And the truth is: what web analytics system should be used in a particular case? The metric should probably be set when the site receives traffic from Yandex Direct, and Google Analytics when you water from Adwords… right?
Why choose?
You know what's the matter. In terms of scale and capabilities, analytics is much stronger. But Metrica has something that Analytics doesn't have. And Google Analytics has something that Metrica doesn't have. And both tools are important. So why choose when you can use them all at the same time! 😉
Therefore, on all projects I use two systems, regardless of the traffic source. And I have at least 2 reasons for this.
The first reason is you, and the second is all your dreams ...
Reason 1 - webview
Metrica has a tool that allows you to view a record of users visiting a site. The webvisor is a cool thing to understand how people behave on the site.
Webvisor - see the record of the visit
Reason 2 - Multi-Channel Sequences
But Google Analytics has something more valuable. The Multi-Channel Funnels report, which is also available in the Adwords interface, will allow you to learn more about what steps users take before converting. Very entertaining...
Here the most pleasant thing is that you can see how this or that channel is involved in the conversion. And assisted conversions will help with this.
A little about assisted conversions
He can go for a walk on VKontakte, visit YouTube, where he will stumble upon your remarketing, and then return to the site through an advertisement in mailbox and leave a request.
And according to this scenario, the conversion will be counted towards the last indirect visit. But in fact, the user did not start with him. There are several channels involved in the chain. And it may very well be that throw out one - and the conversion would not have taken place. The user's paths are inscrutable… 🙂
The Assisted Conversions report allows you to at least roughly estimate the degree to which a particular traffic source is involved in the success of your advertising campaigns. For me, in particular, this is an opportunity to prove to the client that with the help of search advertising there were not 44, but at least 44+17 conversions (example from the screenshot above).
You can play around with attribution in Yandex.Metrica, but Analytics has a lot more attribution models. Compare:
Attribution in Yandex.Metrica - not a lot 
Summary
For analytics, I use both Yandex Metrika and Google Analytics on all projects. Personally, Metrika gives me at least a webview (although I can live without it), and Analytix provides such important multi-channel sequences (and without them I don’t sleep so well at night). I recommend that you use both tools.
What do you think about this?
comments powered by HyperComments1. GENERAL PROVISIONS
1.1. This policy of WEB IT LLC regarding the processing of personal data (hereinafter referred to as the Policy) is approved in accordance with paragraph 2 of Art. 18.1 of the Federal Law "On Personal Data" and applies to all personal data that WEB IT LLC (hereinafter referred to as the Operator) may receive from the subject of personal data.
1.2. The Policy applies to personal data received both before and after the approval of this Policy.
1.3. This Policy is a public document declaring the conceptual foundations of the Operator's activities in the processing and protection of personal data.
2. PERSONAL DATA PROCESSED BY THE OPERATOR
2.1. For the purposes of this Policy, personal data means:
2.1.1. Personal data received by the Operator for the conclusion and execution of an agreement to which the party, or beneficiary or guarantor, is the subject of personal data.
2.1.2. Personal data received by the Operator in connection with the implementation of labor relations.
2.2. The terms and conditions for terminating the processing and storage of personal data of the subject of personal data are determined in accordance with the legislation Russian Federation okay.
3. PURPOSE OF COLLECTION, PROCESSING AND STORAGE AND LEGAL BASIS FOR THE PROCESSING OF PERSONAL DATA
3.1. The operator collects, processes and stores personal data of the subject of personal data in order to:
3.1.1. Conclusion and execution of the contract.
3.1.2. Implementation of labor relations.
3.1.3. The implementation and execution of the functions, powers and obligations assigned by the legislation of the Russian Federation to the Operator on the basis of and in accordance with Art. 23, 24 of the Constitution of the Russian Federation; Federal Law "On Personal Data"; Federal Law "On Information, information technology and on information protection” and other requirements of the legislation of the Russian Federation in the field of processing and protection of personal data.
4. TERMS OF PROCESSING PERSONAL DATA AND THEIR TRANSFER TO THIRD PARTIES
4.1. The operator processes personal data using automation tools and without using automation tools.
4.2. The operator has the right to transfer the personal data of the subject of personal data to third parties in the following cases:
4.2.1. The subject of personal data has expressly expressed his consent to such actions.
4.2.2. The transfer is provided for by the current legislation of the Russian Federation within the established procedure.
4.3. When processing the personal data of the subject of personal data, the Operator is guided by the Federal Law "On Personal Data", other requirements of the legislation of the Russian Federation in the field of processing and protection of personal data and this Policy.
5. RIGHTS OF THE SUBJECT OF PERSONAL DATA
5.1. The subject of personal data has the right to receive information regarding the processing of his personal data, including information containing:
5.1.1. Confirmation of the fact of personal data processing by the Operator.
5.1.2. Legal grounds and purposes of personal data processing.
5.1.3. Methods of personal data processing applied by the Operator.
5.1.4. The name and location of the Operator, information about persons (excluding employees of the Operator) who have access to personal data or to whom personal data may be disclosed on the basis of an agreement with the Operator or on the basis of federal law.
5.1.5. Processed personal data relating to the relevant subject of personal data, the source of their receipt, unless a different procedure for the provision of such data is provided by federal law.
5.1.6. Terms of processing personal data, including the terms of their storage.
5.1.7. The procedure for the exercise by the subject of personal data of the rights provided for by this Federal Law.
5.1.8. Information about the performed or proposed cross-border data transfer.
5.1.9. The name or surname, first name, patronymic and address of the person who processes personal data on behalf of the operator, if the processing is or will be entrusted to such a person.
5.2. Information regarding the processing of personal data of the subject of personal data, provided to the subject of personal data, should not contain personal data relating to other subjects of personal data, unless there are legal grounds for disclosing such personal data.
5.3. The subject of personal data has the right to demand from the Operator the clarification of his personal data, their blocking or destruction if the personal data is incomplete, outdated, inaccurate, illegally obtained or not necessary for the stated purpose of processing, as well as take measures provided by law to protect their rights .
6. INFORMATION ON THE REQUIREMENTS FOR THE PROTECTION OF PERSONAL DATA
6.1. The most important condition for the implementation of the objectives of the Operator's activities is to ensure the necessary and sufficient level of security of personal data information systems, confidentiality, integrity and availability of processed personal data and the safety of data carriers containing personal data at all stages of working with them.
6.2. The conditions created by the Operator and the mode of protection of information classified as personal data make it possible to ensure the protection of processed personal data.
6.3. The Operator, in accordance with the current legislation of the Russian Federation, has developed and put into effect a set of organizational, administrative, functional and planning documents that regulate and ensure the security of processed personal data.
6.4. A security regime for the processing and handling of personal data has been introduced, as well as a regime for protecting the premises in which the processing and storage of personal data carriers is carried out.
6.5. The person responsible for organizing the processing of personal data, the administrators of personal data information systems and the administrator of the security of personal data information systems have been appointed, they have defined responsibilities and developed instructions for ensuring information security.
6.6. The circle of persons who have the right to process personal data has been determined, instructions have been developed for users on working with personal data, anti-virus protection, and actions in crisis situations.
6.7. The requirements for personnel, the degree of responsibility of employees for ensuring the security of personal data are determined.
6.8. Employees processing personal data were familiarized with the provisions of the legislation of the Russian Federation on ensuring the security of personal data and the requirements for the protection of personal data, documents defining the Operator's policy regarding the processing of personal data, local acts on the processing of personal data. Periodic training of these employees on the rules for processing personal data is carried out.
6.9. Necessary and sufficient technical measures have been taken to ensure the security of personal data from accidental or unauthorized access, destruction, modification, blocking access and other unauthorized actions:
6.9.1. An access control system has been introduced.
6.9.2. Protection against unauthorized access to workstations, information networks and personal data bases has been established.
6.9.3. Protection against malicious software and mathematical influences has been installed.
6.9.4. Regular backup information and databases.
6.9.5. The transmission of information over public networks is carried out using the means of cryptographic information protection.
6.10. A system of control over the procedure for processing personal data and ensuring their security has been organized. Planned compliance checks of the personal data protection system, an audit of the level of personal data protection in information systems personal data, functioning of information security tools, detection of changes in the mode of processing and protection of personal data.
7. ACCESS TO THE POLICY
7.1. The current version of the Policy on paper is stored at the address: 129085, Moscow, Prospekt Mira, 101V, building 2.
7.2. The electronic version of the current version of the Policy is posted on the Operator's website on the Internet.
8. UPDATING AND APPROVAL OF THE POLICY
8.1. The policy is approved and put into effect by an administrative document signed by the head of the Operator.
8.2. The Operator has the right to make changes to this Policy. When making changes in the name of the Policy, the date is indicated latest update editions. The new version of the Policy comes into force from the moment it is posted on the Operator's website, unless otherwise provided by the new version of the Policy.
8.3. The norms of the current legislation of the Russian Federation apply to this Policy and the relationship between the subject of personal data and the Operator.
You wander in the dark if you don’t know the audience of your site and don’t track how this or that text “enters”, how changes in the structure and design of the site affect its traffic, which channels and media partners bring you the most traffic. The first step to "enlightenment" should be the registration of the site in web analytics services. This is the basis for all further marketing activities.
The most important and popular services for collecting statistics about a site in Runet are Google Analytics, Yandex.Metrika, LiveInternet. However, it is not necessary to install everything at once. A little further I will explain why.
1. How to install the Google Analytics code
1.3. A page will open where you need to specify the following parameters:
- website or "Mobile Application";
- "account name";
- "Name of the site";
- site URL;
- industry;
- Timezone.
1.5. Going to the "Tracking code" section, we get the tracking code, which must be inserted on all pages of the site before the closing head tag.
2. How to install the Yandex.Metrica code
Why can the numbers in Yandex.Metrica and Google Analytics differ?
- The tracking code is not installed on all pages of the site.
- Incorrect time zone settings.
- The same counter is installed on several sites.
- Various filter settings are set.
3. How to install LiveInternet code
LiveInternet is one of oldest systems runet statistics. The main advantage of the service is the simplicity of the interface, which captivates novice webmasters. Regardless, I don't see much reason to use this system statistics. Google Analytics and Yandex Metrica will allow you to get a wider range of data for analytics. Perhaps, for a small site, LiveInternet will be useful for monitoring the effectiveness of content, but in the future it is better to use the Google Analytics + Yandex.Metrica bundle.
3.1. To start the installation, go to the registration page.
If the site provides advertising services, it is advisable to install an open informer - a counter of web analytics systems that will be visible to users. Potential customers of advertising services can immediately see the traffic to the site and make an approximate conclusion whether the site is suitable for their purposes.
4. How to use Google Tag Manager
Use Google Tag Manager when adding tracking codes. First, it's convenient: once you've learned how to work with the service, you don't have to add google codes Analytics, Yandex.Metrics and LiveInternet on each page of the site separately and each time disturb the programmer if something needs to be changed.
4.1. We create new account, specify its name.
4.4. For further convenience, we create a variable that will contain the tracking ID. Go to the "Variables" section.
4.6. Specify the name of the variable, for example "UAID", and select its type. In this case, "constant" because the value of the variable will not change.
4.8. Let's start creating tags. Go to the "Tags" section and click "Create".
4.11. As the tracking identifier, we specify the UAID variable we created earlier.
4.12. The tracking type is pageview.
4.13. In the activation conditions, select "All pages", and then click "Create tag".
4.14. The tag appears in the list.
4.15. Create a tag for Yandex.Metrica. Specify a name and select "Custom HTML Tag" from the list.
4.16. In the HTML field, copy the tracking code from Yandex.Metrica and click "Next".
4.17. In the activation conditions, specify "All pages" and click "Create tag".
4.18. We install the GTM code on the site after the body tag. 4.19. After creating the tags, click "Publish Container".
4.20. We confirm the publication.
4.22. You can check the correctness of the GTM code installation on the site by going to the site and going to the "Real-time" - "Overview" section.
conclusions
- If you are not a web analytics professional, feel free to add LiveInternet to your site. The service has basic functions for audience assessment and analysis of traffic sources. For more advanced data analytics, it is recommended to install the Google Analytics + Yandex.Metrica bundle.
- Adding tracking codes is more convenient through Google Tag Manager. Then you don't have to manually publish the code on every page of the site.
- In the case of Google Analytics and Yandex.Metrica, I recommend the following procedure: registering the site in statistics systems - transferring data to Google Tag Manager - publishing the code on the site.
It's time not only to count the visits, but also to understand how many of them are targeted! Goals in Metrica and Analyticscs will help you understand website traffic and user behavior. Let's count everything: how many, who and when viewed the “Contacts” pages, filled out forms and sent orders. detailed instructions about what goals are needed and how to set them up for commercial sites.
Set up Yandex.Metrika and Google.Analytics?
Yes, I advise you to set goals both there and there, regardless of which analytics system you use more.
Firstly, statistics affect the ranking of the site - the better behavioral factors on the site, the higher the PS will put it in the search results. Yes, of course, the dependence of the presence of the counter and the goals in it with the positions in the search is not direct, but whatever one may say, it is useful to work on improving the conversion.
Secondly, there are traffic sources that are best evaluated in Yandex.Metrica - Direct, and others in Analytics - AdWords. Even if in this moment you do not have one or another source of traffic, this does not mean that it will not appear later.
Thirdly, two systems are always better than one. This allows you to check the data if necessary. Nobody is perfect, for example, Kaspersky's "Data collection protection" component prevents NM from collecting information, but it does not catch GA.
What goals should be set?
View important site pages
- "Contacts"
- "About company"
- "Requisites"
Users who are interested in your company, want to know the address or details - target.
How to set up?
Yandex.Metrica
Path: “Settings” -> “Targets” tab -> “Add target”
There are several options for URL matches: matches, contains, starts, and regular expression. For the purposes of visiting specific page I advise choosing “contains”. For example, for the page site.ru/contacts -> select the type “ contains” and paste the value /contacts
Remember: always choose clear and meaningful names for the targets, as if you have a lot of them, then you will definitely get confused.
Google.Analytics
Path: “Administrator” -> “Goals” -> “+Goal” -> “Custom” -> “Landing Page”
Completely similar to Yandex - three matching options, for this purpose, select “starts” and add a value - /contacts. If you know the value of the goal (for example, every contact page view brings you 100 rubles) - use it.
Buttons
- "Add to cart"
- "To favorites"
- "Comparing to"
These buttons can be many different. Clicks on such buttons are useful actions. Such goals can be configured through events and virtual pages.
How to set up?
Yandex.Metrica
In the interface Select the metrics for creating such a goal - “JavaScript event”, come up with a name for the goal and a unique identifier - NAMEGOAL.
On the site the target is configured via a JavaScript event: yaCounterXXXXXX.reachGoal('NAMEGOAL'), where XXXXXX is the ID of the counter, and NAMEGOAL is the name (identifier) of your goal. The names of each goal must be unique. For example: yaCounterXXXXXX.reachGoal('clickfeedback').
Google.Analytics
In the interface Analytics the whole process is exactly the same as for creating a page view goal. The only difference is that instead of the value of the real page, we substitute the value of the virtual page.
On the site the target is configured by sending the virtual page value − page view: ga('send', 'pageview', '/NAMEGOAL'), where NAMEGOAL is your virtual page, for example: ga('send', 'pageview', '/clickfeedback').
Tracking code
There are two placement options: either through onclick into the button itself, or into the JS file by event, for example, in JQURY - the click event.
1 option
| 1 2 3 | < input type= "button" onclick= "yaCounterXXXXXX.reachGoal("clickfeedback"); ga("send", "pageview", "/clickfeedback"); return true;" value= "Feedback" > !} |
Option 2
| 1 2 3 4 | $(".class" ).click (function () ( yaCounterXXXXXX.reachGoal ("clickfeedback" ) ; ga("send" , "pageview" , "/clickfeedback" ) ; ) ) |
$(".class").click(function()( yaCounterXXXXXX.reachGoal("clickfeedback"); ga("send", "pageview", "/clickfeedback"); ))
Filling out and submitting forms
- Feedback
- back call
- goods order
- service requests
- review
These kinds of goals are best set up using “compound goals” (sales funnels)
- called \ went to the page \ went to the basket
- tried to send
- successfully sent
Thus, you can see the funnel: how many users left the first step, how many from the second, etc. If the form is placed directly on the page, then the first step can be omitted. Information on filling out the form will allow you to manage (add or remove) the number of form fields based on site statistics, and not assumptions.
For example, a form fill funnel feedback in Yandex.Metrica:
How to set up?
Yandex.Metrica
In the Metrica interface, select "Compound goal", come up with a name for the goal and for each step. The type of each step can be different - either a page view or a JS event, or their combinations. I gave an example, a goal that consists of two steps and each of them is an event.
The tracking code for such a goal on the site will consist of two JS events: yaCounterXXXXXX.reachGoal('NAMEGOAL'). You need to place each event, as already described above, either in the onclick of the button, or in some kind of JS event. The most important thing is that the code should work at the right moments, a successful submission should work only after passing all validation (both JS and server-side), i.e. after the actual form submission.
Google.Analytics
In the Analytics interface, nothing changes in this case either. In the main field of the goal - you need to add "Landing page" \ "Virtual page" of the last step. Next enable " Subsequence“, and already prescribe all the steps, NOT including the last step already added (it's already added at the beginning).
By the way, setting the final goal for submitting the form through the plugin Contact Form 7 for WP done in an elementary way - so.
How can I check if I did everything right?
In Yandex.Metrica, to check whether goal achievement information has been sent, you can use the _ym_debug parameter in the page URL with a value of 1. In this case, the browser console (call - Ctrl + Shift + J or right-click) will display goals achievement messages. For example, http:///?_ym_debug=1
Google.Analytics has a mode “ real time“, where the goal count will immediately start working.
E-commerce (if online store)
Detailed collection of information about orders and customer behavior on the online store. How to set up extended e-commerce I already wrote -.
If you have any questions, you can ask them in the comments or look for answers in Yandex.Metrica - and Google.Analytics - help.
January 05, 2019
Working with various projects, Internet marketers have to deal with the fact that site owners do not always initially set both of these counters for themselves. According to portal statistics ruward.ru(for June 2016), 67% of Runet sites have only one installed system, and 20.72% put two systems on their site.
Runet counters
Moreover, the share of LiveInternet in 2016 was 27.28%, which is almost 3 times more than that of Google Analytics:
The popularity of counters
But if you go to w3techs.com(a resource that analyzes websites), we will see the following distribution:
Yandex.Metrica is installed on 76% of Russian-language sites (November 2018)
Each of them has a number of advantages over the opponent. Having reduced the object of study to two units, we will try to make a detailed and objective analysis of these two tools in terms of convenience and functionality.
Google Analytics and Yandex.Metrika. What do they have in common?
1. Classic approach– asynchronous loading of the counter code. The code is called asynchronous because it is executed in parallel with all other scripts. What does it mean?
By default, all JavaScript is executed sequentially, and if there is an error in the first code or an element that delays the loading of other scripts, then an error can creep into the tracking of visit statistics. Asynchronous code is executed in parallel with other processes and is the very first one when the page is loaded. This ensures its 100% actuation and accurate data collection.
2. Data storage - aggregated data and data in the form of tables
When you visit the site, you see aggregated data in the reports. Aggregation is the process of combining elements into one system. And data aggregation is the process of collecting, processing and presenting information in its final form. Data on users, pages, cities, etc. That is, some summary statistics for all users.
Also, all data is stored in the form of tables. In fact, each report is a separate table with data, where the main key of the report (left side) is the metric.
In large projects with large amounts of data (petabytes - 10 to 15 bytes), it is very common to use non-aggregated data, where there are a much smaller number of tables, but longer ones, and make highly effective filters and groupings based on them. With the help of them, you can see data about each entry, view, visit, etc.
Working with raw non-aggregated data requires high efficiency from the system, since all calculations must be done at the time of the user's request. This requires a columnar DBMS. Using raw data, you can build complex funnels, custom attribution models, combine data from different sources through the API.
In addition, in Metrica 2.0, the approach to the data structure was revised. Previously, Yandex.Metrica stored pre-aggregated data for a fixed set of reports. IN new version all data is stored in raw form and reports are built on the fly using the open source column DBMS developed by Yandex ClickHouse. That is, you can take data from the API and upload it to the ClickHouse database.
ClickHouse is also used in external projects, for example, to analyze metadata about events in the LHCb experiment in CERN(about a billion events and 1000 parameters for each event), and as a repository in the Tinkoff Bank project.
Google has a cloud database product with the highest processing speed for huge amounts of data. This Google Big Query. The data in both web analytics systems is presented in the form of tables. That is, each report has a key attribute on which information is displayed.
In small online stores and landing pages, you can do without ClickHouse and Big Query. But when it comes to a large number data and hundreds of thousands of daily events, analysts go beyond traditional Yandex.Metrics and Google Analytics. For example, it is advisable to use ClickHouse in the case of advertising networks, RTB, online game analytics, when it is necessary to work with sensor data and monitoring various events, as well as telecom data, financial transactions and stock analytics.
General - table view
3. What Yandex.Metrica and Google Analytics have in common is .
Parameters is a property of an object that can be measured. For example, "City" from which the session originated, "Device type" (PC, mobile devices or tablets), "source or channel" of traffic, landing page URL, etc.
Metrics are quantitative values represented as a number. It can be:
- sessions;
- users;
- transactions;
- income;
- etc.
4. Behavioral characteristics
Yandex.Metrica has a section called "Maps". It consists of 4 reports:
- link map (shows statistics of clicks on links on the site);
- click map (shows statistics on clicks on the site);
- scroll map (shows how the attention of site visitors is distributed in certain areas of the page);
- form analytics (shows exactly how site visitors interact with forms);
There are no similar tools in Google Analytics, with the exception of a separate extension for Google browser Chrome, which is called . One of the functions of this plugin is just "click map" And "click map" in the form of illuminated thermal zones.
A separate Metrics section contains segments that allow you to select the necessary data from the total amount of statistical information.
Examples of Yandex.Metrica segments
E-commerce
On March 27, 2018, Yandex stopped supporting the outdated ecommerce data transfer method, which used a predefined set of visit parameters.
It used to be passed like this:
Deprecated e-commerce transfer method
And the order was sent using the reachGoal method:
yaCounterXXXXXX.reachGoal('TARGET_NAME', yaParams);
Now the formation and sending of the order looks like this:
New e-commerce transfer method
Reminds me of the Google Analytics design? And this is what she is. Instead of setting variables via var and sending the order by the method reachGoal now the order is formed through the data layer dataLayer.push() Now, in order for you to transfer data to Google Analytics and Yandex.Metrica, you only need to install one code for two counters. After the correct settings, a tab with e-commerce reports will appear in Yandex.Metrica:
E-commerce reports
In July 2018, the developers introduced a new "Visitors" report. It collects anonymous and compiles a detailed history of visits, all actions (hits) of each of them.
Report "Visitors"
Most visit data is collected automatically by the Yandex.Metrica counter. However, it is often necessary to supplement the collected data with your own. For example, statistics on orders for certain goods or information about the actions of authorized users may be of interest.
Yandex.Metrica allows you to associate with a visit an arbitrary set of data, called visit parameters. This data can be displayed in reports, as well as used in grouping and segmentation conditions. However, it is often not the statistics of visits of site visitors that are of interest, but information about the visitors themselves. That which does not change from entry to entry. For example, the city of delivery.
Required fields
The last thing I wanted to talk about in the block "Yandex.Metrica" is a data visualization. In mid-October 2018, Yandex presented its new Yandex DataLens service, which is part of Yandex.Cloud.
According to the company's specialists themselves, it will be a platform that will allow:
- visualize data using various datasets that you upload to Yandex.Cloud;
- developers to publish their solutions on connectors (data sources) in the marketplace and earn money on them;
- any companies, agencies interested in data, other people's research, buy ready-made templates third party developers.
For example, I analyzed the birth rate depending on various factors (level and lifestyle, employment of women in production, ecology, the role of religion, etc.), and posted my research on the marketplace. Companies that may benefit from my data, such as research institutes, can purchase it, or if they have their own data, they can insert it according to certain rules into my template and get a quick visualization.
The cost of using will depend on the number of requests that companies will make. The service supports loading data from clickHouse, Yandex.Metrica, BigQuery, MySQL, and other sources.
Data sources Yandex DataLens
In addition, Yandex.DataLens will be able to distribute various rights to its partners. For example, Yandex itself has more than 5,000 partners and more than 15,000 analysts and marketers who need any data. Thanks to the new service, Yandex can create one dataset and distribute certain rights to all participants.
The interface of the product is very simple and intuitive, just like all other products of the company. The Yandex.DataLens metrics are stylistically very similar to "Parameters" and "Indicators" in Google Analytics and Google Data Studio (blue and green).
Data visualization
GoogleAnalytics
In August 2018, Google began rebranding all marketing services, then Google AdWords became Google Ads, Google Marketing Platform united double click And Google Analytics 360 Suite, A Google Ad Manager - Double Click for Publishers And Double Click Ad Exchange.
old and new logo Google Analytics
So far, Google has made the following updates:
- added buttons at three levels (account, resource and view);
- changed the user management interface;
user management
- updated navigation menu;
Google Analytics navigation menu
- introduced a new option after the updated rules for the processing of personal data introduced on May 25 (GDPR);
Data storage
- added a new report. With it, you can estimate the probability with which the user will make a conversion within the next 30 days;
Conversion Rate Report
- In the summer, for all users, he activated a function that allows you to track users on different devices.
Series of reports " Miscellaneous devices»
More than 90+ standard reports for all occasions are available in Google Analytics, divided into different blocks - Custom reports, Real-time, Audience, Traffic sources, Behavior and Conversions.
One of the reports in Google Analytics
If we talk about the "chips" of Google Analytics compared to Yandex.Metrica, then I would highlight the following:
- Reports are a very useful tool when testing new goals and events when you're not sure if your conversions were set up correctly. And a consistent path through the site with a check and a marked entry will give you information after a few seconds.
In real time
- Reports "Comparison" are built on the basis of data on other sites in your industry, which are provided by users of the system. you just give google access to information on your site, and in return you get the opportunity to compare performance with similar projects from a large base of players on the market.
Comparison Reports
- Representation
There are several levels of hierarchy in Google Analytics account(account). Account - resource - view. Views are a set of data about a site, mobile application or devices. They allow you to define how the data from the parent resource will be shown. Thanks to them, you can solve various kinds of tasks:
- track all data on the website without sharing statistics;
- track data for a specific source (organic search, paid traffic, social media etc.);
- track data by device type (separately mobile, PC and tablets);
- track data by domain and subdomain separately;
- track data on specific country or region to the exclusion of all others;
For example, the issue of excluding statistics on referrals from internal company IP addresses is always relevant in order not to take into account test visits or visits by your employees. Or collecting data only for a certain type of source. For example, an SEO specialist is unlikely to be interested in paid traffic from contextual advertising Google or Yandex. Or if you have several offices in other cities, you can create views for each region and provide access to each of them separately.
Representation
All these settings are implemented through filters at the presentation layer. Google Analytics creates the first view by default "All website data".
There are no such access levels in Yandex.Metrica. There you can give only for viewing or for editing, and you cannot hide some of the statistics from the reports.
- in Google Analytics, they allow you to select certain fragments of it from the general traffic, analyze it, and use them as a basis when creating an audience to display ads to a specific audience.
- Search terms
Google Analytics differs too much from Yandex.Metrica big amount encrypted search queries. That is, we are provided with less raw data on how the user interacted with us from organic search. Metrica has a separate report "Sources - Searches", which quite well determines the search phrase by which the user went to our site. Analytics adds more than 80% of traffic to (not provided) and other (depending on the report).
Search queries in Yandex.Metrica and Google Analytics
None of the tools show each other's queries. Google Analytics, for example, marks Yandex search queries as (not set). As an additional means of struggle, you can use Yandex.Webmaster and Google Search Console. We will talk more about the problem of “not set” and “not provided” below.
- contextual advertising
If we consider the differences in the functionality of contextual advertising products (Yandex.Direct and Google Ads), then there are no special differences. By linking Google Analytics with Google Ads, you will have access to all account statistics. The same is true for Yandex.Metrica, when you add "Metrica counter" in the corresponding field in your Yandex.Direct advertising campaigns. But in the number of reports provided, these two services have a difference. Yandex.Metrica contains only 3 reports, while in Google Analytics there are already 11 of them:
Say that Yandex.Direct has a Report Wizard, which is enough to optimize advertising? You will be right in part, since we are talking about functionality Yandex.Metrics and Google Analytics, not their brothers. Ads also has a lot of interesting things.
- Cross device
To link different devices of the same user in Google Analytics, there is a User ID function. It allows you to combine different sessions and activities during those sessions with a unique identifier. This tracking is also called cross-device tracking.
Previously, in Yandex.Metrica, as well as in GA, this User ID could be used, the system must know that the user is logged in to the site. But not all sites have authorization, and not all users are authorized at this moment. This approach was replaced in Metrika by the machine learning technology "Crypta". Demographic targeting, interests, etc. work on the same basis. Now the User ID does not need to be determined programmatically, the algorithm does it for us.
In Yandex.Metrica, to display data in a report, you must have goals or use e-commerce. Report "Cross device" is available if the site has received more than 100 visitors in the last week from at least two different devices.
Cross-device report in Yandex.Metrica
For the time being, only Yandex worked this way. With the advent Google features Signals July 2018 and Report Series "Miscellaneous Devices" It has become easier for online marketers to track users across devices without creating any additional User ID views and defining a variable programmatically.
Different Device Reports in Google Analytics
pivot table
Let's summarize:
Google Analytics vs Yandex.Metrica
Personally, my opinion in this confrontation is the following - the greatest return on the use of web analytics tools can be obtained only if you use the capabilities of several services at the same time, because:
- A- they complement each other;
- B- you can insure yourself in case of a malfunction of one of them;
- C– both are constantly updated and each has new features;
I use Google Analytics most of the time in my practice. All metrics, all reports, all hypotheses are all decided and accepted based on GA data. Yandex.Metrica is an auxiliary tool for me. But sometimes projects come that do not have the Analytics counter installed. Or the site uses other services. Then you have to work with what you have. And there is nothing wrong with that.
Google Analytics vs Yandex.Metrica: similarities and differences
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