Setting up end-to-end analytics google analytics. All data is at your fingertips. What data is shown in the report

Today we will talk about end-to-end analytics and how to implement this tool inside Google Analytics.

What are we going to talk about:

Why do you need end-to-end analytics?

How to implement it in practice?

What errors can there be and how to solve them?

What is end-to-end analytics?

What situation might you have - a large number of different advertising channels through which users find your site. These could be channels that we manage, e.g. paid advertising, contextual advertising or special communication channels. This could be advertising that we manage in a less direct way - e.g. search marketing in search results search engines. These can be any advertising channels.

Simply put, we invest some money, for example 1000 USD, in our marketing. These 1000 dollars are distributed in some shares to different communication channels:

$300 for search engine optimization,

$100 for price platforms.

That is, we can distribute these amounts evenly or unevenly. And we need to understand how effective our investments are, and which ones work out better. For example, where is it better to invest - in SEO, Yandex Direct or Google Adwords. Or close everything and work only with price platforms or some aggregators. Only after analysis will we understand when there will be a greater return on the money we invest.

How to calculate the return and efficiency of these investments in different advertising channels?

On this moment Most businesses or marketers who work with Google Analytics consider cost effectiveness solely based on some kind of user communication actions. Those. the user can call or leave a request, or even, if this is the case of e-commerce, go through the entire ordering procedure and at the last step click “Place an order”. It's great if we have the ability to accept payment from the user at this step or at one of the last steps. When the user has the opportunity to enter his or her credit card or pay via PayPal. In this case, we clearly understand that these are the people who placed the order, these are the people who bought from us.

This is ideal. But in reality? The number of transactions on the Internet using cards or other payment instruments is relatively small. I have statistics for last year or the year before, something in the region of 3-5%, this is not even a dominant percentage, i.e. it's not 50%. We understand that a large number of audiences pay whatever they want.

And the fact that the user communicated (filled out an application to purchase a product or sent us a letter or used an online chat) does not tell us about the fact of the purchase. It is rather a certain desire to buy, a certain step before real purchase. And if we look closely, and for yours real businesses Let's take the number of these communications (i.e. the number of times each individual user contacted the business with the desire to buy) and the number of purchases we will see: - the number of communications we have is much greater than the number of purchases.

For example, 100 users went through the entire checkout funnel and only 50 of them actually paid.

Users may not pay various reasons- they may not like something at the last moment, there may be a million situations why the user did not buy, but, nevertheless, such a situation arises quite often.

What is displayed in Google Analytics?

In Google Analytics we display (if the goals or block are configured correctly) e-commerce) information about transactions, products that the user has selected. In this case, we see, sort of, sales. But these sales amounts or the number of transactions that we have inside Google Analytics may not coincide with what we have in CRM. If so, then we may actually make incorrect decisions regarding the effectiveness of these channels.

For example, we see that we have a lot of people leaving a request or filling out a free search basket from Yandex, Google, but at the same time the number of people who paid is much less. In this case, when we calculate the effectiveness of this channel, if we only take into account those actions, only applications and not actual fees, we may be greatly mistaken in the effectiveness of this particular traffic source.

Maybe we have another one Google source Adwords has a smaller number of completed purchase requests, but at the same time the conversion into actual payment is quite high (100 people go completely to the checkout cart with Google Adwords, 95 of them pay). And we understand that in this case this channel will be clearly more effective for us than free search in Google if we work with the tool

The second point is the moment of taking into account all communications. Users can contact us different ways. We can quite easily and simply track the fact of communication, i.e. what happens directly on our website. If the user left, filled out the form feedback or has completely completed the ordering procedure, we will definitely see that this particular person has done something useful for us.

But if the user called us, sent an email to our regular mailbox, if he came to the store, if he used online chat, then by default all this information is not collected. And for very large quantity For businesses, we may have a situation where the number of these communications through call, letter, offline and online chat will be more than 50-60-70%, and the number of people who fill out the form may not be very large, but in fact we are the only ones and we record only those people who filled out the form with us.

Let us formulate three big problems:

1. We do not see real payments from those linked to advertising or non-advertising channels that we use.

2. We do not take into account all communications by default. Those. Thus, we cannot compare the data that we have in CRM - that this particular order came from this particular traffic source and the user used, say, a call, a letter or something else. If so, it is quite difficult to make decisions about the effectiveness of advertising channels inside Google Analytics. And then how to make decisions about the effectiveness of a particular channel, advertising campaign inside Yandex Direct. and in general any entities that we transfer to Google Analytics (regions, social media, any other information) are difficult. We actually don't know any of this. In fact, the data we have inside Google Analytics cannot be directly trusted.

3. We do not take into account returns

By law, in different countries within 14 days, the user can return the product without giving any reason if it remains in presentation. If you have a business related to clothing, if you have a business related to some things that may potentially not suit the user, then the number of returns may be large. And by default they are also not displayed unless this is implemented additionally.

1. the user did not understand how he contacted us, or rather, we understand, but we cannot connect this with the advertising channel

2. we do not see the exact payment

3. We do not accept returns

The analytics process works as follows - we have some kind of advertising, this advertising generates some kind of traffic, users who visit the site, and actually some of these users become leads and they go to the sales department.

But in fact, in order to correctly collect data and correctly take into account the effectiveness of traffic sources, we need a different scheme. We have traffic that is generated by visitors. These visitors can use our various instruments for communication with business, and We must take each of these tools into account within CRM. But at the same time, we must also understand inside CRM that this user who used the online chat came from a specific advertising campaign, for example, Google Adwords for some reason key query. And as soon as a decision is made here in CRM, i.e. in fact, the manager who is handling this order will set the status that this client has paid, we immediately transfer information about this successful payment to the analytics system. We can also transmit all sorts of communication things in order to build funnels and see the effectiveness of not only advertising tools, but also other methods of communication.

What does the new analytics system look like in practice?

We may have such a situation - we have implemented a callbackhunter, which gives us a certain number of leads and applications. And we think - oh, how cool, great, good tool, we will pay, but if we see the overall picture of the redistribution of ways to contact us, we will see that this callbackhunter can simply take a bite out of other channels - phones, forms, online chat

Thus, before the implementation of callbackhunter we had 100 calls per month and after the implementation of callbackhunter the same 100 calls per month. Those. it did not bring any additional value to the business

Accordingly, from the site, by default, data should also be transferred to analytics systems, but here more information about how the user interacted with the site itself, how he looked at various sections, how he looked at the product card, how he clicked on some buttons that were important to us, and so on.

And after we take and implement such a scheme

If we take into account each communication channel, if we take into account returns, if we only transfer data from CRM to Google Analytics from the moment of actual payment by the user (only at this moment) - only then can we build such beautiful funnels. And then we will have a complete picture of the effectiveness of our marketing. We may have different advertising channels that turn into applications, i.e. users make some kind of communication, then at this stage we see the situation regarding the effectiveness of advertising channels in terms of applications. We see how much one application from Yandex Direct, or one application from VKontakte, or one application from somewhere else costs us. We see the number of applications, we see the conversion rate (i.e. the ratio of those people who left an application to the traffic that came to the site in general).

Actually, we can see deeper, we can see the deal. This is not just an application, but let’s say a transaction, where some kind of communication between the manager and the user has already taken place, they draw up some details, i.e. not just an application, but a transaction, and, accordingly, we can also transfer this information to Google Analytics.

We also have information about paid transactions, i.e. when the user actually bought. And then, here, we can see the effectiveness of the selling price. Efficiency in terms of ROI, efficiency in terms of profit for each of the advertising channels, campaigns and any other entity.

For example, we can clearly understand that Yandex Direct brought us 100 leads, but there were 2 sales, and the ROI, let’s say, is 103%. But Google Adwords brought us 50 leads, less than Yandex Direct, but at the same time we had not 2 sales, but 48 sales. Let's say the conversion from applications to sales is much higher with Google Adwords and then our ROI is 500%. Conclusion: despite the fact that Yandex Direct brings us more applications for us. but from the point of view of business, money, profit, Google Adwords is effective.

But without such a funnel we will never say this, if we do not set up all the nuances in the analytics, then we will be blind.

It is very important to see not only the situation associated with one sale. There are many businesses where we can have much more sales per user than one, and even more often a situation arises where our marketing may pay off not from the first sale, but from the second, the third, the fifth.

It is necessary to take into account all the sales that this specific user made, who came through this specific advertising channel Yandex Direct, Google Adwords or whatever. In this case, if we implement this scheme, we will have a complete picture of how to implement this matter.

We solve problems of end-to-end analytics

There are many different different services, which solve this problem automatically. Those. there is some kind of setup needed, some of the services are more focused on CRM, some are more focused on managing contextual advertising, some are more focused on call tracking, some are purely systems end-to-end analytics. I gave three examples, but there are more. We can implement an end-to-end analytics system using these services, and they are more or less tailored to solve the problems that arise so that we can see the entire funnel, but these services have a lot various disadvantages, everyone has their own.

Probably the main disadvantage of all these services is that they are quite closed systems tailored for one narrow task, either high-quality tracking of calls and end-to-end analytics, or managing contextual advertising and somewhere end-to-end analytics. And the downside is that they are difficult to modify if we have new tasks. Therefore, today we are talking about how to implement this task with using Google Analytics, namely, so that within our analytics we can see in full a report like this, where we have an advertising source, any - paid or free, where we have complete information on the stage of interaction, our costs, the effectiveness of our ads, where we There is information on profitability.

We can enter communication goals into such tables, and, in fact, inside Google Analytics we can measure each of the stages with metrics that best show us the effectiveness of a particular step. We can have several reports, each report will show different metrics. Then we will see the big picture, in fact, see our entire funnel.

How to set up Google Analytics correctly?

First, you need to use advanced e-commerce functionality.

The advantage of expanded e-commerce is that we can take not everything that is implemented there, but only some part, namely the part about specific payment, and actually not take all the other functionality. That is, implement it in parts. But in this case, our implementation scheme will change. And at the last step, on the thank page you page we will not have the same code that transmits information about the transaction to Google Analytics, but will be last step funnels. Roughly speaking, at the last step (transaction) on our website, we will simply transmit information that the user has completed this step, that he has somehow communicated with us.

Moreover, we can transmit this information using such functionality as check out options not only for forms on the site, some ordering procedures, except check out, but also for any other ways for the user to contact us. We can see that the user went to check out or called - and for us this will be equivalent. But just the last step - we will transfer information about the transaction from the CRM.

In order to implement this entire system we need three steps:

1) remember the user id from any communication channel. Those. it doesn’t matter how the user contacted us - he can call, he can write to us by email, he can go offline or do anything. We need to record it from each channel unique identificator. I will say a little more - this is a unique identifier that Google Analytics gives to each user.

2) The second thing we need to do is upload expenses for advertising tools. This is probably a less mandatory step, but it is important from the point of view of calculating various indicators such as ROI and so on. Those. Without this everything will work, but with this we will have much more data.

3) The third step - we transfer successful payments from CRM to Google Analytics only upon actual payment. Moreover, we transmit both payments (the fact of payments) and returns (if we have them).

Setup. Step one

If you use your Chrome browser, for example, go to some site where Google Analytics is installed (in general, this is almost any site), not counting maybe some social networks, click right click, click “view code”, then you will see additional block, which can be on the right or below.

Now this is called application, previously resources, where we have such a tab and a Cookies sub-item, if we go there, we will see a cookie called GA and this unique number is clientID.

Those. this is a unique identifier that is issued to the user (each browser) by Google Analytics. If a user visits, for example, the same site a second time, then his unique identifier will be exactly the same. But if he comes to the site for the first time, this identifier will be different.

Our task:

— take this clientID. WITH using JavaScript, PHP or any technology we can get this clientID.

- we can transmit it along with some kind of communication. For example, if this is a procedure for placing orders through the website. Here we have standard fields: first name, last name, phone number, what the user wants to buy, etc., i.e. a lot of various information. We can add another field, which we will call clientID and, taking this unique identifier, transfer it to our CRM, thus expanding it by one additional field.

If the user called us, we can also take and get this identifier. clientID is a unique identifier to which we associate all the information within Google Analytics about this user’s visits. For example, the initial traffic source through which it came, etc.

If we see this clientID in our CRM, we can then transfer it and expand Google Analytics’ knowledge of what exactly this user bought. Accordingly, we have different communication channels - call, letter, online form, online chat. Each of these communication channels can be taken into account.

Call- here we need dynamic call tracking, with which we can replace the phone number for each client, user, who is recorded in Google Analytics. Accordingly, upon a user’s call, we will be able to obtain a unique clientID from the call tracking system.

Letter we can send to the address [email protected]. The letter will be sent to [email protected], but at the same time we will retain our identifier. Those. we will show each user a unique mailing address, but all mail will be sent to our main mailing address [email protected].

If this form, then everything is very simple here. If a user places an order with us through the website or submits a form, then along with his contact information we also take the clientID, a unique identifier, and transmit it.

If this offline, then we can display a banner with a QR code on the site, in which this clientID will be encoded and oblige our managers to ask for the presence of this QR code, if it is, then we read it as usual mobile phone with a camera. Thus, this code will be saved with us.

If this online chat, then here we have the opportunity to pass some custom field to administrative panel, with whom the sales manager works - there will be a name, correspondence, phone number and, among other things, clientID.

Setup. Step two

There are many services that allow you to do this. Most of them are paid. For example, OWOX BI - they have the ability to import data on advertising costs.

Setup. Step three

The third step (the most important) is transferring data from CRM to Google Analytics. This step is implemented using Measure Protocol technology. This is one of the APIs that Google Analytics has internally. With this API we can expand the data we have. Those. data, on the one hand, is collected from us using regular code that we place on the site. And another way is to transfer data from any place where we have Internet. This could be a CRM, any website or device connected to the Internet. From there we can transfer some information using the Measure Protocol to Google Analytics. In particular, in solving our problem, we can transmit information about the successful transaction that the user made.

The last step. Analyzing ready data

In this case, we receive ready-made data - we have a source, channels, sessions, costs, profit, price per transaction, number of transactions, number of conversions and ROI (already ROAS). We can add some other necessary and important data to such reports, but, in any case, here we can fully see the situation that we have. And then we can clearly say which advertising channel is more effective or less effective for us.

We can visualize our reports. For example, we can use Google DataStudio to display all this information visually and work with this information and conveniently analyze advertising campaigns.

When transferring data via measure protocol, a new session is created within Google Analytics for this user and this session with direct/none.

Problems arise here from time to time, because the attribution model that exists inside Google Analytics is the last indirect click, and if the user has already visited once through direct, if we have a long enough sales procedure, he could come back to the site after the initial advertising channel and , accordingly, the last indirect click will not be our initial source through which he made the conversion, but, say, another channel or the same direct.

What can we do?

We can overcome this in the following way - we can, along with clientID, transmit the value of this metric if this is a paid advertising channel, or the value of the source and channel of traffic that the user used when he made the communication.

Attribution only works for channel sources, not regions or other session variables.

If we need these additional characteristics, for example, where the user came to us from and what he bought, from the point of view of the city, then we can also transfer this information to CRM, we will link this data, and then our transaction will be recorded exactly in the region where the user was when he left the application.

Measure protocol may not always work correctly and this must be controlled. Periodically, problems arise with data transmission via this protocol if we use POST requests, often fewer problems if we use GET requests. Experience suggests that when implementing this scheme, it is advisable to have a log file in which to record each request that was sent by Google Analytics, because Google Analytics may simply respond that everything is fine, but in reality everything may not be fine. If we have a log file we can quickly find any errors.

If the CRM is a mess, then Google Analytics will not help.

For example, if we have currencies inside CRM written differently - somewhere we have rubles, somewhere dollars, somewhere hryvnia, somewhere euros. And, if we do not bring this data into one form or do not take it into account at all when implementing the entire scheme, then our Google Analytics data will be inaccurate.

The same with the payment accounting process itself - if we have a lot different statuses, which we have or may have upon successful payment, then here we also need to be very careful when implementing this entire scheme, so that there are no moments when the payment is fixed, but, in fact, the money has not come and will not come.

In this article we will explain in detail what end-to-end analytics is, how to use it and how to save money on advertising budget. AND how can you earn money, using end-to-end analytics when setting up the Customer’s advertising campaign. If you are actively advertising in different channels, but you can’t calculate the effectiveness of all these activities and find out which gives the most benefit? To do this, you need to set up end-to-end analytics. , guest posts with a link, social networks - now all sources of clients and orders will be taken into account. Read on to find out where to start and how to achieve this result.

• a summary report or a single tool that collects statistics on all advertising channels and analyzes conversions;

a detailed picture of where the client came from and what request he used;

a visual path of the client from attraction to the amount of the check that he left with you.

What does end-to-end analytics provide?

CRM, web statistics and CallTracking become one, and you gain insight into which channels perform better.

You will be able to influence the sales funnel.

You'll see which tools don't work so you won't waste time or money on them.

• You always know how much an application and a visitor cost.

An end-to-end analytics report allows you to make accurate predictions about the future of your business.

Sales and online statistics will give you an understanding of exactly how your sales mechanism works and what attracts the buyer.

End-to-end analytics saves you time on data aggregation when it is performed by a special tool or specialist.

Peculiarities

• The formation of a sales funnel should occur simultaneously with the implementation of end-to-end analytics. It will not be possible to “jump in on the fly” - the reliability of the data may suffer as a result.

End-to-end analytics is useful because at each stage of the buyer’s movement towards the target action there is a different indicator, and from it you can understand whether your ad is effective, conversion percentage, repeat purchases, etc. It is illogical to judge the quality of ads based on completed sales - between There are several intermediate points in these stages, and this may be the case.

It is with the help of end-to-end analytics that you will begin to calculate your ROI indicator and see how well your advertising investments have paid off.

UTM tags must be on all sources in order to distribute all visits and actions clearly across channels.

How to implement?

For end-to-end analytics you will need special service like "Yandex.Metrica". and how to set it up, read the link. Here, ideally, it will be possible to “link” data from many sources: Yandex.Direct, Google AdWords, Yandex.Market, Facebook, VKontakte, Google Merchant, and also, for example, Podarki.ru. All this can be found out from a specific service before starting work. For example, the list above is Roistat's capabilities, and that's not all.

Roistat

Using end-to-end analytics in Roistat

Offers statistics on 22 indicators and 11 advertising integrations. There are 14 days free period. Cost: from 177 to 1623 rubles. per day, depending on the size of your business and the number of projects.

Attention:

The advantages of the service are that you receive a package of useful reports, it has its own good CallTracking, simple integration with advertising channels and analytics for various channels, convenient SMS notifications about expenses and profits, as well as ROI fluctuations. There are also disadvantages: a somewhat abstruse interface, integration with some CRMs occurs with errors, termination of work means receiving data in XLS format, and then as you wish.

Calltouch

End-to-end analytics are also offered by the Calltouch service. Here you can calculate a budget to suit your needs. Free trial period not in the service, the estimated cost for a small project is 5,400 rubles. To view the interface, you need to register, which is approved by the service manager during business hours. Here you can link Yandex.Metrica and Google Analytics data to get extended SEO data. The service has its own visit statistics, worthy of CallTracking, as well as the ability to order modifications to the tool to suit the personal needs of a specific project. Disadvantages: emphasis on calls, interface requires improvements, ready-made integrations No.

Alytics

An end-to-end analytics service with automation of contextual advertising, which it previously specialized in. In addition, it allows you to flexibly integrate with CRM, and do it for free if you top up your account. approximate cost for three small projects - 5100 rub.

Using end-to-end analytics in Calltouch

There are some peculiarities: there are few advertising channels for automatic tracking, visits are displayed only from Google data Analytics (nothing to compare with). Among other things, the service is quite young, and not all processes have been streamlined yet.

Google Analytics

You can combine everything into Google Analytics, but you need special knowledge or someone who will control the entire array of data, set parameters and do correct conclusions. This is either through an acquaintance or for a fee. The possibilities are quite wide, so it’s definitely worth paying attention to this option, even for the money. A few more arguments in favor of delegation:

working with formulas is difficult;

it’s hard to “make friends” with the interface if you are a beginner, and the ultimate goal is end-to-end analytics;

Without call tracking nothing will happen.

Conclusion: Google Analytics is needed big projects or perfectionists with experience.

Who doesn't need it?

There is a specificity of business for which end-to-end analytics is not urgently needed. If you sell cars or apartments, there is a big risk of losing a client. End-to-end analytics is designed for slightly more short cycle making decisions and evaluating the results of promotional activities. In this case, the costs of end-to-end analytics may be unreasonably high. If you sell high-margin products and business is objectively going well, you are looking for new market sales, don’t get hung up on end-to-end analytics - you don’t need it. If your product is extremely popular in a short period of time, and the fashion for it quickly passes, quickly create landing pages, “pour” contextual advertising on them, and don’t think about complex analytics. A regular application report will be enough for you.

The "End-to-End Analytics" report is designed to evaluate the effectiveness of each of your advertising channels, both as a whole and within the framework of an advertising campaign, keywords, landing pages, and more. In the report designer, you can see all the data from advertising costs and traffic to your website, to calls to your company and closing a deal.

Using the report you can generate transparent system KPIs for your marketing department or advertising contractor to plan advertising campaigns in the most effective advertising channels.

2 What data is shown in the report?

• number of impressions advertisements or banners;
• consumption for a given channel/campaign in Yandex.Direct and Google Adwords, or for channels for which consumption was entered manually;
• number of unique calls;
• number of applications from the site;
• total number of leads;
• CPL (cost of acquiring a lead);
• the number of transactions taken on by sellers;
• number of successfully closed transactions;
• profit and revenue;
• ROMI.
• how indicators change over time;
• cost of attracting a lead, client, sale, time to close a deal, etc.

3 How to connect?

Access to the End-to-End Analytics report is determined by the terms of your tariff plan for the product "Calltracking".

In order to receive an assessment of the effectiveness of your advertising campaigns, you need to set up integration with services and, and in order to display data on applications from the site - To receive data from CRM, you need to set up integration with the corresponding CRM. , .

4 Built-in report forms (templates)

Use the built-in report forms (templates) to evaluate the effectiveness of advertising campaigns and channels, evaluate the performance of the landing pages of your website, and advertising costs in the regions:

1. Venues: costs for advertising platforms, visits, number of leads, cost per lead, etc. Find the sites that work most effectively and comply with the media plan;
2. ROMI: ROMI indicators by advertising platform, number of transactions, profit from marketing activity;
3. Campaigns: results of advertising campaigns in various promotion channels. Look at the results and compare them with the planned ones, find the most effective campaigns;
4. Landing: the effectiveness of the “landing” pages of your website (those on which the Client is invited to buy a product or service): page traffic (sessions), conversion of sessions into leads, etc.;
5. Request channels: the effectiveness of channels for Customers to contact your company. Monitor that Clients use the most conversion channels for sales;
6. Regions: advertising costs, number of leads and CPL by region and city.
7. Keywords: most effective keywords, V contextual advertising, which bring you sales and referrals.

5 How to start using the report?

To open a report on the website " Personal Area» select “Tools > Dynamic Call Tracking > End-to-End Analytics”. Next, select:

1. name of the VCT widget;
2. select the report form in the “Reports” field, see Figure 2.

Figure 1 - “Personal Account” website page

6 What does the report consist of?

The End-to-End Analytics report displays a graph and a table.

The graph shows changes in indicators over time. By selecting one or another indicator in the report table, you can see changes in this indicator on the graph. For example, Figure 2 shows a graph of costs for the advertising platforms “Yandex.Direct” (green graph) and “Google AdWords” (blue graph).

Figure 2 – Graph of the “End-to-End Analytics” report

The report table displays indicators for each advertising channel, source, advertising campaign, region or landing page. The structure of the table (that is, the list of columns and rows) corresponds to the report form you previously selected. The appearance of the table is shown in Figure 3.

You can change appearance tables, that is, determine the order in which columns and rows are displayed. For this purpose, the following settings are implemented:

• data grouping;
• column display;
• data filters.

Figure 3 – Table of the “End-to-end analytics” report

7 Manually setting up the table structure

7.1. Groups

You can group all report data, and also configure the order in which the groupings are displayed in the table. Maximum amount(depth) of data groupings – 5.

For example, Figure 4 shows the grouping settings window, the grouping conditions are as follows:

1. all report data should be grouped by campaign;
2. data about a specific campaign should be grouped by source (by the name of the sites from which Clients went to your site);
3. data about each source should be grouped by promotion channel.

Figure 4 – Setting up data grouping

7.2. Filters

Using filters, you can display only certain data in the report, for example, look at the number of calls, transactions and the amount of sales for a specific advertising channel or set of advertising campaigns.

Figure 5 shows the filter settings window, the filtering conditions are as follows: the table should contain the number of calls and transactions for advertising on Google.

Figure 5 – Setting up filters

7.3. Columns

You can show or hide any columns in the report table. For example, Figure 6 shows the column display settings window, the display conditions are to show the columns “consumption”, “impressions”, “sessions”, “conversion of sessions into leads”. The “Conditions” field displays the order of the columns in the table. You can change the order in which columns are displayed by dragging the column names with the mouse cursor.

Figure 6 – Speaker setup

8 Report designer. How to use?

The report designer is convenient feature to create your own report forms, the structure of which is determined by you. You can assemble a part from the parts of the designer, and from the list of report parameters you can select those from which your report will consist. Save the report you created and use it to get updated data.

You can create your own report form; to do this, on the “Personal Account” website, select “Tools  Dynamic call tracking  End-to-end analytics”. Next, select:

1. period of report generation, see Figure 1;
2. name of the VCT widget;
3. Click "Generate Report". You will need to enter the name of your report form, see Figure 7;
4. configure the table structure manually as you need;
5. select “Save changes to report”, see Figure 8.

Figure 7 – Entering the name of your report form

9 How to download the report

To download the report table, you need to click on the “Download” button, then select “Download report in CSV (data grouping level)”. The table with the corresponding data grouping depth will be downloaded to a CSV file.

Figure 9 - Report table. Download button

10 Important restrictions

1. Data is downloaded from the Yandex.Direct and Google Adwords services at night for the previous day.
2. The report does not automatically display expenses by advertising channels other than those listed above. You can enter expenses for these channels, for example, organic (SEO) traffic manually in the report or in the Expenses tab. You can read about how to enter expenses in detailed manual follow the link below.

You receive many calls and requests every day from potential clients. End-to-end analytics helps you know exactly which of them are profitable and which are not.

The article explains what it is and how to implement it. Thanks to Konstantin Chervyakov, commercial director of Ringostat, for the methods.

What is end-to-end analytics and why is it needed?

As a rule, most people associate efficiency with ROI, ROMI, CTR, etc. For e-commerce - also the e-commerce module in Google Analytics (if it is advanced, this is quite close to the topic. However, 90% of online stores use the regular one).

All these indicators are not about end-to-end analytics. Yes, they can be supportive, especially if the sales cycle is long. From them you understand in time that everything is completely bad, or vice versa. But final decisions should be made based on real data.

This is true for any type of business, except in rare cases.

Applications and calls seem to be targeted, but they don’t bring clients. Or there are fewer sales per campaign, but the check amount is higher and includes products with higher margins. There is a risk of making a wrong decision.

For your judgment and choice - 3 types of systems, depending on complexity and advancedness.

Level "Axe"

This can hardly be called an end-to-end analytics model. But since many small and micro businesses at the initial stage cannot afford paid tools, this option deserves attention. As practice shows, not everyone knows about it.

The set of tools is simple, with minimal, sometimes zero, budget costs.

• Google Spreadsheet, Excel;
• CRM or site admin with application sources;
• Google Analytics and/or Yandex.Metrica. The first gives more opportunities, but Metrica has its own features that Google does not have - a web viewer, reports on peaks of visits;
• Automatic or semi-automatic.

Many businesses use automatic dynamic call tracking. The system shows a unique phone number for each visitor, in order to then match the call with a specific user and find out more about him: what queries he entered, what campaign worked, what pages he looked at, etc.

Everything is available up to operating system devices.

Semi-automatic call tracking is more primitive and requires routine work:

The principle is this: every user on the site sees unique code. The manager requests it in order to manually associate the call with a specific session.

50-60% of calls can be recorded in this way, but, as a rule, after 2-3 months managers get tired of this hassle. In this case, everything depends on the human factor.

It is important that the manager does not forget or confuse anything. This is an additional burden for him: instead of selling, he enters promotional codes. The company is losing profits.

To be fair, we note that this method is inexpensive. And sometimes it's the only one affordable option- for example, for micro-businesses with a small budget.

Implementation principle

Users come to the site, make certain actions. Everything is recorded by the analytics system. When placing orders or applications, information about sources goes to the admin panel or CRM.

The simplest model does not have a combination of these tools, so we upload the data to Excel separately.

Here is an upload from CRM - these are all closed transactions (case from Ringostat agency):

Applications from the site, in our example - registrations, indicating sources, campaigns and keywords:

And the same sample for calls:

Excel skills make the job easier, but it still takes time. The lack of automation is the main disadvantage of the model.

At the initial stage, when the traffic is small and the budget is low, this is enough, but over time you have to expand the capabilities. Especially if the company can afford more advanced technology.

Level "Automatic"

• Google Analytics - everything is tied to it;
• CRM system;
• Automatic call tracking;
• Automatic import of OWOX BI expenses;
• Microsoft Power BI (optional).

You can leave the same Spreadsheets for visualization and reporting, but Power BI has more features and has an automatic link to GA. Cost: $9-10 per user per month.

Implementation principle

Based on requests, we set up a goal in GA - “Transactions”. Information about visits is collected automatically.

99% of call tracking services transfer data to GA.

For calls, there are WebHooks - triggers that we send in real time.

Then data on closed transactions must be transferred to GA. Popular systems- retailCRM, amoCRM - allow you to upload them directly. Either you can create your own connector in 1 week, or entrust this task to a programmer. In the end you get full control over business metrics at Google.

What do you see as a result in GA? Here is a screenshot of one of the Ringostat clients:

The Cost Per Acquisition column shows how much money you spent. “Cost” - how much you “paid” for visitors. “Revenue” - how much income it brought in.

Minuses

To understand the shortcomings of this level, let’s analyze the data structure of the analytics system:

This is how Google Analytics works: a person visits a website and generates a session. Within the framework of it, he performs actions (hits): views pages, calls, sends requests, downloads materials, etc.

At first glance, everything is correct in terms of hierarchy.

The problem is that in GA you only have aggregated data.

1) There is no access to a specific user and session, and this limits the capabilities of analytics. You cannot take a visitor and see what he did on the site, how many times he visited, what actions he performed during a certain session.

2) With large volumes of traffic - about 40,000 sessions per day - there is a risk of sampling (for large projects).

This is when Google takes part of a group of visitors - a sample of 5-7% - and transfers its behavior according to its own mathematical algorithm to the entire population. As a result, you see distorted data.

All that can be done is to customize the report, but this is hindered by type restrictions: one parameter cannot be included in the report with another, you cannot add more than two parameters, etc.

4) Cannot be transferred personal information. The basis is Google's privacy regulations. This further complicates the challenges of end-to-end analytics.

Level "Machine gun"

Let's look at 2 options.

Option 1:

• Google Analytics;
• Automatic call tracking;
• Cloud (Google Bigquery) or own database (MySQL, Mongo);
• Excel, Spreadsheets, Power BI, Data Studio, Tableau, Qlikview.

Your own database is more difficult to implement. That's why we're looking at Bigquery. This cloud service With high speed processing.

OWOX BI can do streaming in Bigquery. This is data interception from GA in raw, non-aggregated form. Thanks to this, you can ask any questions regarding the audience, behavior, its dependence on various factors, income for example. In general, test various hypotheses as much as you like, without restrictions.

To draw any conclusions, you need to visually represent tables from Bigquery in the form of graphs, charts, etc. Eat paid services Tableau and Qlikview - they provide advanced visualization.

Option 2:

• Kissmetrics or equivalent (Mixpanel, Woopra, Amplitude);
• Automatic call tracking.

Kissmetrics replaces points 1, 4 and 5 of the previous version. This is the so-called user-based, or person-based analytics system. All the “conveniences” are here, unlike GA: the program itself collects data, including in raw form, gives access to users, sessions and allows the transfer of personal data.

Implementation principle

If you have Kissmetrics or an analogue, you upload all the information there and connect the CRM system. In the case of a database, you throw streaming from GA, etc. into it. and select a program to visualize the results. While Kissmetrics already has visual reports.

Let's find out the cost of a lead in Google analytics.

In previous articles, we described the theory and some of the capabilities in Google Analytics. Now it's time to show the setup using a real example.

Our task was to display the “Lead Cost” (requests)

So let's get started:

1. We collect all requests. Setting up the goal “Requests accepted + targeted calls + callback”

Since we can receive requests from application forms on the website, call back and by phone, we will need to configure all 3 goals. And then make a general “All leads”

A. The “Accepted Application” goal will include all requests from the forms that are on the site.

Setting: Goals /// Own /// Goal name “Accepted applications” /// Events /// Category equals “Accepted application”

b. The “Callback” goal will include calls from the callback widget.
We used the Starton call tracking service, which transmits events to Google Analytics. When the user fills out the callback form and clicks the “Call me back” button, an event in the “callback” category will be triggered in Google Analytics
We will write it into the goal.

Setting: Goals /// Own /// Goal name “Callback” /// Events /// Category regular expression"callback"

V. Targets "Targeted calls" will include calls in which the conversation lasted a certain amount of time.
In our example, a conversation that lasted more than 60 seconds will be a target call. We will also configure it through call tracking “Starton”, which transmits the “target” event when a target call is made.

Setting: Goals /// Own /// Goal name “Target calls” /// Events /// Category equals “target”

d. Now let’s set up the general goal “Requests accepted + targeted calls + callback”
Setting: Goals /// Own /// Goal name “Application accepted + target calls + callback” /// Events /// Category regular expression “Application accepted|callback|target”

Important! If, having visited the site, one user leaves a request through the site form, then orders back call and calls, then 1 target will work, not 3.

2. Let's move on to setting up the transfer of expenses.

Important! For more detailed statistics, it is necessary to register the main tags

Let's set up two imports:
“Facebook” which will transfer expenses from Facebook and Instagram.
“My target” which will transfer expenses from mytarget and classmates.

Import of expenses will be transmitted using the “Owox bi” service.
Detailed instructions for transferring expenses from advertising sources to google analytics look

3. Setting up the “Lead price” indicator.

Once the cost data starts flowing into Ga, we can configure the “Cost of Lead” metric through the “Calculated Metrics” function:

We need to set the formula: Cost (expenses) * 1.18 (to take VAT into account) / goal (accepted application + callback + target call)

Setting: Name: Lead price /// external name calcMetric_LeadCost /// type: Currency (decimal format) /// formula ((Cost)) * 1.18 / ((Requests accepted+target calls+callback (Achieved transitions to goal 3)))

Also for the report you need to set up the “Cost with VAT” indicator. The setup is similar.

4. Building a custom report.

Let's move on: Special reports /// My reports /// + report
Setting: type Analysis
Indicators:
- sessions
- new users
- bounce rate
- price including VAT
- accepted applications(reached transitions to the goal)
- targeted calls (reached transitions to the goal)
- callback (reached transitions to the goal)
- accepted applications + targeted calls + callback (conversion rate for the goal)
- accepted applications + targeted calls + callback (reached transitions to the goal)
- lead price

Options:
- Source or channel
- Campaign
- Keyword