Tire and wheel shop TireStock

case

Task

What we did

Tire and wheel shop TireStock applied to us to set up contextual advertising for tires as they lacked requests from Avito and Yandex.Market.

From the very beginning we decided to compile the semantic core manually in order to prevent non-targeted traffic, which could appear if we had approached automatic setting based on the feed. That is why we requested the client to differentiate the tires according to their model, size, season, radius or brand.

We compiled the semantic nucleus, divided up the words into groups. It turned out to be more than 106 000 key words in total. Direct search advertising worked in the most effective way, though dynamic smart banners did well, too.

According to our experience, the display in the Yandex advertising network (YAN) on mobile devices should be turned off, because users often see ads in apps or on non-targeted sites like authorizations for free wi-fi. Therefore, in the beginning we set downward adjustments, which was 100% for remarketing and look-alike campaigns (a similar audience to those who left the application).

Nevertheless, the display on mobile devices was not completely turned off. They resulted in even more applications, although they were more expensive, but still within the planned indicators.

An ad with the lowest cost of conversions

Result

It was an understandable landing page and detailed semantic core, which resulted in the achievement of such excellent indicators. Of course, we also reduced the number of keywords and platforms, analyzed social demographics, but the greater weight of success was in the elaboration of keywords.