Google Analytics and Yandex.Metrika for effective site markup

Hi all! I’m Oleg Korolev, director of analytics at the company AGIMA. We often receive tasks related to site markup. Customers want to know how users behave in their web applications: what they read, what they scroll through, where they get stuck for a long time, etc. This information helps to evaluate how convenient and intuitive user paths are. In this article, I will show the capabilities of the two most popular analytics tools – Google Analytics and Yandex.Metrica. It will be interesting for novice project managers, product managers and analysts – I collected the most basic in the text.

Why web analytics is cool

With the help of web analytics, we can obtain data about site visitors, their behavior and interaction with it. This data helps to understand the needs of users, optimize the site, make it as effective as possible.

More specifically, web analytics helps:

  • find out how many people visit the site;

  • where they come from;

  • how to find the site;

  • how much time is spent on each page.

Thanks to this data, we can see which parts and elements of the site attract the attention of users and which need to be optimized, where client paths break and why they do not reach the end.

For example, we see that some page has a high bounce rate. Most likely, this means that it does not meet the expectations of visitors or that it has problems with UX or incorrect traffic. Let’s say the wrong link got into the ad, and now users get to the wrong page of the site. Analytics helps to find such problems and solve them.

Web analytics also allows you to evaluate the effectiveness of marketing campaigns. We can track which traffic sources bring in the most visitors, which marketing channels are more effective and lead to more conversions. And this, in turn, allows you to more intelligently build a marketing strategy and save your budget.

For example, for the site of brand N, we have identified key metrics that reflect the goals and results of a marketing campaign:

  • Conversion. Using the conversion funnel, we tracked the number of site visitors who completed the target action – filled out the form, leaving their contact information.

  • Traffic and its sources. We analyzed the traffic sources that brought users to the site (search engines / social networks, the advertising campaign we are interested in, etc.), which of these sources turned out to be the most valuable in terms of attracting new users.

  • Time on site and bounces. We studied how much time users who came to the site thanks to an advertising campaign spent on the site and which pages they left most often.

As a result, the bounce rate of this cohort of users turned out to be 14% lower than that of the representatives of the organic traffic cohort, the conversion to the target action was 8% higher. At the same time, our marketing campaign did not become a traffic leader – search engines remained the main source.

The client and I evaluated the marketing campaign positively, because, despite the not-so-impressive values ​​of the new user acquisition metric, those who were “attracted” turned out to be exceptionally valuable as a result. The logic of the marketing campaign was based on the results of a qualitative study of the needs of different segments of the target audience, which were validated using A / B tests. Of course, this affected her success.

Popular analytics tools

Most often, we use Google Analytics and Yandex.Metrica in the site markup.

Google Analytics is one of the most widely used website analytics tools in the world. It provides detailed data about visits, user behavior, traffic sources, conversions, and more.

Yandex.Metrica is a popular analytics tool in Russia and the CIS countries. It provides a feature set similar to Google Analytics. This is data about visits, user actions, traffic sources, as well as goals and conversions.

Key features and capabilities of both tools

Key features and capabilities of both tools

What metrics and reports are provided by Google Analytics and Yandex.Metrica

Attendance and users:

  • The total number of visits. This metric shows the total number of visits to a website over a given period.

  • unique users. Displays the number of unique users who visited the site in a given period.

  • Sessions. This is the number of user interactions with the site during one session.

Traffic sources:

  • organic search. Visitors who find your site through search engines such as Google, Yandex, Bing, etc. This traffic is tagged Organic or Organic Search.

  • Direct traffic. Visitors who enter your site’s URL directly into the browser’s address bar or use bookmarks. This traffic does not come from another website or search engine.

  • Social media. Visitors who come to your site through social media links.

  • Partner sites. Visitors who come to your site through links on other websites that are not search engines or social networks.

  • Paid advertising. Visitors who come to the site through advertising campaigns in search engines such as Google Ads or Yandex.Direct.

Other sources. Traffic that cannot be unequivocally assigned to one of the above categories.

Behavior on the site:

  • Average time on site.

  • Pages per session. It displays the average number of pages that visitors view in one session.

  • Failure rate. The metric shows the percentage of visitors who left the site after viewing only one page.

Conversions and Goals:

  • Goals. Both tools allow you to set and track goals, such as completing a form, placing an order, or registering on a website.

  • Goal funnel. It allows you to see the path users take on your site to reach your goals and determine at what stages problems or user churn occur.

Demographic information:

  • Gender and age. Both tools provide information about the gender and age of users, allowing you to better understand your audience and fine-tune your marketing strategies.

How to use conversion data to improve your sales funnel and optimize user experience

As you know, all sales go through certain funnels, at the end of which there are users who have successfully completed the product. Web analytics systems help build sales funnels. With their help, we can improve user paths.

Now I’ll tell you how to use data on conversions and sales funnels when analyzing a site.

Analyzing conversion data can help you identify the stages at which users are most likely to abandon a purchase. This could be a checkout page, form completion, or other funnel steps.

Conversion data helps you determine which elements or page layouts lead to higher conversions. To do this, you can use A / B testing: change something on the page – headings, buttons, colors or element layout – and then analyze the test results and implement more successful options.

Analytics data helps to determine what content on the site attracts more users: which pages or articles are of interest to the audience and lead to the fulfillment of goals. Based on this information, you can make your content more relevant and engaging.

Time on site, bounce rate, and user journey data can also be used. If users leave the site immediately after viewing a page, it may have content or navigation problems.

Conversion data allows you to evaluate the effectiveness of marketing campaigns.

How to write the right technical specification for site markup

1. Define goals and objectives. What do you want to measure and track on the site? These can be targeted actions, ROI, conversion funnel, purchasing behavioral metrics, etc. It is better to set the most specific goals.

2. Define the required markup. Decide what data you want to track and collect on the site. This may include information about page visits, events. For example, button clicks, form submissions. Consider what information your marketing or product team needs.

3. Be aware of site features and privacy requirements. Consider site features such as dynamic elements, single page applications, and other interactive features. Make sure the markup will work correctly and collect the necessary data in such cases. Also pay attention to data privacy requirements and make sure that your markup complies with privacy regulations.

4. Describe the verification and debugging process. Develop a process for testing and debugging markup before running it. Make sure the markup tags and codes work correctly and collect the right data. Test the markup on different pages of the site and make sure it reflects your needs and goals.

5. Document your TOR. Prepare a detailed TOR that describes all the requirements and markup details. Include information about the goals and objectives, the web analytics system chosen, required markup tags and codes, site features, review and debugging process, and any other specific requirements.

What’s next

Choosing the right metrics, collecting data correctly, analyzing them thoughtfully are all the first steps to ensure that the site brings the results you expect. If sales are not going on, the number of users is falling, or feedback like “everything is inconvenient” arrives every now and then, then web analytics will help you understand what are the reasons and how to change the situation.

In the article, I tried to briefly explain why it is important to study user behavior and what tools will help with this. Next time I will tell you how to properly conduct A / B testing and why a business needs it at all. Ready to answer questions in the comments or in our telegram channel. There we tell you how to work on a digital product so that it is cool, useful and popular. Come read!

And on June 14, we held an online meetup about the Data Driven approach to creating digital products in medicine. We talked about user acquisition and retention metrics. Meetup can be viewed Here.

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