Optimizing Performance-Based Internet Advertisement Campaigns

نویسندگان

  • Radha V. Mookerjee
  • Subodha Kumar
  • Vijay S. Mookerjee
چکیده

This study provides an approach to manage an on-going Internet ad campaign that substantially improves the number of clicks and the revenue earned from clicks. The problem we study is faced by an Internet advertising firm (Chitika) that operates in the Boston area. Chitika contracts with publishers to place relevant advertisements (ads) over a specified period on publisher websites. Ad revenue accrues to the firm and the publisher only if a visitor clicks on an ad (i.e., we are considering the cost per click model in this study). This might imply that all visitors to the publisher’s website be shown ads. However, this is not the case if the publisher imposes a click-through-rate constraint on the advertising firm. This performance constraint captures the publisher’s desire to limit ad clutter on the website and hold the advertising firm responsible for the publisher’s opportunity cost of showing an ad that did not result in a click. We develop a predictive model of a visitor clicking on a given ad. Using this prediction of the probability of a click, we develop a decision model that uses a threshold to decide whether or not to show an ad to the visitor. The decision model’s objective is to maximize the advertising firm’s revenue subject to a click-through-rate constraint. A key contribution of this paper is to characterize the structure of the optimal solution. We study and contrast two competing solutions: (1) a static solution, and (2) a rolling-horizon solution that re-solves the problem at certain points in the planning horizon. The static solution is shown to be optimal when accurate information on the input parameters to the problem is known. However, when the parameters to the model can only be estimated with some error, the rolling-horizon solution can perform better than the static solution. When using the rollinghorizon solution, it becomes important to choose the appropriate re-solving frequency. The implemented models operate in real time in Chitika’s advertising network. Implementation challenges and the business impact of our solution are discussed. In order to present a head-to-head comparison of our implemented approach with the past practice at Chitika, we implemented our solution in parallel to the past practice.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimizing direct response in Internet display advertising

Internet display advertising has grown into a multi-billion dollar a year global industry and direct response campaigns account for about three-quarters of all Internet display advertising. In such campaigns, advertisers reach out to a target audience via some form of a visual advertisement (hereinafter also called ‘‘ad’’) to maximize short-term sales revenue. In this study, we formulate an adv...

متن کامل

Mediacampaign - A multimodal semantic analysis system for advertisement campaign detection

MediaCampaign's scope is on discovering and inter-relating advertisements and campaigns, i.e. to relate advertisements semantically belonging together, across different countries and different media. The project’s main goal is to automate to a large degree the detection and tracking of advertisement campaigns on television, Internet and in the press. For this purpose we introduce a first protot...

متن کامل

Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies.

Online systems promise to improve advertisement targeting via the massive and detailed data available. However, there often is too few data on exactly the outcome of interest, such as purchases, for accurate campaign evaluation and optimization (due to low conversion rates, cold start periods, lack of instrumentation of offline purchases, and long purchase cycles). This paper presents a detaile...

متن کامل

Adaptive Targeting in Online Advertisement: Models Based on Relative Influence of Factors

We consider the problem of adaptive targeting for real-time bidding for internet advertisement. This problem involves making fast decisions on whether to show a given ad to a particular user. For demand partners, these decisions are based on information extracted from big data sets containing records of previous impressions, clicks and subsequent purchases. We discuss several criteria which all...

متن کامل

Does deceptive advertising reduce political participation

We examine the effect of deceptive advertising on voting decisions in elections. We model twocandidate elections in which 1) voters are uncertain about candidates' attributes; and 2) candidates can inform voters of their attributes by sending advertisements. We compare political campaigns with truthful advertising to campaigns in which there is a small chance of deceptive advertising. Our theor...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Operations Research

دوره 65  شماره 

صفحات  -

تاریخ انتشار 2017