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.

Learning Opportunities

AI and ML are also used to dynamically generate and optimize ad creatives that are based on the user's profile, context and preferences, ensuring that the most engaging and relevant ad content is delivered to the user. Additionally, AI and ML enable advertisers to track and target users across multiple devices, providing a consistent and personalized ad experience.

Finally, by analyzing user-generated content, such as social media posts and customer reviews, AI and ML are able to help advertisers understand user sentiment and preferences, which facilitates the creation of more relevant and effective ads.

How Are Brands Using Programmatic Advertising?

Programmatic advertising has emerged as a game-changer for brands, enabling marketers to refine their strategies, zero in on their target demographics and fine-tune campaigns on-the-fly. By tapping into the potential of AI, ML and data analysis, brands can now create personalized, attention-grabbing ads that resonate with users across a wide range of channels and devices.

Brands can use localized targeting and retargeting to increase brand awareness, while real-time bidding (RTB) optimizes ad spend. Stephen Davis, managing partner at Flourish Direct Marketing, a specialist independent CRM agency, told CMSWire that by using programmatic advertising, he is able to reach highly motivated target audiences at the right time and place using geo radius targeting. “Using specific longitudes and latitudes, we can target users who are actively passing through precise locations down to a geo radius of 10x10m — showing these users tailored ads,” said Davis. “In conjunction with ad scheduling, we can show tailored ads to users in specific locations, at certain times of the day.”

Many brands not only use programmatic advertising themselves, but they also offer it to their clients:

  • As of November 2022, advertisers were able to purchase Netflix ads using the Xandr DSP, which enables them to set up programmatic ad campaigns with guaranteed pricing and placements.
  • In 2018, Procter & Gamble pitched its Performance Marketing Retail Partnerships to retailers, requesting that they share their customer data so that it can use programmatic advertising to serve targeted ads.
  • Amazon uses programmatic advertising to serve relevant advertisements for products and services to its customers and also offers its own DSP to clients.
  • Walmart also has its own DSP that provides brands with access to Walmart’s in-store and online shopping data. 

Programmatic advertising enables brands to target narrow audiences at the time and place they are most likely to be receptive to advertisements. “We can deliver sport tickets ads to users who are located at a certain stadium when we know there is a particular fixture taking place,” said Davis. “For example, during the Autumn Rugby Internationals, we were able to show ads to promote the upcoming Six Nations tournament to users who were located at Twickenham Stadium before, during, and after the game. These directed through to a specialist rugby ticketing website.” 

Geo-targeting, used in conjunction with programmatic advertising, enabled Davis to segment based on customer history and what segment or stage of the journey they were in. “These users were high intent, as we knew they had visited Twickenham during an England Rugby game so are likely interested in purchasing tickets to watch England,” said Davis. “Because of the specificity of the audience, we were able to show tailored ads directing through to an England-specific landing page, offering a range of ticket packages for upcoming England Six Nations.” 

What Are the Challenges of Programmatic Advertising?

Despite its benefits, programmatic advertising faces several challenges and ethical concerns. Data privacy is a major concern, as the use of personal data to target ads raises privacy issues among consumers and regulators. For example, in December 2022, the Irish data protection agency went to court over Meta’s use of personal data to target advertising, the result of which is that Meta will only be able to target Irish users with advertising based on personal data if the users provide consent. 

“With the increase in consumer privacy concerns and adoption of new consumer privacy regulations and laws, brands must be diligent with the consumer data they not only collect but utilize for their advertising initiatives,” suggested Bucci. “Solutions such as data clean rooms, unified IDs and the increased use of using data for strategic contextual targeting (which does not rely on identity signals) are ways in which brands can try to solve these challenges within programmatic advertising.”

Algorithmic bias is another challenge, as AI and ML algorithms may perpetuate biases present in the data they analyze, leading to unfair or discriminatory ad targeting. In 2019, Facebook was sued by the US Department of Housing and Urban Development because it allowed advertisers to target ads based on race, gender and religion. At a later date, it was revealed that Facebook’s algorithm discriminated by serving up automated ads to over 2 billion users based on their demographic information. Advertisements for preschool teachers and secretaries were displayed to a higher percentage of women, while advertisements for janitors and taxi drivers were displayed to a higher proportion of minorities.

Final Thoughts on Programmatic Advertising

Programmatic advertising enables brands to display the most appropriate advertisements to the right customers at the right time. By using AI and ML, programmatic advertising helps brands optimize ad placements, targeting and budgets based on real-time data, increasing the effectiveness of advertising campaigns while improving the customer experience.