End-to-end analytics system for contextual advertising. End-to-end analytics: overview of configuration methods

Without end-to-end analytics, all your efforts to make money online can turn into one endless nightmare. Advertising doesn't work - and you don't know why. People don't buy - and you don't understand how to fix it. The site doesn't sell - and there's nothing you can do about it.

To prevent this from happening, you need an “X-ray” that will show exactly what is happening in your funnels and how to improve them. End-to-end analytics will become such an X-ray.

In this article we will look at the simplest and most effective scheme for setting up end-to-end analytics in 5 steps. And you can do it for free, with your own hands, literally in one evening.

As a short introduction, let's look at the example of my website to see how end-to-end analytics systems work and what they are needed for.

What is end-to-end analytics and how it works

End-to-end analytics is a system that allows you to track everything that happens inside your sales funnel. From the moment a potential client first sees your ad, right up to the time he places an order and pays money.

Sometimes all these actions can be tracked in one place, and sometimes you need to configure several programs to do this. But the main thing is that all your indicators are before your eyes. and you can control them. And when we control something, it means we can manage it (increase and improve).

Here, for example, is what a sales funnel with configured end-to-end analytics might look like.

An example of end-to-end analytics in action

In order not to go far, let's look at this site. whichever you are on right now. From the outside it may not be noticeable, but I also have my own sales funnel with configured end-to-end analytics.

I warn you right away that my sales funnel is built a little unusually, because this is blogging, information business, and other “obscurantism”. In a more traditional business it will look a little different.

But we will look at and build a traditional funnel a little lower, and here we at least have the opportunity to look at specific numbers.

So, here are the steps my sales funnel consists of:

1. A person goes to my site
2. A person goes to the subscription page for my “Contactless sales” newsletter
3. A person subscribes to my newsletter
4. A person studies my free materials and purchases a paid package

Everything is so simple and clear. But to track all the indicators, I have to use two whole various systems analysts.

The first system is tracking a person from the moment they visit the site until the moment they subscribe (step 1 - 3). Here I use Yandex Metrica. The second system is tracking a person from the moment of subscription to the moment of purchase (steps 3 - 4). Here I am using the service JustClick.

How I find weak points in my funnel

To understand why I haven’t become a billionaire yet, I open the indicators of my sales funnel and see where there are “holes” in it through which money flows.

The first thing I do is go to my Justclick store and see how many payments I received during the reporting period. In our case, the reporting period is one week.

Here I see the following picture:

Within a week, 39 people subscribed to the “Contactless Sales” newsletter, and I earned 8,460 rubles. Is it a lot or a little? Frankly speaking, it’s not the ultimate dream. I would like 10-20 times more. So we have to look weak links in the funnel and strengthen them.

Based on the justclick indicators, I see that after subscribing everything is going quite well. 4 paid invoices out of 39 subscribers is a conversion rate of 10.2% into payment. The average bill is 2115 rubles (8460 rubles divided into 4 payments). These are very decent indicators for an automatic sales funnel.

I received the most clients in a week from the “Direct Calls” source. This is exactly my blog where you are now. The conversion to purchases from people on the blog is the highest. The question is - why are there so few of them? If in a week not 29 people but 290 people came to my funnel from the blog, then my income would be 10 times more.

Maybe I have bad page subscriptions, and people don’t want to subscribe to my mailing list? Or maybe I have too few visitors to my blog, and there’s simply nowhere to get 290 subscribers a week? Yandex-Metrica will give us answers to these questions.

Analysis of indicators in Yandex-Metrica

Following the instructions below, I set up conversion tracking on my website. These are just the first four steps in my funnel:

1. The man came
2. The person went to the subscription page
3. The person subscribed

I open the corresponding section of Yandex Metrics and see the following picture of conversions for the week.

During the reporting period (week), 3,422 people came to my site. Of these, only 56 went to the SQ subscription page (1.64%). And 23 people (41.1%) signed up for the newsletter.

So I can see that my subscription page is working very well. 41.1% is a high figure. And yes, don’t be confused by the fact that one system shows me 26 subscribers, and the other only 23. This happens according to various reasons. The main thing is that the indicators do not differ greatly.

And here is our “hole” - a very small percentage of site visitors get to this very registration page. Only 1.64% of total visitors.

This is very little. This is where we need to work - do more persuasive appeals, make a brighter and more catchy banner, and all that jazz. And of course, we need to work on increasing site traffic. If I had 3422 visitors not per week, but per day, then this would greatly increase the final result.

Now you can see how end-to-end analytics can help you make decisions in practice. If I didn't have all these metrics, I might think that I have a bad email series and that's why people don't want to buy anything.

Or that my subscription page is bad - and I need to completely redo it, or even change it free product, which I offer for a subscription (and after that the entire concept of the project).

But analytics shows that you just need to make the banner brighter, and everything will be fine. This is what I will do right after I show you how to set up the same end-to-end analytics system yourself.

Setting up end-to-end analytics in 3 steps

As agreed, let's look at a more “traditional” version of Internet business and analytics.

Let's say you decide to create a small business in order to finally leave your hired job and become a free person. As a niche, you have chosen the sale of soft toys, sewn by skillful Chinese hands. A normal niche, no better or worse than others.

Have you completed a couple of trainings on “ successful success"and you know that first of all you need a specific goal to which you will go. And with this goal you set yourself an income of 300 thousand rubles per month. According to your calculations, this should be enough for the first time.

In order to earn 300 thousand net, you need to make 600 thousand turnover per month. Because half of the income will be eaten up by taxes, overhead costs and the cost of goods. And there is still the issue of advertising. Because it is completely unclear how much it will cost you.

But having estimated, we decide that 1.5 million turnover should definitely give us the desired 300 thousand rubles of net profit per month. We sell Chinese bears at a price of 2000 rubles per piece. Therefore, we need to sell 750 bears every month (25 bears per day).

These are our initial data, and now we need to set up the entire sales funnel, immediately “implanting” end-to-end analytics into it. Because later it will be much more difficult to do. And we start with the first step - choosing indicators for control.

Step #1 - selecting indicators for control

From the very beginning we need to determine control points, which you and I will track using end-to-end analytics. It is very important to avoid cluttering reports with numbers, but at the same time maintain an understanding of the big picture.

That is, there is no need to try to track absolutely all indicators. Otherwise, you risk getting confused in them and never understanding anything.

Our funnel will look something like this:

1. A person sees an ad (Direct, Google Display Network, VKontakte Target, banners, etc.);
2. A person follows our ad to a landing page;
3. A person places an order;
4. The person pays for the order.

Accordingly, we have only 3 main indicators that we need to track using metrics:

1. CTR of ads (the ratio of the number of ad impressions to the number of clicks);
2. Number of orders placed;
3. Number of paid orders.

And in the end we get two main indicators to which all the others lead:

1. How much money did one client cost us (according to advertising);
2. How much money did one client bring us (average purchase receipt).

The ratio of these two indicators gives us the most important indicator in end-to-end analytics.

The most important indicator

This indicator is called ROI (Return On Investment). If we spent 1000 rubles to attract one client, and received the same 1000 rubles in payment from him, then our ROI is 100%. For every ruble spent, we earned one ruble and got back 100% of the money spent.

It is precisely the ROI indicator that all your end-to-end analytics will come down to. All these 5-10-100 smaller indicators should lead precisely to the calculation of ROI. So that at the end of the reporting period you could say - “So, we have ROI 350% from advertising in Yandex-Direct, ROI 230% from advertising in Google Adwords, and ROI 50% from targeted advertising on VKontakte. Therefore, we are abandoning the target so as not to feed these parasites, and we are transferring the entire advertising budget to Direct as much as possible.”

Now, if you can say so, then you have correctly set up end-to-end analytics, and with its help you can track which advertising source gives you profit and which takes it away.

Okay, we have chosen the indicators to control. Let me remind you that this is:

1. Conversion to order
2. Conversion to payment

And from these indicators we ultimately calculate ROI. Let's now see where and what code needs to be inserted in order to properly control the funnel.

Step #2 — Technical setup of analytics

Setting up utm tags

First of all, we need to form the correct links for our future advertising sources. To track where our visitors came from, we need to insert special tags into the links. They are called UTM tags.

If you are interested, UTM stands for Urchin Tracking Module, and means “Urchin Tracking Module”. There was a company called Urchin Software that came up with these tags, and then it was absorbed by Google.

Currently utm tags are used as universal tool to track the sources of visitors to your sites. You can generate a link with utm tags, for example right here.

Just come up with names for your traffic sources and enter them in the appropriate fields. I usually only use three required fields - campaign source (utm_source), traffic type (utm_medium) and source name (utm_campaign).

• yandex&utm_medium= cpc&utm_campaign= yandex-direct(traffic source - Yandex, type - pay per click, name - Yandex Direct)
• http://yoursite.ru/?utm_source= google&utm_medium= cpc&utm_campaign= kms(traffic source - Google, traffic type - pay per click, name - kms).
• and so on

This will give you separate links to all your traffic sources. which you are going to configure. Then you can track them using Yandex Metrics (I’ll show you how), or any other end-to-end analytics system. But Yandex-Metrica is free, so we will consider it for now.

Setting up goals in Yandex-Metrica

Now we go to the office Yandex-Metrics. If your site is not yet connected to this system, be sure to connect it. To do this, you will simply need to indicate the site address and, using a simple verification, confirm that you really are its owner.

Now you need to paste this code on all the pages that your visitors will go through. The simplest option usually looks like this:

1. Your offer page (selling landing page)
2. "Thank you for placing your order" page
3. “Payment successful” page (“Thank you for your purchase”)

It is on these pages of yours that you need to insert the counter code received from Yandex. And after that, you can move on to setting goals. I prefer setting up compound goals. It seems clearer to me this way.

To do this, in the same “Settings” section, select the “Goals” item.

Then click “Add goal” and select the goal type - composite.

Now you need to define three steps that your visitors will go through. These are the three pages we talked about above.

Now you just need to save this funnel and start receiving data for analysis. After you run advertising from all sources, receive a certain number of orders and payments - you will be able to see exactly where your clients came from.

Step #3 - Tracking Funnel Metrics

Let me remind you that we specifically set utm tags in order to track where exactly the buyers came from, and not just visitors. In the end, we can see the number of clicks and visitors in the advertising system office itself.

In order to see where clients came from, we go to the Reports - Standard Reports - Sources - UTM Tags section

There you will see a list of all utm tags by which people came to you during the reporting period. It will look something like this.

As you can see, I had the most clicks on utm label from Yanex Direct, and some other little things from partners.

To see which source exactly the buyers came from, select the third step of our composite goal “Purchase” in the list of goals. For me this will be the “Subscription” goal.

In the screenshot below you can see that today my most conversions came from the “fixed” source (this is a banner on my website). The conversion was 41%, as we saw above. There were also conversions from partners, but not many.

This way you can see how many visitors came to you, and from which advertising source. Next, you will enter all these indicators into your CRM or simply into excel file, and there you will see our most important indicator - ROI.

And based on this indicator, you will make further decisions about which advertising source to invest in more money, and which one you don’t need to invest in at all (or you need to greatly improve it before investing).

Conclusion

End-to-end analytics is needed to understand where in your sales funnel there are “holes” through which money is leaking. Too many businesses fail because they make bad decisions because they don't see the whole situation.

They invest money in advertising that doesn't work. They're redesigning landing pages that were actually converting well. Or they even close projects that would generate excellent income, even after minimal changes to the funnel.

I hope that this instruction will help you gain “X-ray vision” and make only the right decisions.

Save the article to your favorites and share with friends. Don't forget to download my book. There I show you the most fast way from zero to the first million on the Internet (extract from personal experience in 10 years =)

See you soon!

Yours Dmitry Novoselov

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

What we will talk about:

Why do we 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 divided into some shares in different channels communications:

$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 at the 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/her data 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 a 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 for 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 e-commerce block are configured correctly) 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 such a 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 the conversion into actual payment is quite high there (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 in 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. And if so, within Google Analytics it is quite difficult to make decisions about the effectiveness of advertising channels. 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 explanation if he saves 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 a variety of tools to communicate with businesses, and We must take each of these tools into account within CRM. But at the same time, we must also understand within CRM that this user who used the online chat came from a specific advertising campaign, for example, Google Adwords for some key request. 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 callbackhunter, which gives us a certain amount 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 there is 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 something important to us buttons 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 made by this specific user 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. some kind of customization is 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 end-to-end analytics systems. 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 such a report, 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 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 other than check out, but also for any other way 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 identifier. 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. 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. many 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 postal 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. From time to time, problems arise with transmitting data over this protocol if we use POST requests; often there are 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 reduce this data to one form or do not take it into account at all when implementing the entire scheme, then Google data Our analytics 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.

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End-to-end analytics is a tool that allows you to evaluate the effectiveness of your advertising. It gives a clear understanding of the financial result each ruble spent brings. How to implement end-to-end analytics, configure and receive from it maximum benefit, – we will consider in this material.

Ways to build end-to-end analytics

Before implementing end-to-end analytics, you need to determine the main goal: what exactly do you want to track and what metrics to calculate. Depending on the tools used, three methods can be distinguished.

Whatever method you choose, end-to-end analytics is impossible without combining information from different sources. Advertising data is provided by advertising systems: Yandex.Direct and Google Adwords. Sales information is available in CRM. Call statistics are collected using dynamic call tracking.

After combining all this data, a general picture emerges about the effectiveness of advertising. Let's take a closer look at how end-to-end analytics is built using the CoMagic service.

Combining data in CoMagic

The CoMagic service collects all marketing and sales data in your personal account. As a result, end-to-end analytics reports become available, allowing you to understand which advertising channels are effective in terms of the number of calls, cost of call, and return on investment (ROI).

Where does CoMagic get its data?

IN General settings site, in the Integration with services tab, select Advertising systems and enter the account identifier to which the advertised site is linked.

If you have a phone number on your website and customers often call you, your end-to-end analytics will be incomplete without call data. To see all calls from site visitors, we connect call tracking.

When dynamic call tracking is enabled, each visitor is shown a unique number. He is assigned to him on certain time, which allows you to analyze the behavior of this visitor: starting from key query, according to which he came, before the transaction was completed.

Suppose there is a keyword “buy a car”, you see how many visits it brought, you see how much a call for this word cost, but was it targeted? Did this keyword lead to a deal or not? What is its sales conversion rate? If they not only called using this keyword, but also made a purchase, then you can accurately evaluate - yes, this word works.

In order to see not only visits and requests to the company, but also the transactions themselves, sales data is needed. Then you will be able to analyze not only “how many visits this keyword brought me,” but also specifically “how much money I earned from it.”

1. Sales - pulling from CRM

The next step is to combine marketing data with sales data - we integrate your CRM system and CoMagic.

Most integrations are done in just a few clicks, allowing you to do them yourself. We have developed integrations with the most common CRM systems. But CoMagic is able to collect data from any CRM, even self-written. In this case, integration is performed using the API.

Any integration is free and carries only advantages - additional data for your analytics.

After CRM connections The List of Transactions report appears in your personal account.

This report can be configured differently, depending on what exactly you want to track. What you can see here: date, type of request, from which advertising campaign, which keyword worked, transaction amount, visitor ID (using it you can go into the visitor’s card and see the entire history of interaction with him), etc.

You can now add end-to-end analytics to the report additional columns– Financial data. This financial data is the very return on advertising! How many sales were there, what was the conversion, average check, total revenue, ROI. You need to click the Customize Columns button and select necessary indicators.

You can select all columns or make your own customization end-to-end analytics. We recommend paying attention to indicators such as expenses, visits, requests, total sales, revenue, ROI, average bill. The obtained data can be downloaded in the form of a ready-made report in PDF format, Excel, CSV or Google Sheets.

But if you are a convinced visual person, speed and ease of perception are important to you, or you need to show your boss beautiful and understandable graphs, and not a pile of numbers, use dashboards.

This is a kind of showcase of your key indicators. Customize your graphs by setting thresholds and always have all the metrics you need at your fingertips in a simple and understandable way.

Dashboards work in Real Time mode, which will allow you to always be aware: advertising is working perfectly, increasing traffic and calls, or the lead plan is going to hell and urgent action needs to be taken.

The resulting visual report can be downloaded in PDF or PNG format. Or set up sending dashboards by email.

Usage

So, we have set up end-to-end analytics and connected dashboards for convenient information analysis. What's next?

End-to-end analytics only works and brings real value when you not only observe, but also make business decisions based on it. After 1-2 months of advertising and tracking all indicators, you can adequately analyze what works in your advertising and what doesn’t.

For example, you have a set of keywords. From month to month, only 2 or 3 of them bring real deals. For the rest, there are no requests or no transactions are made. Increase bids on ads for working keywords, thereby increasing conversion. Having all the necessary data, you can fully optimize your advertising and thereby achieve greater effectiveness.

Analyze transitions across all advertising channels, calculate ROI, try new ways to attract traffic to the site. End-to-end analytics makes it possible to see all your advertising at a glance: what works and what doesn’t. Use this vision to make your advertising even more effective and your business successful.

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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 create a transparent KPI system for your marketing department or advertising contractor, and plan advertising campaigns in the most effective advertising channels.

2 What data is shown in the report?

• number of impressions of 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 channels promotion. 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. Key words: most effective keywords, in contextual advertising that bring you sales and appeals.

5 How to start using the report?

To open a report on the website " Personal account» 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 quantity(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 a convenient function for creating your own report forms, the structure of which you define. 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 "Create 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.