End-to-end analytics: what it is and how it connects advertising to sales

Why end-to-end analytics matters

End-to-end analytics doesn’t show how many clicks or submissions a channel got — it shows how many of them ended in a deal.

What it gives you:

• which channel or campaign led to paid deals, not just to site visits;
• which submissions didn’t turn into a deal, and on which channel there are more of those;
• where there’s a gap between leads and sales in your advertising or on your site — a reason to take a closer look at that channel;
• how comparable different advertising channels really are by final result, not just by the number of visits.

This matters most if a business runs several advertising channels at once. Without combining deal data, each channel is visible only through its own clicks and submissions, and comparing them directly is hard.

What it doesn’t give you:

• a ready-made ROI, ROMI, or cost-per-lead calculation — those metrics are calculated from the collected data separately;
• a replacement for advertising or SEO itself: the system shows data, it doesn’t change your promotion channels;
• a guarantee of higher sales — the result depends on what you do with the data you get.

In other words, end-to-end analytics answers the question of what from your ads and site actually turns into deals, not the question of how much traffic and inquiries you got on their own.

What the path from click to deal consists of

The word «end-to-end» means exactly this: data passes through several systems, and none of them on its own shows the whole picture. The path from click to deal is a sequence in which customer data moves through several systems:

1. A user clicks an ad with a UTM tag — a parameter in the link that lets analytics identify the traffic source and channel (how to tag ad traffic with UTM parameters). Without a tag, the system sees a visit but doesn’t know which campaign it came from.
2. The web analytics counter on the site logs the visit and automatically assigns the visitor an identifier, such as a ClientID. This identifier is needed later to link the visit to a submission and a deal.
3. The visitor submits a form on the site or calls. At this step, the customer’s contact details — phone or email — are added to the data.
4. The submission lands in the CRM, where a manager moves it toward a deal: changing its status, recording the amount and the outcome.
5. Customer and deal data from the CRM is merged with visit and ad data by a shared identifier — phone, email, or ClientID. This is the key step: without it, ad data and sales data stay two separate tables.
6. Based on the merged data, a report is built: which channel and campaign led to the deal, not just to the visit or the submission.

If a link in this chain is missing — for example, call tracking isn’t set up — the report breaks off at that step, and the channel beyond it is counted as unknown.

What data end-to-end analytics combines

To bring the customer path together in one report, you need to reconcile data from at least four sources:

Data source	What it provides	Example
Advertising (UTM tags, campaign spend)	the source and channel of a visit, acquisition cost	a visit from a Direct ad tagged with a specific campaign
Web analytics (site counter)	visits, a visitor identifier, what counts as a conversion on a site	a form submission logged as a target action
Call tracking	calls linked back to the traffic source	a call to a number shown only to visitors who came from advertising
CRM	deal status, amount, responsible manager	a submission turned into a paid order

On its own, each row of this table is an ordinary report that already exists in its own system: the ad account shows spend, the counter shows visits, the CRM shows deals. End-to-end analytics brings these four reports together in one, linked by a shared customer identifier.

What systems and services are used for end-to-end analytics

In practice, several classes of services are used for end-to-end analytics:

• web analytics systems — count visits, events, and traffic sources on the site; this is the base layer of data that the other systems build on;
• call tracking services — identify which channel a call came from by showing different phone numbers for different traffic sources;
• CRM systems — store deal data, statuses, and amounts; without them, you see submissions but not their outcome;
• dedicated end-to-end analytics services — combine data from the systems above into one report and automate part of the work you’d otherwise do by hand.

Different combinations of these systems suit different tasks and data volumes. A small business may need only web analytics and a CRM; a more complex sales process with several channels and calls may need all four classes at once. Choosing a specific service is a separate decision that depends on what the company already uses and how its sales process is structured.

What’s needed to set up end-to-end analytics

For end-to-end analytics to work, several conditions need to be met — regardless of which service you end up using:

• correct UTM tags on every advertising link, with no exceptions;
• a single web analytics counter installed on every page of the site;
• deal data passed from the CRM into the analytics system;
• call tracking, if some submissions come in by phone;
• a shared user identifier — phone, email, or ClientID — that links data from the different systems.

If even one of these conditions isn’t met, gaps appear in the report. For example, without call tracking, calls stay without a traffic source, and without deal statuses passed from the CRM, you see submissions but not which of them were actually paid.

These conditions can be rolled out gradually: start with UTM tags and a single web analytics counter, and add call tracking and CRM data later, once it’s clear which link is missing from your reports.

Personal data and consent when collecting data

The customer’s email and phone number, which land in the CRM and the analytics system when data is merged, are personal data. Their processing is governed by Federal Law No. 152-FZ, «On Personal Data.»

The law allows processing personal data only in the cases listed in Part 1 of Article 6, and the first of those is the data subject’s consent to the processing of their personal data. The law’s definition of «processing of personal data» is broad and covers, among other things, collecting, storing, and transferring data (Item 3 of Article 3) — meaning that passing customer data between a site, a CRM, and an analytics service falls under this definition, even when it happens automatically. If a company builds this kind of integration, it’s worth making sure consent to process personal data has been obtained and documented correctly before merging customer data across services.

Common difficulties when building end-to-end analytics

In practice, building end-to-end analytics tends to run into similar difficulties:

• different systems use different user identifiers — for example, a phone number in the CRM and a ClientID in web analytics — and the data doesn’t always link automatically;
• calls without call tracking lose their traffic source and drop out of the report even if the deal closed;
• managers enter data into the CRM by hand, and some deals end up there with errors, with a delay, or not at all;
• the same customer sometimes gets several records in the CRM — for example, by reaching out from different phone numbers or through different channels — and their data gets duplicated.

None of these difficulties is critical on its own, but together they reduce the report’s accuracy: some deals stay unlinked to the channel that actually brought them in.

How end-to-end analytics helps you evaluate channels

End-to-end analytics itself doesn’t calculate ROI, ROMI, or cost per lead — it supplies the data those calculations need: which channel and campaign led to a deal. That distinction matters: an end-to-end analytics report is input for calculating metrics, not a ready-made answer to which channel is more worthwhile.

The difference between these metrics and how they’re calculated is covered in separate articles: how ROI is calculated from end-to-end analytics data, how ROMI differs from ROI, how cost per lead is calculated.

Frequently asked questions

What is end-to-end analytics, in simple terms?

It’s a system that gathers data about advertising, your site, and deals in a CRM into one report, showing which channel and campaign ultimately led to a sale, not just a click or a submission. Without it, this data stays in three separate systems and has to be reconciled by hand.

Does a small business with one advertising channel need end-to-end analytics?

It depends on how many channels there are and how submissions are processed. If there’s only one channel, submissions are few, and it’s easy to match them to deals by hand, setting up a separate system to combine data may not be necessary. If there are several channels, many submissions, or more than one person processing them, doing this without a system is noticeably harder.

Can you set up end-to-end analytics without a CRM?

Partially. Without deal data from the CRM, you can see how many submissions and site visits came from each channel, but not which of those submissions actually ended in a paid sale and which didn’t.

How is end-to-end analytics connected to call tracking?

If some submissions come in by phone, without call tracking those calls don’t link back to a traffic source and drop out of the channel report.

Do you need a customer’s consent to pass their data between analytics services?

Yes, if the data being passed includes the customer’s email or phone number: that’s personal data, and processing it requires a lawful basis — more on this in the «Personal data and consent» section above.