One of the best ways to get insight into a user behavior is with actual data.
If you're redesigning an existing site,
chances are that you have access to visitor stats of
the current site that can tell you an awful lot about your current users.
The most common tool used to track user data is Google Analytics.
It's enabled by replacing a tiny bit of code onto every page of your site
which then captures user activity data for you to evaluate later.
This allows you to find answers to questions like,
how many people visit the site each day?
As I mentioned, having actual hard data can be very powerful,
but any data analyst will tell you that it's important to interpret data correctly.
Otherwise it can be a little bit like reading tea leaves.
For example, if you found out that you site had 1,000 daily visitors,
is that a lot or not?
Does it mean the site is successful or not?
If you go for the sidewalls to grow the amount of visitors to a 100,000,
it would be quite a failure.
On the other hand, if your site only had 100 daily visitors in the past,
this would present a tenfold increase.
I think that websites stats are best approached with
specific questions in mind before you look at the data.
Here are some example questions that are more specific.
What percentage of my users visit the site on a mobile device?
Or we ran a Facebook ad last week,
did this increase the amount of visitors?
How many users still use Internet Explorer?
Are my users mostly local or is there a sizable worldwide audience?
Let's take a quick tour of Google Analytics so you
can get an idea of how the interface works.
We'll use as an example a website that my business partner Nicole and I
created to showcase our favorite albums of the year.
You can take a look at the website at FavoriteAlbums2017.eBrigade.com.
We've worked hard to make it a fun interactive experience.
Now, when I log onto Google Analytics,
I can find out a lot about the visitors of this site.
I can see how many users are currently on the site.
Right now there is just one,
so, that must be me.
In fact, here you can see that the visitor is from Los Angeles.
So yeah, it's me.
You can also see how many visitors came to the site over time.
Here are the stats for the last week,
or I can look at the last 30 days or a custom time period.
You can see the site launched in late December.
You can also see the total amount of visitors and how long they stayed on the site.
I'd say the average interaction with the site of almost two minutes is pretty good.
If it was only a few seconds,
I would be worried that the site is not really working at all.
So, what are some specific questions I could ask?
Here's one, we entered the site in some design competitions,
did this make a difference?
Let's go to acquisition.
You see that about three-quarters of visitors came to
the site by clicking a link on another sites.
We can explore this further.
Now you see a list of the top referral sources.
I can switch to a pie chart view,
and it's obvious that over 92 percent of these referrals came from two sites,
awwwards and onepagelove, exactly the sites whose competitions we entered.
So, to answer my question, yes,
it did make a difference that we entered the site in design competitions.
That's helpful information for the future.
Here's another question, I know that because of the experimental nature of this site,
it works best on a desktop computer with a mouse and not-so-well on a mobile device.
So, the question is,
do we have a lot of mobile viewers?
Should we spend the resources to make the mobile experience better?
I can click on audience, mobile,
and I find out that almost 95 percent of our visitors were on a desktop computer.
So, we probably don't have to worry too much about this issue.
You probably agree that Google Analytics is a really powerful and complex tool.
It would probably take an entire course all by
itself if you wanted to learn all of its capabilities.
In fact, Google offers detailed free courses to learn more about their products.
But finding out a few fundamental facts about your site's visitors isn't too difficult.
Just remember, having a lot of data is worth
very little if you don't interpret them correctly,
and in order to interpret data,
you need to start the specific questions that you'd like to be answered.