The Gist

  • Precision targeting. Programmatic advertising leverages AI, ML and analytics to deliver highly personalized ads to specific target audiences, maximizing engagement and conversion rates.
  • Efficiency boost. Automating the ad-buying process through programmatic advertising streamlines campaign execution, reduces manual tasks and provides real-time insights for data-driven optimization.
  • Challenges ahead. Brands must navigate data privacy concerns and address algorithmic bias to ensure ethical and effective programmatic advertising strategies.

Programmatic advertising uses advanced technology, including artificial intelligence (AI), machine learning (ML) and analytics, to gain a deep understanding of a brand’s audience before ad space is purchased. This enables brands to deliver highly relevant and personalized ads to their target customers, increasing the chances of engagement and conversion.

This article will discuss programmatic advertising, the ways that brands are using it to achieve highly personalized marketing campaigns and the challenges of doing so. 

What Is Programmatic Advertising?

Brands often spend millions in an effort to design the best advertisements for their products and services but often falter when they fail to target the right customers at the right time. To maximize an ad campaign’s success, brands must ensure strategic placement targeting their ideal audience, otherwise, even the most perfect ad may fail to achieve its full potential. Programmatic advertising seeks to solve that challenge by automating the process of buying and selling online ad inventory through an efficient, data-driven and real-time bidding system. 

Programmatic advertising uses AI and ML algorithms to make decisions about which ads to show to specific users and when and where to show them. This streamlines the ad-buying process, making it more efficient and targeted compared to traditional ad-buying methods.

This automated advertising methodology offers several benefits, the chief of which is improved targeting. Using programmatic advertising, brands are able to use customer data to reach those customers who are the most likely to be receptive at the most appropriate time with more relevant and personalized. Real-time bidding facilitates optimized ad spend by paying only for the ad impressions that match the target audience.

Additionally, programmatic advertising automates the ad-buying process, which reduces manual tasks and speeds up campaign execution. Brands can access real-time data and insights, allowing them to optimize their advertising campaigns.

Bari Bucci, vice president of trading and programmatic operations at Ampersand, a data-driven TV ad sales and tech company, told CMSWire that one of the main reasons why brands use programmatic advertising is because of its ability to identify and reach a brand’s target audience.

“Whether it be interest-based, behavior-based or demographic-based, reaching a brand’s specific audience allows for a better return on investment,” explained Bucci. “Additionally, programmatic advertising gives a brand real-time insights including the ability to see campaign performance, optimize and adjust their targeting which decreases potentially wasted spend and drives better overall outcomes.”

Related Article: 4 Ways That AI Is Improving the Customer Experience

How Does Programmatic Advertising Work?

With programmatic advertising, advertisers and publishers use a demand-side platform (DSP) and a supply-side platform (SSP) respectively, which are connected via an ad exchange.

Here’s how the process works:

Advertisers set up their campaigns on a DSP, and define their target audience, ad budget and bidding strategy. They also upload the creatives (ad content) they wish to display. Examples of DSPs include Amazon DSP, AdKernel, Google Ads, Facebook Ads Manager and Basis DSP

Publishers make their ad inventory available through an SSP. They define the criteria for the ads they want to display on their site, such as industry, format and minimum bid price. When a user visits a publisher’s website, their SSP sends a request to the ad exchange, which then sends the request to the connected DSPs. Examples of SSPs include Google Ad Manager, OpenX, Pubmatic, Sharethrough and Xandr.

DSPs are able to analyze the user’s data and context (e.g., browsing behavior, demographics, location) to determine if the user matches the target audience of any active campaigns. When it finds a match, the DSP submits a bid for the ad space. The ad exchange then conducts an auction among the competing bids, and the highest bidder wins the ad space. At that point, in a fraction of a second, the winning ad is displayed on the publisher’s site.

“From a consumer perspective, having ads that are relevant provides an overall better user experience,” said Bucci. “This can increase the likelihood that the users will engage with a brand and move further down the purchase funnel.”

Related Article: AI’s Role in Digital and Retail Personalization, Part 1: The Big Picture

What Role Do Artificial Intelligence and Machine Learning Play?

AI and ML are integral components of programmatic advertising and are used to automate and optimize various aspects of the process, making it more efficient and effective. AI and ML algorithms analyze extremely large amounts of data, including user demographics, browsing behavior and interests, to identify the target audience for specific ad campaigns. This enables advertisers to deliver more relevant and personalized ads to users. The algorithms assess the value of each ad impression in the real-time bidding process, allowing advertisers to place an optimal bid for the ad space. The use of these AI and ML algorithms results in more cost-effective ad placements and better returns on ad spend.


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