Online Advertising

This chapter explores what makes online advertising different from traditional advertising channels. We argue that online advertising differs from traditional advertising channels in two important ways: measurability and targetability. Measurability is higher because the digital nature of online advertising means that responses to ads can be tracked relatively easily. Targetability is higher because data can be automatically tracked at an individual level, and it is relatively easy to show different people different ads. We discuss recent advances in search advertising, display advertising, and social media advertising and explore the key issues that arise for firms and consumers from measurability and targetability. We then explore possible public policy consequences, with an in depth discussion of the implications for consumer privacy

Web-analytiikan käyttö yritykseltä-yritykselle -verkkosivuston suorituskyvyn mittaamiseen, arviointiin ja parantamiseen

Companies are struggling with decisions about web sites. Web analytics is a study about visitor online behaviour and one of its key benefits is that decisions can be based on facts instead of opinions. This thesis was done for Company that was interested in facilitating web analytics to better guide decision-making. The thesis can be divided into three parts: the first is about measuring web site usage, the second is about estimating the monetary value of web site usage and the third is about improving the business performance of the web site. We used A/B testing methodology to improve the web site performance. A web site valuation framework was developed for this thesis. The framework contains two subcategories: revenue generating usage of the web site and cost saving usage of the web site. The framework is based on measuring the amount of important actions that visitors complete on the web site and on estimating the monetary value of those actions. A product purchase or a brochure download are examples of important actions. The framework provides multiple formulas to estimate the monetary value of those actions. We found out that web analytics is a useful and powerful tool for web sites and basic web analytics is relatively easy to implement. However, to fully leverage the potential of web analytics site-specific customizations and manual labour from analyst is needed. We also found out that business-to-business web sites can benefit from A/B testing. We were able to improve the effectiveness of the "request a quote" form. One of the findings was that it is possible to estimate the monetary value of business-to-business web site even though the web site does not have e-commerce capabilities. Traffic observations also revealed some interesting insights: visitor behaviour is improved when they are browsing the web site in their local language; visitor behaviour is improved when the web site is fast and providing responsive design to mobile visitors is important as the usage of mobile devices to browse the web is increasing rapidly.Yritykset kamppailevat päätösten kanssa, jotka koskevat verkkosivuja. Web analytiikka on oppi vierailijoiden online-käyttäytymisestä ja yksi sen tärkeimmistä hyödyistä on se, että päätökset voi perustaa faktoihin mielipiteiden sijaan. Tämä diplomityö on tehty yritykselle, joka on kiinnostunut hyödyntämään webanalytiikkaa päätöksenteossa. Työ voidaan jakaa kolmeen osaan: ensimmäinen osa kertoo yrityksen verkkosivuston käytön mittaamisesta, toinen osa arvioi verkkosivun käytön rahallista arvoa ja kolmas osa kertoo web-analytiikan käytöstä verkkosivuston liiketoiminnan parantamiseen. Tässä työssä käytettiin A/B-testausmetodologiaa verkkosivuston parantamiseen. Verkkosivuston arviointimalli kehitettiin tätä työtä varten. Malli koostuu kahdesta osasta: liikevaihtoa kasvattava osa verkkosivuston käytöstä ja kuluja säästävä osa verkkosivuston käytöstä. Malli perustuu siihen, että mitataan, kuinka paljon vierailijat tekevät tärkeitä toimintoja verkkosivuilla ja siihen, että arvioidaan naiden toimintojen rahallista arvoa. Tuotteen ostaminen tai esitteen lataaminen ovat esimerkkejä tärkeistä toiminnoista. Työn aikana selvisi, että web-analytiikka on hyödyllinen ja tehokas työkalu verkkosivuille ja web-analytiikan käyttöönotto on suhteellisen helppoa. Webanalytiikan täysi hyödyntäminen vaatii kuitenkin sivukohtaisia kustomointeja ja manuaalista työtä analyytikolta. Tulokset paljastavat, että A/B-testaus on hyvä tapa suorittaa kokeita verkkosivustoilla ja yritykseltä-yritykselle -verkkosivustot voivat hyötyä siitä. Löysimme myös, että on mahdollista mitata yritykseltä-yritykselle -verkkosivuston rahallista arvoa, vaikka verkkosivustolla ei olisi verkkokauppaa. Liikennetarkkailun tulokset paljastivat muutamia mielenkiintoisia näkemyksiä: vierailijat käyttäytyvät enemmän toivotulla tavalla, kun he selailevat verkkosivustoa paikallisella kielellä tai silloin, kun verkkosivusto on nopea ja mobiililaitteille optimoidun käyttökokemuksen tarjoaminen on tärkeää, koska mobiililaitteiden käyttö verkon selailuun kasvaa räjähdysmäisesti

Measuring the Performance of eCommerce Websites– An Owner’s Perspective

Measurements that capture performance have long enabled businesses to monitor and improve their strategic and operational goals. For eCommerce websites, there has been a limited understanding of how to measure performance even though it has been researched in many ways and in various contexts over the past decade. The authors of this study adopted an owner perspective to develop and empirically test a model of website performance measurement. The results suggest that performance is a second order factor model. The first order factors of the model are usage, financial benefits and owner satisfaction. The model is useful as a tool for benchmarking the performance of the website as well as a foundation for operationalising performance. Available at: https://aisel.aisnet.org/pajais/vol3/iss1/2

Using clickstream data to analyze online purchase intentions

Hoje em dia as técnicas de negócio tradicionais estão ultrapassadas devido à emergência de novos modelos de negócio, nomeadamente no espaço online através da Internet. Este novo espaço de comércio eletrónico difere substancialmente das atividades tradicionais que têm por bases espaços físicos. Assim, torna-se imperativo que as empresas adotem novas estratégias e sejam capazes de compreender as motivações que guiam os compradores online, caso pretendam suceder no competitivo ecossistema virtual.Os logs dos servidores são a principal fonte de informação, sobre os seus utilizadores, que as empresas dispõem. Estes ficheiros contêm detalhes sobre como cada cliente navegou pela loja eletrónica, mais ainda, através destes dados é possível reconstruir a sequência exata das páginas que cada um acedeu. Este tipo de dados, conhecidos como dados de clickstream, são fundamentais para conseguir compreender o comportamento dos utilizadores. Aliás, a análise e exploração desta informação são essenciais para melhorar a relação com os clientes.A análise de dados clickstream permite, acima de tudo, a compreensão de determindas intenções que motivam os utilizadores a realizar determinadas ações. A percentagem de conversão de utilizadores é uma das métricas mais conhecidas e que se relaciona diretamente com as intenções dos mesmos. Durante esta dissertação nós investigamos outro tipo de intenções, nomeadamente, fatores relacionados com os utilizadores que passam a ser compradores e ainda com a probabilidade de compra em tempo real. São utilizados dados concretos, provenientes de uma das maiores empresas europeias na área do retalho alimentar, para alimentar e avaliar diferentes modelos de data mining.Nowadays, traditional business techniques are almost deprecated due to the insurgence of the world of online virtual shopping, the so-called e-commerce. This new, in many ways, uncharted territory poses difficult challenges when it comes to apply marketing techniques especially traditional methods, as these are not effective when dealing with online customers. In this context, it is imperative that companies have a complete in-depth understanding of online behavior in order to succeed within this complex environment in which they compete.The server Web logs of each customer are the main sources of potentially useful information for online stores. These logs contain details on how each customer visited the online store, moreover, it is possible to reconstruct the sequence of accessed pages, the so-called clickstream data. This data is fundamental in depicting each customer's behavior. Analyzing and exploring this behavior is key to improve customer relationship management. The analysis of clickstream data allows for the understanding of customer intentions. One of the most studied measures regards customer conversion, that is, the percentage of customers that will actually perform a purchase during a specific online session. During this dissertation we investigate other relevant intentions, namely, customer purchasing engagement and real-time purchase likelihood. Actual data from a major European online grocery retail store will be used to support and evaluate different data mining models

Data Mining Applications On Web Usage Analysis & User Profiling

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2003Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2003Tez çalışmasında veri madenciliği teknolojisi, fonksiyonları ve uygulamaları özetlenmiştir. OLAP teknolojilerine ve veri ambarlarına da veri madenciliğinin anahtar kavramları olarak değinilmiştir. Uygulama kısmında müşteri ve alışveriş kalıpları analizi için bir internet parakendecisinin işlemsel verileri kullanılmıştır. Müşteri segmentasyonu ve kullanıcı betimleme gibi konulardaki kurumsal kararları desteklemek amacıyla veri içerisindeki kalıplar çıkarılmaya çalışılmıştır.This thesis gives a summary of data mining technology, its functionalities and applications. OLAP technology and data warehouses are also introduced as the key concepts in data mining. The usage of data mining on the internet and the decisions based on internet usage data are introduced. In the application section a web retailer’s transactional data is used for analyzing customer and shopping patterns.Hidden patterns within the data are tried to be extracted in order to support business decisions such as user profiling and customer segmentation.Yüksek LisansM.Sc

Understanding the Value of Online Ad Targeting - Advertiser's Perspective

Online advertising is a huge, growing industry and a key part of the growth is the improving efficiency of online advertising due to ad targeting. Targeting is a process that includes collecting data from various sources to help match advertisements with consumers who are most likely to be interested and to purchase the advertised products. While the consensus is that targeting can be used to provide value for advertisers, and for consumers, the incremental value is difficult to quantify. In this paper, we take a look at some of the problems advertisers face when using targeting and present some existing solutions to mitigate these challenges. Earlier literature is used to exemplify how advertisers can effectively identify desired target audiences, choose the optimal methods for targeting to reach the selected audience and measure the success of their campaigns. One of the key challenges for advertisers however, appears to be difficulties understanding the platforms they use for online advertising. Participant observation, a method often used for ethnographic research is presented here as a way for advertisers to learn about the ad platforms and the success of their campaigns. In business, participant observation has been used to analyze the quality of in-store services, but here its use is developed and demonstrated in an online environment. To exemplify how the method can be used in an online advertising context, this paper presents the findings of a study, where ads were observed on YouTube. The study is a combination of market research and marketing research. First, ads from four different markets are observed to find out whether market size and the level of data privacy regulations affect how advertisements appear to consumers. Then, additional observations are made in two of the markets, to see how disabling personalized advertising affects how adverts are distributed to consumers. The study presented here, is intended as a proof-of-concept and advertisers can use the developed method in a multitude of ways to find out valuable insight about online advertising platforms. Participant observation can be used for example to better understand the setup process of targeted advertising campaigns, to optimize one’s campaigns and to examine how one’s competitors appear to be running their campaigns. In addition to numerous business use cases like these, the method can be used for academic purposes, as presented in this paper