  Real-Time Bidding is nowadays one of the most promising systems in the online
advertising ecosystem. In the presented study, the performance of RTB campaigns
is improved by optimising the parameters of the users' profiles and the
publishers' websites. Most studies about optimising RTB campaigns are focused
on the bidding strategy. In contrast, the objective of our research consists of
optimising RTB campaigns by finding out configurations that maximise both the
number of impressions and their average profitability. The experiments
demonstrate that, when the number of required visits by advertisers is low, it
is easy to find configurations with high average profitability, but as the
required number of visits increases, the average profitability tends to go
down. Additionally, configuration optimisation has been combined with other
interesting strategies to increase, even more, the campaigns' profitability.
Along with parameter configuration the study considers the following
complementary strategies to increase profitability: i) selecting multiple
configurations with a small number of visits instead of a unique configuration
with a large number, ii) discarding visits according to the thresholds of cost
and profitability, iii) analysing a reduced space of the dataset and
extrapolating the solution, and iv) increasing the search space by including
solutions below the required number of visits. The developed campaign
optimisation methodology could be offered by RTB platforms to advertisers to
make their campaigns more profitable.
