When I started working with analytics this summer as an intern at Brightfind, I had no idea how important or applicable it was to nearly every part of the web development process. Admittedly, two and a half months of exposure is not a lot of time, but I did have an amazing mentor (shout-out to Justin Atkinson, aka Digital Analyst wizard) and new things to learn every single day. In this blog post, I’ve summarized a lot of what I’ve learned this summer to show you how important analytics really are.
Right now analytics are all the rage. Everyone is talking about them; everyone wants more data, more numbers, more analytics they can use to describe their website. The problem is that a lot of people don’t know what to do with this data. Coming into this internship, I had very little idea what web analytics were, let alone how to effectively leverage the data to drive decision making.
So what is the big deal? What is the significance of “data-driven decision making”, and why do people have such a hard time figuring it out?
Before we can address anything about web analytics, we need to talk about establishing goals. Here at Brightfind, we preach that people need to define their website’s goals and direction before a redesign or initial building of the site. This way they can ensure the website is designed to meet those objectives and align their analytics in a way that supports these strategic goals.
Once these goals are established, an organization can measure its success by evaluating the achievement of these goals. Combined with data analytics, this will give the organization a concrete, measurable definition of success.
Analytics can empower organizations by letting them know what’s working and what’s not, so they can make changes that will help them reach their goals. This is where the importance of “data-driven decision making” comes in. Leading-edge organizations have moved from passively collecting data to actively leveraging data to drive decisions. A study from the MIT Center for Digital Business found that firms that use data-driven decision making have a 5-6% increase in output and productivity.
That sounds simple enough. So why do people have such trouble doing this? As it turns out, there is a ton of data that analytics programs give, but not all of it will be helpful for an organization. It is easy for organizations to get stuck on numbers that do not matter much. “Total visits” will not tell an organization anything substantial about their site, let alone drive anyone to make an effective change. It can act as a feel-good number (since “total visits” will only ever increase), but has virtually no other use. Good, useful metrics are comparative (total signups in a certain time period vs another time period), understandable, and will influence changes on the site.
So now that we know the importance of establishing goals and defining what a good/bad metric is, how much can analytics tell us? What information do analytics give that you can then use to drive your decision-making? Analytics can tell us a lot about users and their behavior. Some examples of what they tell us and how we can use that information are as follows: