To examine the success of your website or campaign, keep in mind the TAO of conversion optimization. This acronym stands for track, analyze, and optimize. In this article, we’ll talk about analyzing data analytics. To recall, various metrics can help you gather information on how well the campaign is meeting its objectives. Web analytics can be categorized as count or ratio, with groupings like aggregate, segmented, or individual.
Numbers on your key performance indicators or metrics do not mean anything if you don’t interpret them. The raw figures do not mean anything. You typically have to look at what these tell about user interaction with the website. Trends should be analyzed over time since the web analytics package won’t offer fully accurate results. Doing this activity will give you an in-depth understanding of your brand’s progress based on performance.
Important Elements When Analyzing Data Analytics
When analyzing data analytics, consider this three-point approach by Kaushik.
- Why are the users visiting your website? In analyzing data analytics, the term for this is behavior. It infers the intention of the visitor of your website.
- Are these visitors attaining the goals that the company desires? This is referred to as outcomes. Analyzing outcomes is all about the number of visitors who performed the goal action on your site
- Are there noticeable patterns of user behavior? In what ways can the users be influenced for the campaign objectives to be achieved? The user experience can answer these types of inquiries.
Behavior
The behavior of web users determines their intent. They expect certain problems to be solved by your site. If you want to know which problems they are referring to, look at referral URLs. You’re also required to pay close attention to the terms they search for on your site.
The heatmap tells a lot about the noteworthy clicks on your site. In analyzing data analytics, this is known as click density analytics.
You can also analyze certain groups through a method called segmentation, which will be discussed later on.
The other method for gauging the intent of your site visitors is by looking at the behavior and content metrics. Ideally, you should know how many hours people spend on your site. Also note the page views. It helps you know which parts of the site are engaging and useful to them. It can help you make more decisions on your content marketing strategy. You’ll also know what your audience is currently engrossed in!
An underrated part of analyzing data analytics is the internal search. It’s all about the searches of the content of the website that users make. External searches are usually the ones being analyzed and optimized the most. But internal searches reveal the site navigation’s weaknesses. It also sees how effective a website is in addressing the needs of the visitors. Analyzing data analytics with regards to internal searches can help find inventory gaps which the website can take advantage of. The keywords that a user might use can be capitalized when someone is looking for a hotel site. For example, they use “Cape Town Hotel” for searching for a hotel. Then, they use your site to search “table mountain,” “pets,” and “babysitting.”
Outcomes
In general, your website visitors should perform actions that will increase your revenue. This desired action is known as the goal, and analyzing it determines which areas need improvement. You also want to analyze other KPIs. Ask yourself, is the user intent aligned with the website goals and objectives? On the other hand, user experience indicates how to influence the outcomes.
Not everyone who visits your website will translate into conversion. As an example, only 80 out of 100 visitors may visit the page toward the goals. This means the conversion rate is only 80%. Then, only 20 might go on the next step, meaning there’s only a 25% conversion rate. Again, only 10 pay you, so the conversion rate is 50%. Overall, the conversion rate for all visitors is just 10%. Don’t feel down, though! Breaking this up into events will let you analyze and optimize for every part.
User Experience
A fundamental part of analyzing data analytics is testing and determining the patterns of user behavior. This is vital to know which factors influence the user experience. This can influence their behavior as you improve your outcomes.
Segmentation in Analyzing Data Analytics
More importantly, you can segregate and examine users into groups when analyzing data analytics. You can refer to this process as segmentation.
Referral Source
You can categorize users based on where they came from. This is essential in analyzing data analytics. That’s because users who arrive from search engines behave differently than those who come from news articles. Some even type the URL directly.
Geographical Locations
Users from different countries, regions, provinces, and other locations have varying behaviors on your site.
Landing Page
As you may know, some users behave differently depending on where they entered your site. Analyzing data analytics entails asking what to do to affect the page where they land. You may also decide which features of the landing page you want to modify to persuade better results.
Browser, Connection Speed, Operating System
A high bounce rate for users that are low-bandwidth can mean that your site takes too long to load. This feature has a big impact on your conversion rate. Moreover, users who use open source technology differ from other types of visitors. Similarly, the same is true for users who use varying browsers.
In-Page Heat Maps
Fortunately, many applications and software can help you know exactly the parts of the site which users click on. These things allow you to produce information about which areas of the website are clickable but have little to no clicks. They also let you know the visual cues of the influence of your webpage. In short, you can use in-page heat maps to optimize your visitors’ click path.
Analyzing the factors that hinder your visitors from attaining your site goals is now easier. Now, it is easier with in-page heat maps. It could be the color of your page. Other times, it’s the tone of the text that was written. Everything affects your conversions, whether big or small. That is why changing one factor may lead to improvements or fewer conversions. Unforeseen consequences are typical here, so it’s vital to make sure you find the right cause.
© Image credits to Pixabay
Posted in data analytics
