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How AI & Other Emerging Tech Are Revolutionising Programmatic Ad Industry

By leveraging technology, programmatic advertising enables real-time bidding and targeting of ad inventory.

By Biddappa Muthappa

As the world is constantly changing, so is the way people consume media and make payments digitally. People are gravitating towards TV screens, connected devices like smart TVs, smartphones, speakers etc. The rise of virtual reality has also been a factor that had a positive impact on digital consumption. As we move forward in a digital world, digital platforms have become the first place where people go to consume content. This shift in behaviour has led brands and marketers to realise the importance of reaching their target audience where they are most active. “Programmatic” has been a game-changer for digital advertising, making it easier and more cost-effective for brands to reach their target audiences.

Programmatic advertising has transformed the way digital ads are bought and sold. By leveraging technology, it enables real-time bidding and targeting of ad inventory, making it possible for brands and marketers to reach specific audiences with greater precision and efficiency. 

Though programmatic advertising has evolved significantly over the years, one of the key developments in this segment has been the use of artificial intelligence (AI). AI is transforming the sector by enabling marketers to deliver more personalised, relevant, and targeted advertising to consumers at scale. AI enables marketers to collect large amounts of data and allows them to gain insights into customer behaviour, such as preferences, purchase history, and online activity.

Impact Of AI On Programmatic Advertising

  • Identify audience or touch point across multiple channels: Traditionally, programmatic advertising has always been part of multichannel strategies. However, with the rise of technology, phones have become smart, TVs are connected, iPods have given way to Spotify and even billboards are digital. That means almost all screens and channels can be bought programmatically, and it means advertisers must take an omnichannel approach to programmatic. 
    To achieve an omnichannel approach, marketers need to integrate siloed data from different sources, to create more reliable attribution models, better cross-platform targeting and align budgets with optimal outcomes. AI can help us in bringing the masses of disparate data together, and then use lookalike, attribution and recommendation models to analyse vast amounts of data (consumer behaviour, user journey, interests, demographics) to identify patterns and define user personas, targeting attributes and domains to determine target audience or touch points to make informed decisions.
  • Improved targeting and campaign optimisation: Historically, programmatic advertising faced several challenges in scaling due to the fragmentation of the advertising ecosystem and access to limited data. The data-enabled AI solutions (multi-armed-bandit, reinforcement learning, linear optimisation, etc.) allowed marketers to automate the tasks involved in ad placement and optimisation, such as bidding, budgeting, and targeting at scale. Now marketers can run campaigns more efficiently and effectively, reducing the time and resources needed to manage their campaigns and also automatically target ads to the right audience and optimise campaigns for maximum performance.
  • Better performance using real-time data: Real-time data is critical in programmatic advertising as it allows marketers to make data-driven decisions and adjust their campaigns in real time. Real-time data includes information on user behaviour, demographics, location, and interests, which can be used to serve targeted ads to users. AI algorithms can also optimise ad delivery by analysing user engagement with ads, click-through rates, and conversion rates to improve ad performance.
  • Ad creative intelligence: In programmatic advertising, ‘creative’ plays a key role in the success of the ad campaign and it is important to continuously monitor and invest in high-quality creative that resonates with the target audience and aligns with campaign objectives. Using Machine Learning and Computer Vision we can not only predict the creatives customers would prefer, but also answer why they prefer it - by analysing images, videos, and text to identify which elements are most effective in driving engagement and conversions.
  • Fraud detection: As the number of addressable channels grows, the risk of fraud also increases, and traditional measurement methods are unable to identify and detect fraudulent activity.  Fortunately, AI-enabled fraud or anomaly detection algorithms help identify fraud by learning key browsing and behavioural patterns across all data. 

Future Of Programmatic Advertising With AI

The future of programmatic advertising with AI is exciting, with numerous potential benefits that can shape the future of the industry, including:

  • User privacy has become one of the top concerns in the ad tech industry. Phasing out Personal Identifiable Information (PIIs) can have a significant impact on the industry as they play a major role in identifying audiences for targeting and measurement. Natural language processing can help overcome this by identifying customer sentiment and journey to enable cohort or topic-based targeting.
  • Then as we move towards a privacy-first ecosystem, advertisers and marketers must share their first-party data for researchers and data scientists for analysis without divulging personal identification. Differential privacy is one of the key AI techniques that enables researchers and database analysts to use aggregated data for advanced insights while maintaining privacy standards and this will be one of the key evolutions in programmatic advertising.
  • Computer vision will evolve and benefit programmatic advertising by enabling dynamic creative optimisation within the ecosystem. Creativity is the primary and key component for ads to be eye-catching and visually appealing to stand out from the competition.
  • Lastly, generative AI, involves using machine learning algorithms to generate new content, such as ad copy or creative assets. As generative AI technology advances, it could be used to automate the process of ad creation and testing, allowing marketers to develop and iterate on new ad concepts quickly and efficiently.

It is a known fact that AI would disrupt all sectors by providing new ways of working, communicating, and solving problems; and it is true for programmatic advertising as well. These emerging AI technologies have the potential to transform the programmatic advertising industry, enabling more personalised and effective ad targeting, and improving campaign performance. Embracing AI in programmatic advertising is crucial for businesses that want to stay ahead of the competition in this fast-evolving digital landscape. 

(The author is the Director of Data Science at MiQ)

Disclaimer: The opinions, beliefs, and views expressed by the various authors and forum participants on this website are personal and do not reflect the opinions, beliefs, and views of ABP Network Pvt. Ltd.

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