Podcast Summary

Podcast: The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
Episode: #795: Resident Expert: Novi CEO Kimberly Shenk on How Agentic AI Changes the Buyer's Journey
Date: January 8, 2026
Host: Greg Kihlström
Guest: Kimberly Shenk, CEO and Co-founder, Novi

Overview

This episode dives deep into the revolutionary impact of agentic AI on the buyer's journey — especially in CPG and retail. Greg Kihlström interviews Kimberly Shenk, CEO of Novi, to explore how the dominance of AI-powered agents is fundamentally shifting product discovery, purchase behavior, and brand strategy. The conversation is rich with actionable insights for brands looking to stay relevant in an algorithm-driven marketplace, and offers a blueprint for marketing leaders grappling with emerging data, process, and measurement challenges in the age of AI shopping.

Key Discussion Points & Insights

1. From SEO to AEO: Redefining Product Discovery

Timestamp: 03:19–05:54

• Agentic AI is transforming the discovery process: Where once victory meant ranking high in SEO/SEM, now it means becoming the "selected" product in an AI-generated answer.
• Shift in Optimization Focus: Brands must move from optimizing for keywords to optimizing for clear, structured, and verifiable answers that AI can confidently cite.
• Data as the New Differentiator: Smaller, agile brands can now outcompete entrenched leaders if their product data is more trustworthy and consistent.

“Brands that have built this empire around SEM and SEO now have to retrain this muscle around not optimizing for keywords, optimizing for answers.”
— Kimberly Shenk, [05:13]

2. Compressing the Messy Middle: How AI Replaces Human Comparison Shopping

Timestamp: 06:55–08:36

• AI as the Ultimate Middleman: AI does in seconds what took humans dozens of website visits—comparison shopping and evaluation.
• Three Keys for Brands:
  1. Trust: Information must be verifiable and from authoritative sources
  2. Relevance: Complete product info mapped to user queries
  3. Extractability: Data must be structured for machine readability
• Outcome: If brands fail any of these, they fall out of the AI-driven consideration set.

“Your product is no longer being merchandised to humans, it's being merchandised to machines.”
— Kimberly Shenk, [07:57]

3. Data Types That Matter Most Under AI

Timestamp: 09:03–11:03

• Beyond Basic Specs:
  • Verified claims such as ingredient disclosures, certifications, efficacy, safety, or environmental impact data are now vital.
  • Consistency across retailer platforms is crucial: Variance in product claims introduces uncertainty that can cause AI models to skip your product.

“The unobvious thing is enriched claims, because that's what differentiates your product and that's what AI actually heavily relies on.”
— Kimberly Shenk, [10:50]

4. Why Keyword Chasing is the Wrong Game for AI

Timestamp: 11:03–13:56

• Answer Engine Optimization (AEO) is not SEO:
  Traditional keywords strategies are less effective, and can even harm visibility.
• AI interprets, summarizes, and personalizes answers, drawing on real understanding of data, not keyword density.
• Brands must focus on structuring authoritative product data, not optimizing for specific prompts or keywords.

“No, focusing on keywords is not the right approach. It actually can hurt your AI visibility.”
— Kimberly Shenk, [11:45]

“The success is being trusted enough by AI to be represented in the answer based on whoever is asking.”
— Kimberly Shenk, [13:21]

5. How Marketing Teams, Tech, and Processes Must Adapt

Timestamp: 15:31–18:13

• Shift to 'Marketing to Machines': Content must become more structured, scannable, and verifiable beyond just appealing to humans.
• Cross-functional Alignment: Marketing, R&D, and digital teams must collaborate closely to generate complete, structured data sets.
• Budget Realignment: Smart teams are reallocating SEO/SEM budgets to AEO initiatives, not treating AEO as a mere add-on.

“Finding folks that are really inept at that and treating data is a core advantage... instead of thinking of AEO as incremental budget, they're actually reallocating budget.”
— Kimberly Shenk, [16:48]

6. Measuring Success in the AI-Driven World: New Metrics & KPIs

Timestamp: 18:39–22:38

• Three Measurement Phases:
  1. Readiness — Is data consistent and structured for AI? Site audits, consistency scores.
  2. Momentum — Are products surfacing in AI answers? Share of voice.
  3. Visibility Consistency — Is your product cited reliably over time?
• Attribution Without Clicks:
  ROI can be shown through increases in branded search, direct traffic, and direct referral traffic from AI answers/citations.

“Share of voice is still really important. But then traffic is really the measurement of ROI and attribution today.”
— Kimberly Shenk, [22:25]

7. Holiday Insights: The AI Category Manager Emerges

Timestamp: 23:02–24:16

• AI as Consumer’s Preferred Curator:
  Consumers turned to ChatGPT and similar tools for holiday curation, price/availability checks, and even cart-building.
• Brands and retailers may be caught flat-footed as consumer trust and decision-making shift from retailer curation to AI recommendations.

“AI becoming this category manager, if you will... now the consumer is shifting their trust to AI.”
— Kimberly Shenk, [23:37]

8. AI’s Role in Loyalty and the Direct Brand-Consumer Relationship

Timestamp: 24:42–26:02

• Loyalty Loops Are Being Redefined:
  Legacy loyalty from advertising/programs may be outpaced by AI-mediated, trust-based loyalty—where brands chosen consistently by AI are “locked in.”
• AI can foster deeper brand recall and repeat purchase by repeatedly surfacing consistent, trusted products.

“Loyalty is built in—AI is built on trust and transparency. It's not based on legacy brand equity. The real opportunity is making sure that AI remembers.”
— Kimberly Shenk, [25:19]

9. Looking Ahead: The Rise of Agentic Commerce

Timestamp: 26:14–27:05

• Prediction:
  AI agents will soon handle research, comparison, selection, and transaction—effectively shopping on behalf of consumers end to end.
• Key takeaways:
  Data clarity and machine readability will only grow in importance as agents take over more steps.

“Shopping agents won't just recommend the products, they'll do the full end to end research, compare, decide and then transact on behalf of the customer.”
— Kimberly Shenk, [26:25]

Notable Quotes & Memorable Moments

• “Brands that have built this empire around SEM and SEO now have to retrain this muscle around not optimizing for keywords, optimizing for answers.”
  [05:13], Kimberly Shenk

• “Your product is no longer being merchandised to humans, it's being merchandised to machines.”
  [07:57], Kimberly Shenk

• “No, focusing on keywords is not the right approach. It actually can hurt your AI visibility.”
  [11:45], Kimberly Shenk

• “AI becoming this category manager, if you will... now the consumer is shifting their trust to AI.”
  [23:37], Kimberly Shenk

• “Loyalty is built in—AI is built on trust and transparency. It's not based on legacy brand equity. The real opportunity is making sure that AI remembers.”
  [25:19], Kimberly Shenk

• “Shopping agents won't just recommend the products, they'll do the full end to end research, compare, decide and then transact on behalf of the customer.”
  [26:25], Kimberly Shenk

Conclusion

This episode offers a playbook for brands navigating the shift from traditional digital marketing to an AI- and agent-driven commerce world. By focusing on data clarity, cross-functional collaboration, rethinking measurement, and quickly reallocating marketing resources, brands can earn durable visibility and trust—not just from consumers, but from the AI agents that increasingly mediate their choices. Kimberly Shenk’s practical advice, strategic frameworks, and forward-looking predictions make this a must-listen for anyone shaping tomorrow’s brand strategies.

For more information about Novi and AI-driven brand infrastructure, visit noviconnect.com.