Device (Mobile – Desktop and Tablet): Since we found a significant disparity between the conversion rates on different platforms, the Boost team started by bifurcating mobile and desktop into discrete ad campaigns. The analysis that showed significant behavioral differences between these two sets of users made this decision fairly straightforward.
User Location: The objectives, intentions, and behavior of users varies by location. In Milliyet Emlak’s case, this is partly due to non-uniform brand recognition and partly due to location-specific services/listings on offer. Keeping this in mind, the Boost team customized and split ad campaigns by city.
User Search Query: All search terms cannot be treated equally and our analysis showed vast differences in conversion, depending on the search terms used by visitors. Since generic search queries had much lower conversion rates compared to more specific ones, we split campaigns by search query as well.
In order to use the technical language in the best way, we had to improve the incomplete parts of the infrastructure. From page speed optimization to the content creation side, we took great pride in all the improvements we have made.