The Role of Analytics in Contextual Advertising. Expert Opinions and Cases

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Content
Reduce the share of advertising costs and double the revenue of the online store
Case
See the result in real time, not later
Understand at what stage of the funnel you are losing customers
Case
The father of American management philosophy, Peter telegram codes list Drucker, said: "You can only manage what you can measure." How true is this for contextual advertising? We asked experts what role analytics plays in contextual advertising, what and with what tools they track, and what results it brings.

Reduce the share of advertising costs and double the revenue of the online store

Igor Chikarov, Director of Production, Digital Geeks

When a client contacts a digital agency for contextual advertising, they don’t just want to “buy out an ad space in Google or Yandex search results.” They want to make a profit. They want to see the return on their investment in advertising, and not deferred. The key indicators for assessing the results of such placement are ROMI and DRR.

As we know, to calculate these indicators, it is not enough to know the number of clicks received and even leads from advertising activity - you need to know the financial result. But how can a business understand what share of revenue/profit was received precisely due to investments in contextual advertising? At this stage, end-to-end analytics comes to the rescue .


How the CoMagic end-to-end analytics system works
For the client, this is an independent system for monitoring the contractor's performance, and for the advertising agency, it is a powerful tool for analyzing and optimizing advertising campaigns. After all, by evaluating the effectiveness of an advertising campaign only by the indicators registered by the web analytics system, specialists see only the tip of the iceberg. Let's consider a real case from the life of our agency, in which the implementation of end-to-end analytics became the cornerstone for the breakthrough results of the client's business.

Case
Our client, one of the largest online stores of sleep products in Russia, has always been very sensitive to contextual advertising. At least because this channel consistently generated more than half of the site's traffic and about 2/3 of the total number of requests to the company. I would like to note separately that the sleep products segment is somewhat different from typical e-commerce, because most customers require additional consultation before purchasing. They do not understand how to evaluate the quality of the materials from which a conditional mattress is made, and are also afraid of making a mistake with the rigidity and other important orthopedic functions of the products offered. Therefore, orders through the basket on the site account for less than half of the total number of orders. The rest are placed during a consultation with a specialist by phone or through an online consultant.

Indicators such as the average purchase receipt, call-to-sale conversion, and percentage of cancelled orders were unknown to us across advertising channels. As a result, even the configured advanced e-commerce in Google Analytics and Yandex.Metrica did not give advertising specialists a full picture of the effectiveness of certain advertising formats. And it did not give us the opportunity to justify to the client the effectiveness of placement in the Yandex and Google advertising networks and the need to scale this direction.

The implementation of end-to-end analytics based on the K50 toolkit allowed us to obtain statistics in real time for each advertisement, right down to the revenue received. The main conclusion we received from the analysis was a higher average purchase receipt for orders placed after a telephone consultation with a store manager, and a lower percentage of cancellations. As a result, the actual value of the DRR from placements in advertising networks turned out to be significantly lower than expected. This allowed us to justify to the client a strategy of a more active presence in advertising networks.

As a result, after implementing end-to-end analytics for one year, we managed to double the store's revenue without significantly increasing the advertising budget. The client is happy - win-win!