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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Counterfactual-based Incrementality Measurement in a Digital Ad-Buying Platform · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1705.00634/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1705.00634/feed.xml" rel="self" type="application/rss+xml" /><item><title>Counterfactual-based Incrementality Measurement in a Digital Ad-Buying Platform — HN submission</title><link>https://news.ycombinator.com/item?id=14272581</link><guid isPermaLink="false">urn:hackerpapers:submission:1705.00634:14272581</guid><pubDate>Fri, 05 May 2017 11:21:42 GMT</pubDate><description>&lt;p&gt;MediaMath&amp;#x27;s ground-breaking new paper on causal ad-effectiveness measurement&lt;/p&gt;&lt;p&gt;https://arxiv.org/abs/1705.00634 Abstract: The problem of measuring the true incremental effectiveness of a digital advertising campaign is of increasing importance to marketers. With a large and increasing percentage of digital advertising delivered via Demand-Side-Platforms (DSPs) executing campaigns via Real-Time-Bidding (RTB) auctions and programmatic approaches, a measurement solution that satisfies both advertiser concerns and the constraints of a DSP is of particular interest. MediaMath (a DSP) has developed the first practical, statistically sound randomization-based methodology for…&lt;/p&gt;&lt;p&gt;3 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1705.00634/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>stat.ME</category></item></channel></rss>
