57:56Austin 2026
San Diego 2024
AI and Emotional Advertising with Sarah Levinger
Sarah Levinger explores how customer language, emotional context, and AI-assisted research can help brands develop more relevant advertising and positioning.
Watch it. Put it to work.
ABOUT THIS SESSION
Understand the person behind the purchase.
Sarah Levinger explores how customer language, emotional context, and AI-assisted research can help brands develop more relevant advertising and positioning.
For creative strategists and marketers turning customer research into more meaningful messages.
- Speaker
- Sarah Levinger
Co-Founder, Tether Insights - Recorded at
- San Diego 2024 ↗
September 2024
Speaker roles and platform examples reflect the session’s original context. This is an archived conversation.
TAKE IT BACK TO YOUR DESK
Ideas to put to work.
- 01
Look for the meaning beyond the product
Ask what the product represents in the customer’s life, not only what it does.
Read this part · 00:33 ↓ - 02
Use language as research material
Gather real customer language and inspect the evidence behind the themes an AI tool identifies.
Read this part · 03:09 ↓ - 03
Connect the research to a creative question
Give the analysis a concrete messaging question and turn the answer into a testable idea.
Read this part · 06:38 ↓ - 04
Study competitors for positioning gaps
Compare competitors’ promises and emotional angles before choosing your own creative direction.
Read this part · 11:35 ↓ - 05
Keep context and customer evidence together
Use research-informed personas to explore ideas, then validate them against real customer response.
Read this part · 14:35 ↓
READ THE SESSION
The edited transcript.
A condensed, edited reading version based on the YouTube captions and session chapters. Repetition and unclear audience audio have been removed; the discussion is paraphrased for clarity, rather than presented as a verbatim transcript. Timestamps refer to the original video.
Original recording on YouTube ↗Look for the meaning beyond the product
Sarah opens with a personal story about an emotional connection to a brand. The example shows how a product can carry associations that are not visible in its specifications or price.
That becomes the foundation for the session: understand what the product means in someone’s life. A marketing team that only catalogs features can miss the reason a message resonates. Emotional context helps explain why the same functional offer can feel different to different people.
Use language as research material
The talk introduces AI as a way to examine customer language for recurring sentiments and themes. Reviews, social comments, and service interactions contain clues about expectations, frustrations, and the experience people want.
Sarah’s emphasis is on using those signals to understand the audience more deeply. The model is a research aid, not direct access to someone’s thoughts. Keep the underlying customer evidence in view when turning a pattern into a creative hypothesis.
Connect the research to a creative question
The practical section moves from collecting language to using it in marketing. A useful analysis should help answer a specific question about the customer and the message, rather than produce a broad personality description that the team cannot act on.
Ask what concern or desired feeling the material suggests, then consider how the creative could acknowledge it. This makes the output part of a working research process. The next step is a test of the message, not treating a generated explanation as a proven result.
Study competitors for positioning gaps
Sarah discusses examining publicly available competitor material, including pricing, products, and core messages. The aim is to understand the emotional territory the market already occupies and where a brand could offer a different perspective.
This is more useful than copying a competitor’s visible ad format. A different-looking ad can still say the same thing. Compare the underlying promise and customer context so the team can decide how its own product deserves to be positioned.
Keep context and customer evidence together
The later section considers research-informed customer representations that a team can question while developing ideas. Sarah describes using survey and other customer data to make that exercise more grounded than an invented persona.
These representations can help explore reactions, but they remain a model of the audience. Use them to develop questions and alternatives, then return to customer feedback and real performance. The goal is more thoughtful creative, with the brand’s evidence and judgment still guiding the process.
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