Generative AI (genAI) represents a groundbreaking technological leap. It's also a transformative catalyst in the world of AdTech.

The development of artificial intelligence has been a gradual process over several decades. The technology has its roots in the mid-20th century, and over the years, there have been significant advancements in machine learning, neural networks, and other AI-related technologies.

These advancements are now being implemented in the realm of the AdTech world.

Key Points

• Generative AI in AdTech enables the creation of context-aware advertisements and reduces time and human resources in content creation.

• Brands and ad agencies can leverage genAI to streamline the whole ad campaign process, including asset creation, measurement, and analysis.

• The integration of genAI into AdTech solutions is an ongoing process.

Generative AI in AdTech

Generative AI relies on automated content creation, employing generative adversarial networks (GAN) and natural language processing (NLP).

GANs involve two competing neural networks, generating content and assessing authenticity, resulting in high-quality, human-like content. NLP complements GANs by processing text to generate responses mimicking human communication.

In AdTech, this enables the creation of context-aware advertisements, generating personalised content, and reducing time and human resources in content creation.

6 Use Cases of Generative AI in AdTech

Current and emerging use cases for generative AI in AdTech fall into three categories:

• Generative AI as interactive help

• Content inspiration and generation

• Value articulation

The AdTech industry has started to adopt generative AI and benefit from it.

Creating and Scaling Assets for Ad Campaigns

Google is in the process of beta testing the new feature of genAI in Performance Max (PMax). Inside the solution, Google AI creates and scales new assets in seconds.

The search giant aims to generate assets “that help you reach customers across all of Google’s performance inventory and formats”, but with the supervision of a person responsible for overseeing the ad campaign.

Before creating new assets, Performance Max will analyse past advertising performance data to generate content that resonates better with the target audience. 

To embrace experimenting with content creation, Google AI will always generate different images.

Performance Max suggests and creates headlines, descriptions, and images. You can also input text prompts to generate additional assets.

In addition to creating new assets, Performance Max can help edit existing images directly in Google Ads. Simply describing your new idea for a specific image, Google’s generator will deliver visualisations you can test at scale.

The genAI image editor helps create new image elements.

Ad agencies and advertisers can generate:

• Text assets

• Image assets

• Logos and business name assets

• Video assets

Google is actively beta-testing the integration of AI-generated search and shopping ads into standard search results, demonstrating its commitment to enhancing advertising workflows through AI.

Enhancing Ad Creatives

Meta's Ads Manager harnesses generative AI to advance advertising efficiency. The company introduced three new features to maximise advertisers' productivity, personalisation and performance.

The first feature lets advertisers change the backgrounds of their product images by generating various options. These backgrounds are created based on the original product images and are generally simple with colours and patterns.

The second feature, image expansion, helps advertisers adjust their assets to fit different sizes required for various products, such as Feed or Reels.

In Meta Ads Manager, the text variations feature uses AI to generate up to six text versions from the advertiser's original copy. These variations can emphasise specific keywords and input phrases. Advertisers can edit the generated text or choose the ones that best fit their goals. Meta may display different text combinations to varying users during the campaign to test which ones get better responses. However, detailed performance information for each text variation is unavailable, as reporting is based on a single ad.

In a survey, most advertisers who tried generative AI believed it would save them time. Half of them think it could save them five hours or more every week, which is like gaining an extra month each year. The new enhancements benefit the small business owners the most.

Reducing Friction in Ad Imagery Production

In March 2023, Amazon ran a survey which discovered that among advertisers who build unsuccessful campaigns, nearly 75% underscored building ad creative and choosing a creative format as their biggest challenge.

Later that year, the company introduced a generative AI mechanism to help advertisers produce ad images in seconds. The generative model needs only a selected product, available for advertisers when creating ad campaigns for Sponsored Brands, and a short description of the requested ad creative.

The feature is dedicated to advertisers of all sizes but may be the most useful to advertisers without in-house capabilities or agency support.

Source: Amazon

Streamlining the Ad Campaign Creation Process

Typeface unveiled a comprehensive generative AI solution in collaboration with GrowthLoop and Google Cloud's BigQuery and GenAI Foundation Models.

This integrated solution streamlines the entire campaign creation process — from defining audience segments to crafting personalised content, enabling rapid campaign launches across various marketing channels.

The GenAI Marketing Solution offers key features:

• Unified Customer Data Access In BigQuery: Users can create a holistic Customer 360 view by accessing first-party data from ads, sales, customers, and products.

• Audience Definition With Natural Language Understanding: Marketers can define audience segments using GrowthLoop's natural language understanding within their data cloud.

• Cross-Channel Content Creation: Typeface's embedded application allows the crafting of personalised content leveraging Google GenAI Foundation Models, ensuring brand-personalised AI content generation across channels.

• Orchestration And Performance Measurement: Deploy target audiences and content to advertising channels easily and monitor audience targeting and creative success in BigQuery.

The solution addresses challenges in efficiently transforming audience and customer data into targeted, personalised content.

Enhancing Efficiency in Advertising Workflows

Salesforce is leveraging generative AI technology across its Marketing and Commerce Clouds to enhance efficiency in campaign creation, personalisation, segmentation, measurement, and offer customisation.

Marketing GPT and Commerce GPT, both powered by Einstein GPT, enable marketers to use generative pre-trained transformers for human-like text creation. 

These tools, inspired by consumer-facing generative AI tools, including ChatGPT, allow marketers to build segments, create personalised content, and automate journey creation through natural language prompts, reducing the need for coding skills.

Salesforce's integration with OpenAI facilitates the incorporation of generative AI capabilities into various Salesforce clouds, including Marketing Cloud, Commerce Cloud, Slack, Tableau, and MuleSoft. 

Marketing GPT empowers marketers to query CRM data and generate personalised email versions and subject lines through natural language prompts. The partnership with Typeface enhances content creation scalability using generative AI. Segment Intelligence for Data Cloud connects first-party, revenue, and third-party paid media data for comprehensive campaign performance insights.

Commerce GPT provides marketers with tools to quickly create multiple content versions and auto-generate product descriptions. It responds to prompts such as "liquidate an outdated product line" and provides recommendations for storefront design, merchandising setup, and promotions. The Commerce GPT release includes a chatbot tool for AI-generated conversations with customers across channels.

Salesforce emphasises security and data integration, recognising that customers may have data outside its systems. 

An expanded partnership with Google Cloud Platform allows marketers to bring custom AI models to Salesforce through Vertex AI. 

The integration ensures secure data access between systems without physically moving or copying data, maintaining the privacy and security of customer information.

Making Marketers Independent From Data Analytics

AppsFlyer uses generative AI powered by ChatGPT to enhance its data clean room capabilities. 

The AppsFlyer data clean room uses AI to make it easier for marketing teams — they can ask questions and access data without needing technical help. This is especially important in today's privacy-focused era, as data clean rooms help measure and improve marketing across different channels more efficiently while preserving privacy.

Summary

Generative AI is transforming the AdTech industry. The current use cases are milestones in the journey toward a more efficient, personalised, and responsible advertising landscape.