Luka Androjna (2019) Optimization of conversions in programatic advertising. EngD thesis.
Abstract
Publishers on the web monetize their businesses by running advertisment on their websites. Ads are targeted at their readers and paid for by advertisers. Advertisers generally show ads to either improve their brand perception or to get users to make some specific action. They want to get engaging users onto their product’s landing page and take actions that generate value for the advertiser, for example registering a new account, subscribing to a newsletter, making a purchase etc. Those actions are called conversions. Optimizing buying of advertising to induce clicks and conversions is the business of programatic advertising. We will look at different approaches for lowering the CPAs and raising conversion rates. We approach the problem with the use of a whitelist containing combinations of exchanges, publisher websites and tag ids, and a blacklist of useragents. We conducted an A/B test, which was running in an online production environment and affected bidding in real time for Zemanta d.o.o., that showed buying traffic on premium ad space gives us better conversion rates and lower prices per acquisition. We also noticed that prices per click dropped even though the average price per impression went up.
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