be and will often lead to non-actionable observations.

Telling the Story: Avoid “Data Puke”

You will find that some want to understand every little thing that is going on, but don’t realize the opportunity cost of this action. A meeting can quickly derail if the subject is reviewing a spreadsheet of figures as inevitably someone will wonder why a single number went down 3%, then your analyst will spend 5 minutes explaining where it came from and the potential reasons for the change. Overuse of human capital comes to mind here; you’re mining all this data, but what is it really telling you and how is it related to important aspects of your business? This takes time to track and analyze and will often get you nowhere.

The big question; what metrics and reports should I be using to make business decisions? The answer, as always, is that it depends on your business and its goals.

Once you’ve decided on the overarching goals, such as those in the graphic above, it’s time to identify the metrics that help drive your business forward. In looking at our predefined KPIs we lay out pathways of data to follow in order to key in on important metrics that represent performance in areas most relevant to your company and focus there. Avinash says that the data puke should be used to inform dashboards for managers and executives where you report on the KPIs and metrics that are relevant to the high level decisions they need to inform. This is the next step to productive analytics.

Be Sure You’re Listening

One of the biggest factors in reporting results is managing expectations for both your marketing execution partners as well as for those you are reporting to. In other words, what level of result is expected? You’re in trouble if you have a miscommunication there. In laying the data pathways, sometimes you will find that you’re missing an element, so be sure that your analysts are collaborating with web developers to track the right user actions wherever they may be.

Align to your set-up based on KPIs, be conscious of the business landscape, and use data to inform meaningful and actionable decisions that are going to give the business a competitive advantage. If you can do that correctly, you’ll be setup for success with analytics.

At Three Deep, we have the structure to manage powerful analytics, yet are nimble enough to work with clients like you to find the right KPIs and metrics that you can use as an advantage and grow your business. We are experts at the “it depends” part of data analytics and helping clients make sense of their data management. Please let us know if you have a data puke that needs some data smarts you have thus far been missing.