> [!meta]- Document Info > **Author**: [[Iman Ahmadi]] > **Full Title**: Overwhelming Targeting Options: Selecting Audience Segments for Online Advertising > **Category**: #articles > > **Summary**: This paper discusses the challenges advertisers face when selecting audience segments for online advertising and the profitability of targeted campaigns. The authors propose a model that helps advertisers determine the break-even performance needed for targeted ads to be as profitable as untargeted ones. They emphasize the importance of carefully evaluating narrow audience segments, as they often require significantly higher performance to be viable. > > **Source**: [Original URL](https://readwise.io/reader/document_raw_content/222573499) ## 📄 Full Document → [[Full Document Contents/Overwhelming Targeting Options: Selecting Audience Segments for Online Advertising]] ## 🔦 Highlights & Commentary - calculate the break-even performance ofan audience seg- ment to make a targeted ad campaign at least as profitable as an untargeted one. ([View Highlight](https://read.readwise.io/read/01j99cwhk2tbdx5sjxfhxxx93x)) - Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. ([View Highlight](https://read.readwise.io/read/01j99cxegmyffc12m8xszsf7g3)) - Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. ([View Highlight](https://read.readwise.io/read/01j99cymggf6nfv5y61p440eaw)) - , it is difficult to ascertain the impact of tar- geting on an advertiser’s profit because targeting affects profit in three ways. First, targeting often comes with extra data costs for the advertiser (or an increased price of the ad impression), which negatively affects the advertiser’s profit. Second, tar- geting reduces the number of reachable users, which may decrease the total number of conversions and, in turn, the adver- tiser’s profit. Third, and despite the above, targeting should improve the performance of advertising campaigns via an increase in at least one of the following metrics: The probability of a click, the probability of a conversion, and the (long- term) margin per conversion (Beales, 2021; Yan et al., 2009). Those opposing effects make it difficult for advertisers to pre- dict the profitability of audience segments. ([View Highlight](https://read.readwise.io/read/01j99dcvs9mvb78y5cxdsdcnc0)) - Note: Think of this as two axes: reach and efficacy - Intuitively, the advertiser expects a performance lift (i.e., in CTR, CR, or margin per conversion) when targeting users who are more likely to be interested in the advertiser’s products (Aziz & Telang, 2016; Farahat & Bailey, 2012; Goldfarb & Tucker, 2011b; Rafieian & Yoganarasimhan, 2021; Yan et al., 2009). Yet, targeting may decrease the number of ad impressions by reducing the number of available users because it excludes those who do not meet the targeting cri- teria. Moreover, targeting may come with additional costs for the advertiser because of increased performance from tar- geted users. ([View Highlight](https://read.readwise.io/read/01jd02v2wcj27ws16909nxm5q5))