Programmatic advertising automates the digital ad buying process using tech platforms like DSPs, SSPs, and ad exchanges. Here is my straightforward look at the key terms and concepts:
Ad Network and Ad Server
Ad Network: An ad network connects advertisers with websites that want to host ads, making it easier for both sides to transact. For example, Google AdSense is an ad network that matches ads with relevant websites (Arscop, 2023).
Ad Server: An ad server stores and delivers ads to websites and tracks their performance. Google Ad Manager is a prominent example of an ad server (Nielsen, 2024).
DSP, DMP, and SSP
DSP (Demand-Side Platform): A DSP helps advertisers buy ad space programmatically, setting campaign parameters and bidding on ad spots in real-time (Harvard Business Review, 2009).
DMP (Data Management Platform): This platform collects and analyses data to build detailed audience segments for targeted advertising (Forbes, 2023).
SSP (Supply-Side Platform): An SSP allows publishers to sell their ad space programmatically, maximizing revenue by auctioning it to the highest bidder (WARC, 2023).
How Programmatic Advertising Works
1. Ad Request: A user visits a website, triggering an ad request.
2. Auction: The SSP lists the ad space for bidding.
3. Bid Submission: DSPs place bids on the ad space.
4. Winning Bid: The highest bid wins, and the ad is displayed.
5. Tracking and Reporting: Ad performance is monitored and reported back to the advertiser.
First and Third-Party Cookies
First-Party Cookies: Set by the website you’re visiting, these cookies store information like login details and preferences (McKinsey, 2023).
Third-Party Cookies: Set by other domains, these cookies track your activity across different websites for personalised ads (Arscop. 2023).
Contextual vs. Behavioral Targeting
Contextual Targeting: Shows ads based on the content of the page you’re viewing, without using personal data. For example, an ad for hiking boots on an outdoor adventure blog (Nielsen, 2024).
Behavioural Targeting: Uses data from your online behaviour to show you personalised ads. If you’ve been searching for hiking boots, you might see ads for them on other sites (Harvard Business Review, 2009).
In conclusion the digital advertising ecosystem is intricate and multifaceted. Visualising its components in a segmented and spaced-out 4D map can help one better understand the dynamic interconnections and expansions within this digital framework. This approach highlights how various elements interact and evolve, providing a clearer picture of the digital advertising landscape.
References
1. Forbes. 2023. Put Privacy First to Build Trust and Elevate the Customer Experience Available at: https://www.forbes.com/sites/forbestechcouncil/2024/06/13/put-privacy-first-to-build-trust-and-elevate-the-customer-experience/ Accessed: 14 June 2024.
2. Harvard Business Review (2009) Swimming in Data? Three Benefits of Visualisation Available at: https://hbr.org/2009/12/swimming-in-data-three-benefit Accessed: 14 June 2024.
3. Arscop. 2023. The Future of Contextual Advertising. Available at: https://www.aroscop.com/the-future-of-contextual-advertising-predictions-and-trends/Accessed: 14 June 2024.
4. McKinsey (2023). Digital Marketing Trends Available at: https://getsignals.ai/blog/mckinsey-report-digital-marketing-trends-for-2023/ Accessed: 14 June 2024.
5. Nielsen. 2024. Annual Marketing Report. Available at: https://www.nielsen.com/insights/2024/maximizing-roi-in-a-fragmented-world-nielsen-annual-marketing-report/ Accessed: 14 June 2024.
6. WARC. 2023. Marketer's Toolkit 2023: A new pattern for global advertising investment? Available at: https://www.warc.com/content/feed/marketers-toolkit-2023-a-new-pattern-for-global-advertising-investment/en-GB/7659 Accessed: 14 June 2024.
Comentarios