As a tool for solving the above-mentioned tasks, you can use the FAIR BI service. This is one of the most powerful ETL systems in the world.
FAIR BI allows you to:
- Collect and store data quickly, efficiently and belgium whatsapp data securely, and process it quickly. With FAIR BI, you don’t have to worry about data quality. In the marketing cycle, the service itself finds the necessary information, contacts its source and selects a storage base.
- Automate reporting. The service allows you to automatically generate regular reports on marketing efficiency, product efficiency, competitors, and so on.
- Automate status control: the service monitors how the advertising campaign is working. In the marketing cycle, analyzes its effectiveness and identifies problems, which it immediately reports.
- Search and test hypotheses. The DSS system inside the service independently processes data, finds insights, formulates hypotheses and predicts their results.
Case: How to Make Quality Advertising and Lose on It
To understand how errors at each stage can affect the effectiveness of an advertising campaign, let’s look at one of the cases that we encountered in our work.
The client is a large company with a monthly smart search: blendee launches the new version of smart search advertising budget in Yandex Direct of 4.8 million rubles. The company is quite advanced in terms of analytics: there is cohort analysis, client clustering, and end-to-end analytics is set up. However, all advertising campaigns are analyzed independently of each other, which is partly a mistake.
The thing is that it is better not to consider advertising in a vacuum, because all campaigns influence each other in one way or another. For example, by launching an advertising campaign for branded queries in Yandex search. In the marketing cycle, you take traffic and leads from organic branded traffic. By launching advertising campaigns for queries for which you are at the top of search engines, you take leads from branded search traffic.
So the client’s situation was that the company did not count how many additional leads and sales the advertising brought. Only the total number was counted and the results before and after the launch of the campaign were not taken into account. Therefore, the client, despite the fact that he launched high-quality advertising, had no idea how it worked and how effective it was.
In order to correct the situation, it was necessary to calculate the incremental effect, or in other words, the supplementary effect of advertising campaigns.
This happened in the following way
The business had clustering, that is, users phone number united states of america were divid into clusters, and advertising campaigns into categories. We conducted an analysis and saw that brand advertising in St. Petersburg and Moscow works better.
Then we looked at the effect of advertising campaigns together with conversions and calculated the incremental effect, i.e. the squeezed value from each advertisement, using this data. It turned out that the brand campaign in Moscow gives a negative ROMI. Most people who came through this advertisement were ready to buy the product anyway.
Thus, calculating the incremental effect helped find an answer to the question of whether the business was making money on the ads it launched. As a result, campaigns that were producing good results cannibalized other campaigns. In the marketing cycle, as well as other acquisition channels. We automated the incremental analysis, which allowed us to increase additional monthly income from 1.7 million rubles to 3.6 million rubles.
