Big data is now omnipresent. It is embedded into our day-to-day lives as the hard-wired DNA that fuels our business processes and decisions. Data-driven cultures went mainstream in 2016, with organizations scrambling to establish data strategies that enabled all employees to make better informed decisions. Yet despite all of the hype, the majority of organizations still have a long way to go before realizing the potential that big data holds.
Do you have children? If so, you know what quality time in general means: although you have a stressful job, some overnight-stays in hotels in foreign cities or night shifts in your office you still can have the best moments for and with your children. Even though you are home less often. Meaning: the less time you can spend on “something” the more quality and focus this time should include.
If you do not have children, I assume you get the point of dealing with the limited resource of “time” in a very efficient manner due to this example as well.
The most important aspect of web analytics is being able to utilize the information you collect to create strategic and actionable next steps for your company. As your firm’s analytics expert, the best way you can help do that is by creating specific reports for the various departments throughout your organization that focus on their key goals.
The sales team is solely focused on how the website can generate revenue or bring in new sales leads. You can help them improve their current strategies by providing insight on how the website and other marketing tactics contribute to purchases and lead generation. Depending on whether your website is B2C- or B2B-oriented, you’ll want to structure your report for the sales team differently.
I started making a Halloween costume for my daughter in August. Back then, she told me she wanted to be Cinderella. So I immediately went online to find a tutorial on how to sew a Cinderella dress.
I made custom measurements, picked out supplies at the fabric store, and then cut and sewed the costume. It was a very challenging project but I was happy with the outcome. This costume would grow with my daughter and never fall apart due to how it was constructed. When it was finally ready to try on a month later she immediately took it off and declared that she wanted to be a lionfish-mermaid instead. Despite my toil, my investment in time and money, despite my care to give my daughter exactly what she wanted, what she needed, she was not happy.
Much like B2B marketers must react in real-time these days, three year olds live in the moment. Cinderella was what she wanted in August, but by the time she got it in September her interests had shifted. She is growing at a very fast rate – not just in size, but in her understanding of the world we live in.
I have spent an inordinate amount of time helping clients understand the difference between “unique visitors” and “people” when it comes to measuring web site audiences. The “unique visitor” metric comes from web analytics and is defined in terms of browser cookies. The “people” metric comes from IP/panel data (like Quantcast) and is typically an estimate based on a representative audience sample. Neither metrics actually represent a person, like you or me or the people we interact with in real life (irl) every day.
The “unique visitor” metric is expected to be greater than the number of “irl people,” or customers that access your sites, and the “people” metric varies according to how representative the sample is of your audience.
If only there was a way to tell how many “irl people” are visiting sites.
Universal Analytics (UA) from Google moves us one step closer to being able to have the “irl people” metric and associated insights.
As the prevalence of multi-device browsing grows, brands are investing in mobile experiences in addition to web ones. But are they reaching the same customer twice – once on the web site and again on mobile? Or are they reaching a new audience on their mobile properties that they weren’t reaching before because they only had a website? Are customers converting at a higher rate thanks to being able to have a mobile touchpoint with the brand instead of just a web one?
Many web analytics tools let you capture the User-IDs for logged-in visits in a variable, but the reporting effort needed to answer questions about the impact of cross-device browsing is clunky since the measurement protocols are cookie based, rather than customer based. The measurement protocol for UA is designed around the User-ID, so once you start tracking that information, associated activity is attributed to one visitor in the reports – one “irl person.”
The seamlessness of the solution provided by the new measurement protocol in UA means clunky work-arounds – like having to adjust unique visitor numbers by the number of times a User-ID shows up in visits reports, are obsolete.
Battle scars gained from explaining the difference between “unique visitors” and “people” have made me shy away from reporting on those metrics and made me recommend that analysts focus on discrete sessions which are better captured in cookie-based web analytics tools. Now, with UA, I am excited to see analysts putting the “irl people,” the customers, back into their analyses.
Are new measurement protocols, like cross-device tracking, changing how you measure your site audiences?