We explore the value of Data Science within RTB.
RTB and the digital advertising space has always been at the forefront of Data Science with larger industries such as finance and healthcare only recently investing in building Data Science teams. Since 2004, when Right Media released the first ad exchange, RTB has continuously gained ground. Google, Adex, Rubicon, Pubmatic and FBX are just a few of a broad range of platforms which have revolutionised the digital market. The reasons for this trend is obvious; ad impressions can be bought individually. The period of acquiring bulk impressions, unsure of their single value, is over.
To the advantage of sellers and buyers, the price/bid can be adjusted for every single impression to match market conditions. For the buyers it allows flexible planning of their marketing budget. The bidder/buyer also benefits from the instant feedback received in real-time when the user clicks on a banner.
Who is the customer? How old is he/she? Where is he/she from? These are questions the Ad exchange platform can answer. Analysing these data sets leads to information which can be used to segment customer groups, which ultimately benefits the optimisation of marketing campaigns.
However, the market isn’t just growing, it’s becoming a place for research, discussion and meetings. On the 29th of September, Singapore will host an Ad:Tech Data Summit which will allow digital marketers and advertisers to discuss and examine how they can leverage data to create actionable insights and improve campaigns.
A study from Magna Global about the future development of Ad Tech explains that the value of media inventory traded with programmatic methods will increase by 27% per year. As value increases companies will be willing to spend more on Ad tech and it is expected that advertising budgets will expand this year to approximately 48% (2014: 42%).
These figures show that an increasing number of companies in all industries are realising the importance of Ad Tech, especially RTB, and how it can improve their market activities. Thanks to Data Science huge data sets can not only be collected and processed but also analysed and predicted in great detail. The predictions are based on the information gained through applying analysis which supports the decision making process when planning marketing strategies or budgets.
This leads us back to the question that the Ad exchange platform answers: Who is the customer?
Information about salary, age, number of household members, interests etc. can be effectively used by data science techniques that can clarify the correlation between these details. In its simplest form the Data Science process entails collecting much data, drawing upon connections and explaining users’ behaviour to target them more precisely. If the information is connected to each other a structure is created that shows and explains users’ behaviour and can therefore be used to define retargeting.
The technology and data driven environment that we live in today is constantly shifting and changing. So much so that some organisations (including the e-commerce sector) can no longer make big decisions without real-time information creating meaningful customer experiences. The significance of data science within this market is truly invaluable. The Ad Tech market is exciting and a fast-moving environment that punishes failure harshly, but rewards true market innovation.
Sarah Schnepper | Data Science Consultant | Germany
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