In this world where everyone is talking about “data”, analytics is no longer a word that is uncommon to hear.
Having tons of data is good, but without the proper tools to analyze them, they are essentially worthless. That is why, there exists many analytics tools, attempting to extract value out of these data.
Today, we will be focusing on Web Analytics, answering the What & Why.
What is Web Analytics?
Web analytics is simply the collection, analysis and reporting of web data.
What is Web Data?
Assuming a webpage is being tracked using web analytics, below are some actions that can result in web data being collected:
- Opening a webpage
- Clicking a button
- Clicking a banner
- Playing a video
- Using the search function
- Completing an application form
Web data collected are mainly information of pages, forms, products, etc. Some examples are:
- Page name
- Product name
- Product category
- Form name
- Form step number
- Button name
- Banner ID
Why Do We Need Web Analytics?
With these web data, we can better understand the consumer behavior on our websites!
Take for example an e-commerce website. Sure, even without web analytics, we know exactly how many items were being sold. But we do not know which products are the most viewed ones!
In the past, all we can do is to assume that the best product must be the one with the highest sales figure. But more often than not, that’s not true.
Take for example product A and B, both similarly priced.
Product A had a total sales of 1,000 units, while product B had a total sales of 200 units.
With web analytics, we managed to find out how many times the products were viewed.
Product A was viewed 10,000 times, while product B was viewed 500 times.
We are given a small budget to carry out a product awareness campaign, which product would you do it for?
Without web analytics, we will probably be choosing product A, given the limited information we have.
But with web analytics, we can now determine the sales conversion rate!
Product A : 1,000 / 10,000 = 10%
Product B : 200 / 500 = 40%
Now that we know that product B has a much higher sales conversion rate, it makes sense that we focus on creating more awareness for it rather than for product A!
In this example, let’s continue to assume the CEO role of an e-commerce company.
With the help of data analytics (not web analytics!), we were able to build a statistical model using historical sales figures. The statistical model provides us with a forecast of how much sales can we expect in the next few years.
In 2015, we generated a revenue of $1,000.
In 2016, we generated a revenue of $2,000.
In 2017, we generated a revenue of $4,000.
The statistical model forecasted that we would be generating $7,500 in 2018, and $14,000 in 2019!
It seems like our business is doing great!
Remembering that we also have data collected using web analytics, we decided to take a look too.
In 2015, we had 100 web visitors.
In 2016, we had 400 web visitors.
In 2017, we had 2000 web visitors due to aggressive marketing.
Looking at the user growth, it seems like we are reeaaalllllyyyyy doing GREAT!
Data Analytics + Web Analytics
Wait! Something is amiss…
What if… we take a look at a more useful metric, which is average revenue per user.
In 2015, ARPU = $1,000 / 100 = $10.
In 2016, ARPU = $2,000 / 400 = $5.
In 2017, ARPU = $4,000 / 2000 = $2.
This doesn’t look right. The insight we are drawing here is… the more users we have, the less revenue we are generating out of them.
If ARPU deteriorates as the number of web visitors increases, this means that the business is not sustainable and has a limit to scalability.
Combining data from both data analytics and web analytics, we were able to identify the issue instead of wrongly assuming that the business is doing well!
So… what’s the conclusion?
Depending on traditional data analytics is simply not enough to provide accurate insights and findings.
Using web analytics, we can capture actual consumer behavior, and thus have a greater understanding of our business.
And the important thing is, web behavior truly represents who we are and is the most accurate form of data out there.
Browsing is like breathing
When we are browsing through the internet, do we stop and think or do we browse instinctively?
Browsing the internet is like breathing for us. We just browse as and when we want/need. We do not give it extra thought, unlike doing a survey.
If we were to go through our own browsing history, it is unlikely that we will find anything that is not of interest to us.
Still not convinced? Then I have a question for you. Would you share your browsing history with others? Are you concerned about your personal data privacy?
The reason why we are uncomfortable with sharing our browsing history is simply because, our browsing history holds all the information of who we truly are.
Web analytics is crucial in helping businesses truly understand what the consumers are doing on their websites. It provides an additional data source that is reliable in helping us obtain useful insights that are hard to come by.
So if you’re still new to web analytics, we have some articles that will definitely help you kickstart the whole process:
Google Analytics – https://webanalyticsguy.com/2017/08/22/google-analytics-dummy-lets-get-started
Adobe Analytics – https://webanalyticsguy.com/2017/08/25/adobe-analytics-dummy-lets-get-started
If you already have Google Analytics set up, we know exactly the reports that will help you: