Client Briefs, Campaign Performance: How Ad Agencies Are Using Generative AI Today

Changing old ways and finding new audiences

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Over the past eight months, the ad industry has witnessed a definitive role for generative AI inside creative and media agencies; from decoding client briefs to amassing real-time insights on campaign performance, gen AI is getting the job done more quickly and efficiently.

Across IPG’s Momentum, S4 Capital’s Media.Monks and independent agency PMG, the opportunities presented by generative AI have led to accelerated ad campaign output and reaching new consumers and winning new business.

“We look at generative AI as a force multiplier in terms of our ability to react and respond to client needs,” said Jason Snyder, CTO of Momentum, an IPG agency.

According to a Gartner survey, nearly 63% of marketing leaders plan to invest in this technology in the next 24 months. In a landscape inundated with continuous AI-related developments, the practical applications are providing significant value for marketers and the agencies that support them.

Writing and decoding client briefs

At Momentum, the agency has created an operating system of sorts that employs a unified data model linking existing information with guidance on the next steps in their operations.

This process begins with understanding a client brief. When the agency receives a new brief, its AI tech stack swiftly identifies the most suitable people within the company to tackle it. A large language model (LLM) can extract insights from previous, similar campaigns to aid a response to the new brief.

This response includes what the creative output could look like, what the strategy is and what kind of target and segmentation works, according to Snyder.

Media.Monks, the S4 Capital agency, has taken a consultative approach distinct from the conventional ad agency workflow, where clients dispatch briefs and agencies respond accordingly.

The agency, through its open-source generative AI tools, is encouraging its brand partners’ marketing teams to reduce their reliance on manual processes when drafting briefs.

This means the generative AI taps into real-time signals from a brand’s first-party data across marketing channels which informs real-time variations in creative content, giving rise to new briefs crafted with the assistance of generative AI.

“That effectively is a flywheel that is running in the cloud that is enabled by artificial intelligence,” said Henry Cowling, Media.Monks’ chief innovation officer.

These creative variations have proven particularly beneficial for Media.Monks’ global automotive brand partner, with the delivery of region-specific content, based on micro-moments such as hour, date, location or real-time events taking place. This all led to increased brand relevance for the client, Cowling says.

Speed up ad optimization

At independent digital agency PMG, marketers can glean real-time data visualizations and campaign reports via a generative AI-powered augmented analytics tool called “Ask Alli” trained on data from vendor platforms, aggregated CDP and ecommerce insights.

Made available to the agency’s brand partners next week, marketers will be able to gain myriad campaign insights by posing queries such as “Can you show me the performance of TikTok vs. Snapchat vs. Meta for the past 7 days?” or “What are my best-performing audiences?”

In doing so, they can track their social budget’s pacing over the last month allowing them to make data-driven decisions, such as evaluating platform performance, identifying top-performing creatives and ensuring their ad spend aligns with monthly objectives.

This negates the need for an analytics or data engineering team to construct dashboards, pull reporting or spend time manually identifying and translating insights from data, said Chris Alvares, PMG’s head of technology.

Discover new audiences

Momentum’s AI tech stack, soon to be made client-facing, utilizes an extensive array of data sources including clients’ first-party data, third-party data and the agency’s proprietary research, which range from previous ads, target keywords, funnel data and demographic insights.

This enables precision segmentation that allows brand partners to target their desired audience.

For instance, consider a consumer-packaged goods (CPG) company launching a new product that diverges from its traditional offerings. While they may have a deep understanding of their existing customer, they lack information about the new category because of a lack of data and insights.

Through Momentum’s AI tech stack, these brands gain the capability to identify their potential new customers, determine effective channels for engagement and even create tailored content.

“This is where the generative AI tools become valuable in the realm of experiential marketing,” said Momentum’s Snyder.