Why Is Web Analytics Important?

Web analytics is the process of measuring, collecting and analyzing information about visitors to a web resource, its purpose is to increase the effectiveness of the resource and online advertising.

I suggest you clarify:

Web data is information characterizing a web resource, its users, their actions and sources of visits. For example: views, traffic, rejections, conversions, social dem, device, advertising channel, technical parameters of the site.

Web tools are a set of external and internal tools aimed at increasing profits from a web resource.

• External: all paid advertising, SEO, smm, email, messengers.
• Internal: website/application, online chat, lead catcher, internal advertising campaigns, promotions, etc.

Web analytics is the measurement and analysis of web data in order to make decisions aimed at optimizing the use of web tools.

Businesses use web analytics platforms to manage projects on the Internet. To analyze key performance indicators (KPIs) that define a business, such as the conversion rate or the share of advertising expenses.

Why is web analytics important?

I think it is possible to begin the explanation philosophically, with the help of famous phrases:

“If you can’t measure, you can’t control.”

“Measurements only make sense if they somehow influence business decisions.”

“Everything worth doing is worth measuring.”

When you sail your boat to point Y, you know the speed, fuel balance, consumption, distance to the place and time, there is a navigator — all this will allow you to arrive on time, and if you find the right way, then even before others. But if you need to travel tens or even hundreds of thousands of kilometers, then new priorities and metrics arise.

Why do I need web analytics?

To intelligently manage website marketing, it is necessary to measure the state of the site and advertising, and make decisions based on data.

It is said that web analytics is needed to increase user happiness by tracking how visitors interact with your site and advertising, to find and eliminate weaknesses. It sounds nice, but in fact, the ultimate goal is profit growth.

You spend money… increase your expenses on paid advertising, invest in SEO. How many clients come and how much does one attracted client cost? Which channel works better?

The task of web analytics is to prepare and analyze data for making decisions aimed at improving business efficiency. Reduce uncertainty in decision-making, for example:

• How can I measure the effectiveness of a website and advertising?
• Can I trust the reports?
• Do the monitored goals reflect the state of the business?
• At what stage do we lose potential customers and why?
• Which pages are the most or least conversion-oriented?

Web analytics will show you the most popular pages on your site, their conversion rate and the most popular purchase methods.

An inefficient web project takes money and can damage the brand. But how to understand the point of reference of efficiency? Measure and manage.

How it works: Web Analytics Tools

Analytical platforms measure the activity and behavior of site visitors.

For example: where they came from, by some link or direct visit, how many of them there were, how long they stayed on the site, how many pages they visited. A total of 500 similar metrics are measured.

Most analytics tools tag web pages using a JavaScript script in the code of the web page. This is called a counter.

The analytics counter is triggered every time a user visits the page. The script also collects other information such as time, device, browser, and geographic location (via IP address).

Cookies are used to track individual visits and identify repeat ones from the same browser. Some users periodically clear cookies, and browsers may have restrictions on counters. No analytical platform can give complete accuracy of the data, but the error does not exceed the permissible one. Therefore, the numbers in different instruments are slightly different.

We remember that measurement is about reducing the degree of uncertainty, not getting accurate values. Therefore, we can track the most important thing — the dynamics of indicators.

The most common web analytics services:

• Google Analytics;
• Yandex Metrics.

 

The following tools can be used in conjunction with them:

• Google Tag Manager — for configuration without a developer;
• Google Data Studio, Power BI, Tableau or Qlik — for visualizing data from multiple services.

 

There are other platforms, they are not free or their entry threshold is higher, so they are not so popular:

• Piwik Pro;
• Adobe Analytics;
• Kissmetrics;
• Mixpanel.

 

What Is A/B Testing And How Does It Increase Conversion?

Terms and definitions

Problems and disagreements often arise due to different understandings of the same words. To understand the language of web analytics correctly, let’s clearly define the concepts used.

Terminology in Google Analytics and Yandex Metrics is a little different, but the essence is the same:

Hit is a single user interaction with the site, an event of one type:

• Pageview 
• Screen View — viewing application screens.
• User Timing — tracking user time.
• Event — custom event
• Social Interaction.
• Ecommerce — e-commerce tracking.
• Exception — error tracking.

 

Session — a group of hits made by a specific user during a period of time: 

• The user has closed the page. 
• No activity for 30 minutes. 
• I came to the site from another source.
• A new day has come.

 

User — no, it’s not an individual, it’s a group of sessions within a single user (stored in cookies in ClientID). This is a statistical value, and the value depends on the date period selected in the report.

Page depth is the number of pages viewed by visitors.

The bounce rate is the percentage of sessions in which the condition considered a failure is reached. 

The goal is a meaningful, targeted user action. For example, adding to the cart, ordering, submitting a request, registering or subscribing. 

The conversion rate is the percentage of sessions with the completion of the target action. 

• Macro conversions are goals that directly affect business profits. For example: application, order.
• Micro-conversions are an intermediate action, on the way to an order or application. For example: viewing the terms of delivery, adding to the cart, viewing the service, subscribing.

 

The source is the resource where the visitor came from. A search engine (google, yandex) or a social network (facebook.com , youtube.com ) or another site (site.com ) or direct entry (direct).

Channel is the type of source. Each source can have one of the channels:

• organic: free search
• paid: paid search (cpc, contextual advertising)
• display: display advertising (advertising in the display network)
• social: from social networks
• referral: other sites (except search engines and social networks)
• email: mailing
• direct: direct access to the site, typed the site address in the browser bar

 

A segment is a selection of users based on certain criteria, for example: by source, by order amount, by date of first visit, by device.

The most common mistake is to just get started with Google Analytics and Yandex Metric, not tuning. Why is that?

Web resources are arranged in different ways, there is no way to create a universal analytics system that will take into account all the features of each.

Therefore, any system requires setting up additional events, conversions, filters, reports, and creating the necessary indicators that take into account the specifics of the site and the business as a whole.

The minimum you need to set up is tracking button clicks, sending forms, transactions and requests.

Basic concepts

1. Data validation. 
2. Analysis of “anomalies” on the graph in detail by day or hour. Find out the reasons.
3. Studying the trend. 
4. User segmentation. 
5. The KPI tree is the principle of the Minto pyramid. All metrics are interconnected. The dependence can be direct (one grows and the other grows) or inverse (one grows and the other falls). We are looking for the primary source of growth or decline. 
6. The principle of cuts. Any metric can be evaluated in different sections. 
7. The sales funnel. Separation by stages of the path to conversion. The most popular model is AIDA (Attention, Interest, Desire, Action) 

Find out also about How Web Analytics Helps Business

 

Conclusions

• Who needs it? Any digital project should start with analytics — you need to measure efficiency.
• Web analytics includes processes such as setting up analytics systems, creating KPIs, auditing advertising channels, conversion funnels, site weaknesses, preparing and testing hypotheses.
• The result of the work is an understanding of the situation and recommendations on what to do next. Identification of conversion growth points. Reducing the cost of inefficient budget spending.
• Budget — how much money is reasonable to invest in web analytics.