In recent years, we have received a lot of information from different search engines, and browsed related advertisements that showed up automatically as well. What we can do is to study the behavior of advertisers and the methods about posting advertisements. As Yahoo! has provided some datasets for studying, we decided to focus on the advertisers’ bidding price on specific time and frequency.
project motivation
In this project, we would find out some relationship between behavior of advertisers and bidding price, to assume the rules about price trend among different time. Of course, we would design special models for calculating and use Tableau as major tools to access the data we need. With the tools application and data collections,
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Yahoo! Search Marketing is using real-time bidding (RTB) technique, with which advertising buyers bid on main slots along with Yahoo!’s search results after the user put in certain keywords for search. RTB is different from traditaional bidding methods, such as CPM (cost per mille) and CPC (cost per click). To put it simply, RTB allows advertising buyers to bid for target customers, which are selected through analyzing users’ browsing history and possible interests, and to place specific advertisement for each user. In this way, the presented advertisement becomes more relevant and precise for target customers.
According to eMarketer, a market research company, advertising buyers in United States will spend more than nine billion dollars on RTB in the near future. They also predicted that in 2017 the RTB cost will constitute 29% of total advertisement cost.
The process of RTB:
Use Yahoo! like a example
Step 1, Yahoo! obtains users’ information through the users’ visit history.
Step 2, Yahoo! sends the information to the Ad exchange. The information contains URL, Ad location, user Cookie ID, etc.
Step3, Ad Exchange requests a real time bidding, and sends the bidding request to several DSP servers.
Step4, DSP server sends the data to the bidding engine after it has received the request.
Step 5, Advertiser’s User Data Storage analyses the User ID that send from bidding
for search engines with High probability of booking and Low CPC; (2) for search engines
Advertisement is conducted on TV, radio, website, poster site, and all kinds of media that
d) The information is acquired on the data bus and send it to TDO. (Alghafli, Jones, and Martin. 2012).
4. Exchange state – In this state DBD (Database Descriptor) packets are exchanged. DBDs contain LSAs (Link State Advertisement) headers. The Routers will use this information to see what LSAs need to be exchanged.
Moving right along, I was able to fine many things I could apply to real life, such as rate bases and closing dates. The circulation level on which advertising rates are based are called rate bases. However, depending on how the interested the readers are, the price of the advertisements may vary. I can use rate bases in the real world because in order to know when and where to advertise is important. This will be important in the real world because it helps to track whether your advertisements are succeeding or if your placement is
Source 1: Kovbasyuk, Sergei, and Marco Pagano. “Advertising Arbitrage.” SSRN, 2 May 2014. Eelsevier, papers.ssrn.com/sol3/papers.cfm?abstract_id=2431270.
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Step-7- RFP finalized: the RFP with a 52 line item matrix to overview a 200 total page document with over a thousand requirements was developed to guide the software selection, lists of standard reports, and instructions to vendors for the bidding process was included. 50 hard copies were produced, and the RFP was also copied in electronic format.
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