That is, multi-channeling was already implemented

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As practice has shown, already in 2004, PHP and Javascript programmers, together with a business owner who understood why he needed analytics, were able to write a kind of micro Google Analytics for his website. Perhaps, the reporting was not yet at the modern level - a regular Excel table, but in this table, users who visited the site were marked, it was possible to see from which advertising channel these users come, and how often.

There was also a moment implemented when a user south korea consumer email list downloaded some software product, the software product itself had a system for tracking the fact that the visitor who came to the resource from a site or some advertising channel then opened a paid account on this resource. That is, we are talking about a full-fledged analytics system that uploads all the data on final sales, by channels, to Excel and works great to this day.

This example proves the fact that if you know what you want to measure, clearly know what you want to get from Internet marketing, no analytics systems should impose their regime on you. All the new web analytics that are appearing now were known back in the period from 2004 to 2006, no unique innovations or standards have been introduced until now.

There are also plenty of negative examples from practice, i.e. how not to do web analytics. For example, “payment for increasing conversion” still exists.

The next example is unscrupulous SEO contractors.

For 1 year, the company paid for the SEO company's services to promote the site. Every month, the SEO company provided reports on positions that were consistently in the TOP-10. It turned out that, based on the results for the year, the customer company was operating at a -13% loss.
It turned out that for the entire year, the site's income fell by 13%, conversion by 30%, the number of purchases by 15%, and the conversion was only 1.36% (with a normal conversion in the subject matter of about 4%).

In principle, simple analytics in Google allows us to understand how the trend has changed over the year, compared to the previous one, how the indicators have fallen. As a result, we managed to figure out which search queries were unprofitable. The search marketing strategy was also radically revised: an adjustment was made, and we managed to “make friends” with search engine promotion, select a normal core, distribute it correctly across the site and measure its effectiveness in fact.