Refine
Document Type
- Article (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- App Tracking Transparency Framework (1)
- Apple (1)
- Audience Segments (1)
- Facebook (1)
- Online Advertising (1)
- Spotify (1)
- Targeting (1)
- Third-Party Data (1)
Institute
UNDERSTANDING THE COMPETITIVE ENVIRONMENT FOR DIGITAL CONSUMER ATTENTION IS CRUCIAL FOR BANKS’ STRATEGIC ACTIONS. THEREFORE, BANKS NEED TO DETERMINE THE MARKET THEY COMPETE FOR, THEIR SUCCESS ON THIS MARKET, AND WHO THEY COMPETE WITH FOR CONSUMER ATTENTION. USING ORGANIC SEARCH ENGINE DATA, WE PROPOSE A NEW APPROACH TO (I) DEFINE THE DIGITAL MARKET, (II) IDENTIFY THE PLAYERS IN THE MARKET, (III) ESTIMATE THE DISTRIBUTION OF DIGITAL CONSUMER ATTENTION ACROSS BANKS, AND (IV) UNCOVER THE COMPETITIVE MARKET STRUCTURE FOR THE ONLINE RETAIL BANKING MARKET IN GERMANY.
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). 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. 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. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.