the step-by-step guide to using data to reach your goals
You’ve probably seen the phrase ‘data-driven decision’ bouncing about. While it toes the line of corporate-buzzword territory (anyone remember synergy?) it has also trickled into the small business vernacular as data has become more accessible. Thanks to the ever-growing portion of our business conducted using technology, nearly every business utilizes at least one tool that produces easily viewed data.
The concept of data-driven decision making is simple enough – using your business data to answer questions and direct the decisions you make for your business – but we rarely go into detail as to what that process looks like. When you’re first getting started, it’s hard to know which decisions you should focus on, or exactly what data you need. Of course, every project and business will be a little different, but this is the general flow we suggest:
1. set your goals
First, set your goals. In order to find answers in your data, you need to know what question you’re asking.
Sometimes we put the cart before the horse, thinking our data will tell us what goals we should set. However, it’s important to remember that our data is a tool to use in the journey to reach our goals. We don’t set goals just because we know we can achieve them – we set goals to help us stretch and achieve the business that we want.
After you determine your goals, your reporting serves those goals by tracking progress toward them. We can then use this information to avoid obstacles or clear them faster. This bird’s eye view of your goals, and business, through data, empowers you to redirect as need be – making decisions based on your data.
2. gather the right data
The sheer amount of data we have access to can be both exciting and overwhelming at the same time. More data means more answers, right? Not necessarily. Numbers for numbers sake won’t build your business.
With your goals in mind, the next step is to figure out what data will tell you when you’ve met that goal. It’s important to narrow our focus from all the data we have to just the data that’s helping us make better decisions, bringing us closer to our goal. When we choose to track everything, just in case, we’re putting ourselves on the fast track to analytics burnout.
Collecting it all
Tracking every related data point isn’t just hard to understand, it’s hard to keep up with. Without refining your list, you’ll spend all your ‘analytics’ time on collecting, cleaning, and organizing every single metric available. It’s daunting and time-consuming, and ultimately unnecessary since you won’t end up using most of the data you’ve collected.
Whenever possible, let tools automate the process of data collection, and be selective about any data you need to record manually. Similarly, opt for reports and tools that update automatically where you can, rather than searching for data points each time you want to review. The less time you have to spend on prepping your data, the more time you have to analyze and act.
Making sense of it all
If you’ve ever opened an existing analytics dashboard in one of your tools and immediately thought ‘nope,’ and closed the tab – you know exactly the feeling I’m talking about. Most generic reports and data imports simply have too much to look at. Your job isn’t to review all the data just like your computer would – our job, as the human component of analyzing data, is to connect the dots between data points in a way that computers can’t.
By using our goals to carefully select the information we need out of what we could look at, we shape the kinds of answers we’ll be able to find.
For example, if our goal is to increase the number of people who have heard of us, ‘views’ might be the most important metric we gather from our social media account – but if our goal is to increase social traffic to our online store, we’d probably find more value in the percentage of views that clicked the provided link. In our second example, the overall number of views is still relevant, but it’s not the main focus
3. review and adjust
Once you know what you want to look at, the next step is to look! Many tools offer pre-built, adjustable reporting in their tool. For those that don’t, Google Sheets and Google Data Studio are great, free tools to organize your data into something a little more human-friendly.
After identifying those data points that will tell you whether you’re on track to meet your goal, start asking why you may or may not be headed in the right direction. The answers to this second layer of questioning may or may not be easily found in the data accessible to you. Our audiences and customers are real-world, offline, human beings. We do things offline that aren’t represented in the data, and sometimes we just make unusual or irrational decisions. It’s important to apply our own human-ness to our analysis, use common sense, and knowledge of our business to connect the dots.
It’s also important to remember our goal is to improve the business, not produce the perfect data snapshot. When investigating details and outliers, weigh your time and effort against whether or not the answer will change the decision you’re trying to make. Oftentimes, directional accuracy is enough to get the job done.
TIP:
remember, as you find and build reports, the goal is to see how close you are to meeting your goal and what’s getting in the way – not just a spreadsheet collection
if it doesn’t add context to your goal, don’t include it
the bottom line
Your goals come first – true in most any part of your business, but most certainly true when it comes to analyzing your business. Sometimes we try to skip ahead or lose sight of our goals in the abundance of numbers we have at our disposal, but it’s important to refocus when we do.
By leading with our goals, and only working with the metrics that relate back to improving those goals, we can cut through the noise and give ourselves actionable insights to move the needle going forward.