Insights Unlocked Podcast Summary

Episode: From Novelty to Necessity: Smarter AI Strategies for Retail with Phillip Jackson
Host(s): Mike McDowell (UserTesting), Nathan Isaacs (UserTesting)
Guest: Phillip Jackson, Co-Founder of Future Commerce
Date: January 12, 2026
Duration: ~30 minutes

Episode Overview

This episode explores the evolving role of AI in retail, focusing on how brands can build customer experiences that genuinely resonate. Phillip Jackson, co-founder of Future Commerce, shares his bold perspectives on commerce as a facet of culture, the invisible power of AI, and why some friction is good for shoppers. The discussion covers practical AI use cases, the risks of homogeneity and superficial novelty, pain points in customer experience, and the importance of data, trust, and internal capability as differentiators in the next retail era.

Key Discussion Points & Insights

1. Future Commerce’s Mission: Commerce as Culture

[01:39] - [04:46]

• Phillip Jackson explains the origins of Future Commerce, born from his 22 years in retail and e-commerce.
• The company’s focus is to examine how commerce shapes and is shaped by culture, not simply to chase trends or the latest tech.
• Quote:

  “I believe that commerce and culture are uniquely intertwined and... it is part of our identity... worthy of unique examination.”
  — Phillip Jackson [03:25]

2. AI’s Impact in Retail: Practical, Invisible, and Human

[05:53] - [10:47]

• AI is valuable when it quietly enhances experiences, not when it’s “technology for technology’s sake.”

• Example: Taco Bell’s app integrates AI in a way that users barely notice, powering features for both customers and employees, like personalized rewards and “fan-created” menu options.

• Quote:

  “People don’t want technology for technology’s sake... what they want is a wonderful experience. They don’t care what the technology is.”
  — Phillip Jackson [08:31]

• Discussion on how food apps use AI to crowdsource popular customizations, identifying new menu ideas through customer data.

3. Where Retailers Should Invest in AI

[10:47] - [13:21]

• Most impactful uses: smarter search, better recommendations, product comparisons, inventory availability, post-purchase support.
• Many retailers fall into “box-checking”—implementing flashy AI features nobody uses, like virtual try-on.
• The real value of AI is reducing effort and powering features that actually solve customer pain points.
• Quote:

  "If it doesn't reduce effort, it's not innovation, it's decoration."
  — Phillip Jackson [12:25]

4. Trust, Friction, and the Human Element

[13:21] - [17:18]

• Too much focus on frictionless UX can backfire (e.g., higher return rates, lack of customer consideration).
• Some friction is necessary; it acts as a checkpoint of trust and gives customers time to think.
• There’s no one-size-fits-all answer: each brand must experiment, test, and tune for their customer base.
• Quote:

  "Some friction is good. Some friction causes people to think about what they're purchasing..."
  — Phillip Jackson [14:47]

5. Changing Customer Expectations: Pattern Recognition & Novelty

[17:55] - [22:29]

• Customers quickly adapt to new shopping patterns; e-commerce has grown homogenized (same layouts, same experiences), making branding less visually distinct.
• Shoppers now use AI tools (e.g., ChatGPT, Perplexity) to find coupon codes or write refund requests, reshaping how they interact with brands.
• Demand for authenticity and proof from brands (quality, credibility, reliability) is rising.
• Memorable Moment:
  Mike shares that he literally used AI to find a coupon and draft a customer refund email, exemplifying the shift Jackson observes. [22:29]

6. Personalization: Promise and Pitfalls of AI

[23:06] - [28:13]

• Current personalization is surface-level (“Hey, [name]!”) and brands are still far from true, meaningful personalization.
• AI may unintentionally increase feelings of impersonality as more site experiences are generated automatically and become easier to spot as machine-made.
• Genuine personalization ties to intent and meeting customer needs, not just using a name or offering generic experiences.
• Quote:

  “I bet you we’re a couple years away from also being able to recognize AI-generated site experiences... it's probably going to be impersonal.”
  — Phillip Jackson [27:06]

7. Differentiation in the Age of AI: Clean Data, Change Management, & Feedback Loops

[29:39] - [31:52]

• The differentiator isn’t flashy features; it’s clean, holistic data, strong organizational change management, and continuous feedback from customers.
• Tools alone won’t create a durable competitive advantage; operational design and internal capability are key.
• Quote:

  “Clean data... Real operational design is the moat.”
  — Phillip Jackson [30:00]

Notable Example:

Kith Loyalty Program [32:02]

• Kith built a loyalty program crediting all customers retroactively for lifetime purchases—a feat possible only because they maintained pristine data for 15 years.
• Quote:

  “You can only do something like that... if you have 100% clean data for the lifetime of all of your purchases.”
  — Phillip Jackson [32:25]

8. Sustainability, Platforms, & In-House Tech

[34:51] - [37:45]

• "Box-checking" for sustainability is rampant, partly because retail AI tools are so platform-dependent.
• Brands are reconsidering building tech in-house to own the customer experience and adapt to the growing demand for autonomy and sovereignty from customers.
• Quote:

  “Customers value outcomes. That's all they care about.”
  — Phillip Jackson [37:39]

Memorable Quotes & Moments

• “If it doesn't reduce effort, it's not innovation, it's decoration.”
  — Phillip Jackson [12:25]

• “Some friction is good. Some friction causes people to think about what they're purchasing...”
  — Phillip Jackson [14:47]

• “Customers are becoming more sovereign.”
  — Phillip Jackson [35:56]

• Example of users hunting for coupon codes and using AI for refunds — Mike’s real-life experience [22:29]

Key Timestamps

| Timestamp | Segment Highlight | |------------|------------------------------------------------------------------| | 01:39 | Phillip’s background & Future Commerce mission | | 05:53 | How AI powers Taco Bell’s customer and partner experiences | | 08:31 | AI’s value in being transparent (or invisible) | | 12:25 | Focus on unsexy, but powerful, use cases for AI | | 14:47 | Good friction vs. pain in customer experiences | | 17:55 | Pattern recognition & the homogenization of e-commerce | | 22:29 | AI boosting smart consumer behaviors (promo codes, refund emails)| | 27:06 | The challenge of achieving real personalization | | 29:39 | Differentiation through clean data & operational excellence | | 32:02 | Kith’s clean data loyalty program example | | 34:51 | Sustainability, box-checking, and the return of in-house tech | | 37:39 | Customers’ focus on outcomes |

Conclusion: Actionable Insights

• Prioritize real value over showy AI features: Invest in AI that solves practical problems and delights customers, not just for novelty’s sake.
• Accept and design for meaningful friction: Not all friction is bad; it can build trust and reduce negative outcomes.
• Clean data is essential: Without it, even the best AI or marketing strategies will fall flat.
• Authenticity & continuous testing: Retailers must experiment, gather direct feedback, and align experiences with customer intent and values.
• Prepare for a return to in-house tech: As platforms plateau, owning the customer experience via custom solutions can create lasting advantages.

Further Resources

• Learn more and subscribe: futurecommerce.com
• Research, reports, and newsletter: Future Commerce Newsletter (3x/week)
• Youtube channel: Future Commerce (insightful interviews and content)