SmartAds

Abstract

A recent study showed that while US consumers spent 30% more time on mobile apps than on traditional web, advertisers spent 1600% less money on mobile ads. One key reason is that unlike most web ad providers, today's mobile ads are not contextual-they do not take into account the content of the page they are displayed on. Thus, most mobile ads are irrelevant to what the user is interested in. For example, it is not uncommon to see gambling ads being displayed in a Bible app. This irrelevance results in low clickthrough rates, and hence advertisers shy away from the mobile platform.Using data from top 1200 apps in Windows Phone marketplace, and a one-week trace of ad keywords from Microsoft's ad network, we show that content displayed by mobile apps is a potential goldmine of keywords that advertisers are interested in.However, unlike web pages, which can be crawled and indexed offline for contextual advertising, content shown on mobile apps is often either generated dynamically, or is embedded in the apps themselves; and hence cannot be crawled. The only solution is to scrape the content at runtime, extract keywords and fetch contextually relevant ads. The challenge is to do this without excessive overhead and without violating user privacy. In this paper, we describe a system called SmartAds to address this challenge.We have built a prototype of SmartAds for Windows Phone apps. In a large user study with over 5000 ad impressions, we found that SmartAds nearly doubles the relevance score, while consuming minimal additional resources and preserving user privacy.

An Automatic and Scalable Application Crawler for Large-Scale Mobile Internet Content Retrieval

“…Most of the relevant studies on this topic have focused on automated tesing for applications [2], [3] and commercial advertising [4]. Few studies have worked directly on content retrieval.…”