A lot of online marketing campaigns aim to promote user interaction. The average treatment effect (ATE) of campaign strategies need to be monitored throughout the campaign. A/B testing is usually conducted for such needs, whereas the existence of user interaction can introduce interference to normal A/B testing. With the help of link prediction, we design a network A/B testing method LinkLouvain to minimize graph interference and it gives an accurate and sound estimate of the campaign's ATE. In this paper, we analyze the network A/B testing problem under a real-world online marketing campaign, describe our proposed LinkLouvain method, and evaluate it on real-world data. Our method achieves significant performance compared with others and is deployed in the online marketing campaign.
As compared to the traditional advertising, the word-of-mouth (WOM) communications have striking advantages such as significantly lower cost and rapid delivery; this is especially the case with the popularity of online social networks. This paper addresses the issue of maximizing the overall profit of a WOM marketing campaign. A marketing process with both positive and negative WOM is modeled as a dynamical model knwn as the SIPNS model, and the profit maximization problem is modeled as a constrained optimization problem. The influence of different factors on the dynamics of the SIPNS model is…
Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such as coupons, commissions to merchants. As a result, incentive optimization is the key to maximizing the commercial objective of the marketing campaign. With the analyses of online experiments, we found that the transaction network can subtly describe the similarity of merchants' responses to different incentives, which is of great use in the incentive optimization problem. In this p…
Influencer marketing has become a thriving industry with a global market value expected to reach 15 billion dollars by 2022. The advertising problem that such agencies face is the following: given a monetary budget find a set of appropriate influencers that can create and publish posts of various types (e.g. text, image, video) for the promotion of a target product. The campaign's objective is to maximize across one or multiple online social platforms some impact metric of interest, e.g. number of impressions, sales (ROI), or audience reach. In this work, we present an original continuous form…
Companies have been increasingly seeking new mechanisms for making their electronic marketing campaigns to become viral, thus obtaining a cascading recommendation effect similar to word-of-mouth. We analysed a dataset of a magazine publisher that uses email as the main marketing strategy and found out that networks emerging from those campaigns form a very sparse graph. We show that online social networks can be effectively used as a means to expand recommendation networks. Starting from a set of users, called seeders, we crawled Google's Orkut and collected about 20 million users and 80 milli…
Influence maximization is the problem of finding influential users, or nodes, in a graph so as to maximize the spread of information. It has many applications in advertising and marketing on social networks. In this paper, we study a highly generic version of influence maximization, one of optimizing influence campaigns by sequentially selecting "spread seeds" from a set of influencers, a small subset of the node population, under the hypothesis that, in a given campaign, previously activated nodes remain "persistently" active throughout and thus do not yield further rewards. This problem is i…
Twitter is increasingly used for political, advertising and marketing campaigns, where the main aim is to influence users to support specific causes, individuals or groups. We propose a novel methodology for mining and analyzing Twitter campaigns, which includes: (i) collecting tweets and detecting topics relating to a campaign; (ii) mining important campaign topics using scientometrics measures; (iii) modelling user interests using hashtags and topical entropy; (iv) identifying influential users using an adapted PageRank score; and (v) various metrics and visualization techniques for identify…
In this work, we are interested on the analysis of competing marketing campaigns between an incumbent who dominates the market and a challenger who wants to enter the market. We are interested in (a) the simultaneous decision of how many resources to allocate to their potential customers to advertise their products for both marketing campaigns, and (b) the optimal allocation on the situation in which the incumbent knows the entrance of the challenger and thus can predict its response. Applying results from game theory, we characterize these optimal strategic resource allocations for the voter …
With the growing importance of corporate viral marketing campaigns on online social networks, the interest in studies of influence propagation through networks is higher than ever. In a viral marketing campaign, a firm initially targets a small set of pioneers and hopes that they would influence a sizeable fraction of the population by diffusion of influence through the network. In general, any marketing campaign might fail to go viral in the first try. As such, it would be useful to have some guide to evaluate the effectiveness of the campaign and judge whether it is worthy of further resourc…
Mobile app developers use paid advertising campaigns to acquire new users. Marketing managers decide where to spend and how much to spend based on the campaigns' performance. Apple's new privacy mechanisms have a profound impact on how performance marketing is measured. Starting iOS 14.5, all apps must get system permission for tracking explicitly via the new App Tracking Transparency Framework, which shows the users a pop-up asking if they give the app permission to track. If a user does not allow tracking, the required identifier to deterministically find the online advertising campaign that…
Viral campaigns are crucial methods for word-of-mouth marketing in social communities. The goal of these campaigns is to encourage people for activity. The problem of incentivised and non-incentivised campaigns is studied in the paper. Based on the data collected within the real social networking site both approaches were compared. The experimental results revealed that a highly motivated campaign not necessarily provides better results due to overlapping effect. Additional studies have shown that the behaviour of individual community members in the campaign based on their service profile can …
Viral marketing campaigns seek to recruit the most influential individuals to cover the largest target audience. This can be modeled as the well-studied maximum coverage problem. There is a related problem when the recruited nodes are connected. It is called the maximum connected cover problem. This problem ensures a strong coordination between the influential nodes which are the backbone of the marketing campaign. In this work, we are interested on both of these problems. Most of the related literature assumes knowledge about the topology of the network. Even in that case, the problem is know…
Online social networks provide a medium for citizens to form opinions on different societal issues, and a forum for public discussion. They also expose users to viral content, such as breaking news articles. In this paper, we study the interplay between these two aspects: opinion formation and information cascades in online social networks. We present a new model that allows us to quantify how users change their opinion as they are exposed to viral content. Our model is a combination of the popular Friedkin--Johnsen model for opinion dynamics and the independent cascade model for information p…
Political campaigns are among the most sophisticated marketing exercises in the United States. As part of their marketing communication strategy, an increasing number of politicians adopt social media to inform their constituencies. This study documents the returns from adopting a new technology, namely Twitter, for politicians running for Congress by focusing on the change in campaign contributions received. We compare weekly donations received just before and just after a politician opens a Twitter account in regions with high and low levels of Twitter penetration, controlling for politician…
Efficient marketing or awareness-raising campaigns seek to recruit $n$ influential individuals -- where $n$ is the campaign budget -- that are able to cover a large target audience through their social connections. So far most of the related literature on maximizing this network cover assumes that the social network topology is known. Even in such a case the optimal solution is NP-hard. In practice, however, the network topology is generally unknown and needs to be discovered on-the-fly. In this work we consider an unknown topology where recruited individuals disclose their social connections …
Online Social Networks (OSNs) attract billions of users to share information and communicate where viral marketing has emerged as a new way to promote the sales of products. An OSN provider is often hired by an advertiser to conduct viral marketing campaigns. The OSN provider generates revenue from the commission paid by the advertiser which is determined by the spread of its product information. Meanwhile, to propagate influence, the activities performed by users such as viewing video ads normally induce diffusion cost to the OSN provider. In this paper, we aim to find a seed set to optimize …
Online advertising, as the vast market, has gained significant attention in various platforms ranging from search engines, third-party websites, social media, and mobile apps. The prosperity of online campaigns is a challenge in online marketing and is usually evaluated by user response through different metrics, such as clicks on advertisement (ad) creatives, subscriptions to products, purchases of items, or explicit user feedback through online surveys. Recent years have witnessed a significant increase in the number of studies using computational approaches, including machine learning metho…
Payment platforms have significantly evolved in recent years to keep pace with the proliferation of online and cashless payments. These platforms are increasingly aligned with online social networks, allowing users to interact with each other and transfer small amounts of money in a Peer-to-Peer fashion. This poses new challenges for analysing payment data, as traditional methods are only user-centric or business-centric and neglect the network users build during the interaction. This paper proposes a first methodology for measuring user value in modern payment platforms. We combine quantitati…
Social networks are commonly used for marketing purposes. For example, free samples of a product can be given to a few influential social network users (or "seed nodes"), with the hope that they will convince their friends to buy it. One way to formalize marketers' objective is through influence maximization (or IM), whose goal is to find the best seed nodes to activate under a fixed budget, so that the number of people who get influenced in the end is maximized. Recent solutions to IM rely on the influence probability that a user influences another one. However, this probability information m…
