The most valuable loyalty program isn’t a points card—it’s a living system that knows each shopper, adapts in real time, and proves it can drive incremental spend. We sit down with Jeff Baskin, Chief Revenue Officer at Eagle Eye, to unpack how unified commerce and true one-to-one personalization are reshaping grocery, convenience, and hospitality. Instead of stitching tools together, Jeff explains how a single platform that connects payments, promotions, loyalty, and engagement unlocks a complete customer view and makes every interaction feel relevant across channels.

Jeff pulls back the curtain on two standout case studies. Giant Eagle combined loyalty with digital promotions to generate hundreds of millions in incremental sales by influencing the next purchase, not just rewarding the last. Tesco’s AI challenges push personalization further: models weigh 190+ decisions per shopper to assign tailored goals and rewards, scaling from 3 million to 10 million customers quickly while guaranteeing measurable uplift. These programs win CPG support because they tie spend to clear ROI, not vague impressions, and they help retailers grow margin by moving shoppers into higher-value behaviors.

We also get practical about the messy middle: data silos, legacy POS programs, and organizational friction. Jeff shares why a consultative approach matters—start with customer outcomes, treat data as a strategic asset, and build a feedback loop that improves with every transaction. We compare Walmart’s tech-driven experience gains with the edge regional grocers can reclaim by pairing human connection with AI-powered relevance. The takeaway is simple: personalization works because it mirrors how people already consume content on Netflix and Instagram. When retailers deliver that level of relevance across store and digital, loyalty stops being a cost and becomes a growth engine.

Subscribe, share with a colleague who cares about loyalty, and tell us: where are your silos, and what would you test first?

Fraud doesn’t just show up as a stolen card anymore—it arrives as coordinated global operations and as “friendly” misuse from customers who otherwise look perfect on paper. We sit down with Arman Najarian, CMO at Sift, to unpack how merchants can block the bad without breaking the checkout flow for everyone else. From account takeovers and identity theft to policy abuse and return gaming, Armin explains why risk isn’t a back‑office metric but a core part of customer experience, where a single false positive can cost a loyal buyer and a long relationship.

We dig into how Sift evaluates identity in real time, returning a risk score in about 200 ms, and why context across a network of merchants beats one‑off signals. It takes a network to fight a network, and that shared view turns fragmented behavior into reliable trust decisions. The conversation moves to agentic commerce—AI agents that can discover, sign up, and transact on our behalf. Convenience is huge, but so are questions: how do we authenticate agents, delegate consent, assign liability, and keep fraudsters from hiding behind machine identities? With card networks, banks, processors, and solution providers racing toward standards, the stakes rise as forecasts point to a leap from billions today to over a trillion dollars in agent‑driven transactions by 2030.

We also explore why Gen Z gets phished more despite digital fluency, the practical limits of self‑sovereign identity in the private sector, and the growing dual threat: organized crime scaling up and first‑party misuse spreading inside customer bases. If you care about conversion, approval rates, and loyalty as much as chargebacks, this is a roadmap for making trust invisible when it should be, and unmistakable when it must be. If this conversation helped you see risk differently, follow, share with a colleague, and leave a quick review so more people can find the show.

If you’ve felt the creep of “good enough” in your marketing, you’re not imagining it. We dig into why plausible outputs are everywhere, how AI accelerates the trend, and what it takes to compete on strategic value when leaders only lean in for metrics tied to money. With Andrew Schulkind of Andigo, we get candid about the gap between process metrics and business metrics, the lure of “ornamentrics,” and the practical steps that reconnect campaigns to revenue, profitability, and customer outcomes.

We start where most frameworks gloss over: defining audience segments through real conversations. Not just with sales and success, but with product teams, long-term customers, and the ones who churned. Those insights expose the pains people actually feel and the outcomes they will pay to achieve. From there, we show how to use both fear and aspiration responsibly: articulate the problem that causes daytime heartburn, paint the future state buyers want, and keep your message grounded in what they value rather than what you want to sell.

Then we turn strategy into motion. You’ll hear a simple nurture cadence built around three core pains and three matching outcomes, each email carrying proof, a useful resource, and a micro-CTA that reveals intent. Track those signals, learn which messages trigger movement, and tie engagement to pipeline and revenue instead of vanity stats. We also talk frankly about when to step on implementation to protect strategic value and how to leverage AI without losing customer proximity.

If you’re ready to trade shiny metrics for meaningful results, this conversation gives you a clear path forward and tools you can use this week. Enjoy the episode, share it with a teammate who’s buried in dashboards, and if it helps you reframe your plan, subscribe and leave a review so others can find it too.

Think your customers are loyal? Our data-backed dive suggests otherwise. We sit down with Cardlytics to unpack why non-loyal shoppers often deliver outsized gains and how commerce media—powered by first-party transaction data—can transform media spend into measurable loyalty. From banks to retailers to CPGs, we trace how card-linked offers (CLO) connect incentives to outcomes and deliver immediate consumer value alongside certified incrementality.

We explore how category-level visibility changes everything. A shopper who looks loyal in your CRM might be splitting most of their wallet with competitors. With insights drawn from trillions in annual spend, Cardlytics shows how to spot those leaks, build audiences around real switching behavior, and target them with relevant, timely offers. The results are hard to ignore: higher average tickets, more repeat visits, and a proven path to iROAS that stands up to third-party validation.

Then we look forward. SKU-level targeting lets a brand drive a specific product through a specific retailer, closing the loop from exposure to receipt. Agentic buying is on the horizon, where AI shopping agents will hunt for value across channels. Cardlytics’ position—integrated with banks, merchants, and identity—acts like rails for this future, enabling offers to flow to both humans and agents in ways that are privacy-safe and performance-driven. Along the way, we dig into the unglamorous but essential work of data hygiene, merchant normalization, and building a modern tech stack that makes these outcomes possible.

If you’re rethinking loyalty, measurement, and where your next dollar of growth comes from, you’ll find practical guidance here: focus on non-loyal shoppers, pair CLO with clean identity, validate incrementality, and treat loyalty as a revenue center. Subscribe for more conversations at the edge of data, commerce media, and customer growth, and leave a review to tell us the next question you want answered.

The customer isn’t just human anymore. Agents are already learning our preferences, comparing offers, and making choices that used to hinge on emotion and brand memory. We sat down with Ben Wiener, global head at Cognizant Moment, to unpack how this rewires the entire go-to-market stack—from data foundations to creative expression—and why marketing plus IT has effectively become the business.

We dig into the real preparation work: consolidating and governing data so AI can act responsibly and effectively. Ben breaks down how organizations can fund the future by letting AI handle code cleanup, content migration, and workflow orchestration, then reinvest those savings into agent-ready experiences. We explore the move from omnichannel to omnibuyer, where humans, agentic buyers, and AI-assisted shoppers take nonlinear paths and demand different signals of value. That triggers hard questions about personalization, privacy, and compliance, especially in finance and healthcare, where trust is the currency.

What happens to preference when machines choose? We examine whether platforms, brands, or consumers will own the agent; how pay-for-preference could influence ranking; and why transparency standards will make or break adoption. Ben makes the case for brand-consistent AI personas that carry tone, empathy, and guardrails into machine-mediated interactions—like a great salesperson who’s consistent yet adaptive. Creativity doesn’t disappear; it scales. Relevance, speed, and ethics become the competitive layers that separate resilient brands from those left behind by algorithmic selection.

If you care about data strategy, customer experience, AI governance, and the future of brand loyalty, this conversation will sharpen your roadmap. Subscribe, share with a colleague who needs to hear it, and leave a review with your take: who should own the consumer agent—platforms, brands, or users?

Forget shiny tools. The real power in customer experience comes from simple, disciplined execution that customers actually feel: reliable delivery, fast issue resolution, and clear communication. We sit down with Lee Kemp, former VP of CX at Veritiv, to unpack how a military-forged mindset translates into practical CX leadership across supply chain, sales, IT, and finance. Lee explains why technology should only amplify a solid foundation, and how asking the right “obvious” questions can reframe stubborn assumptions without triggering defensiveness.

We walk through building metrics that matter, starting with familiar signals to align executives, then tying them to operational outcomes like on-time performance, order accuracy, first-contact resolution, and proactive updates. Lee shares a playbook for change management that avoids heroics: sponsor the right projects, let stakeholders own the wins, and keep the mission visible so teams see their role in the outcome. When resistance shows up, executive sponsorship becomes the accelerant, but staying power depends on delivering growth that leadership can see and trust.

ROI often trips teams up, so we break it down to credible indirect signals: reduced churn after onboarding fixes, higher repeat order rates with better communication, lower expedite costs from reliability gains, and faster cash through cleaner processes. Show your work, quantify trends, and be honest when something misses. That integrity builds influence for the next move. If you’re building CX in a complex B2B world—or trying to defend it to a skeptical CFO—this conversation offers practical steps to simplify, measure, and lead change that sticks. Subscribe, share with your team, and leave a review with your best “measure what matters” tip.

What if doing “the right thing for this customer, right now” became the default? We sit down with Rob Walker, VP of Decisioning and Analytics at Pega, to unpack how empathy at scale, AI-driven decisioning, and strong governance can make customer engagement both more human and more effective. Rob explains why empathy isn’t charity; it’s a system for earning relevance and trust that compounds into mutual value. We dive into one-to-one decisioning that prioritizes a hierarchy of needs—solve hardship and service first, consider offers only when appropriate—and how real-time redecisioning keeps conversations useful as context shifts. The conversation gets candid on hype vs. reality: generative AI is expanding the content library needed for true personalization, even demonstrating better bedside manner in some settings. But trust requires more than sentiment; it needs policy. Rob breaks down the T‑Switch, a transparency and model-use framework that enforces explainability where stakes are high and speeds experimentation where stakes are low. Then comes the big horizon shift: customer advocacy agents. These AI agents will comparison-shop, negotiate, and handle service on our behalf, impervious to glossy ads and tuned to our preferences. That future could disintermediate brands and push competition toward price, reliability, and fit—raising the bar for authenticity and interoperability. Inside the enterprise, tools like Pega’s Customer Engagement Blueprint compress months of strategy design into hours, changing roles rather than eliminating them. Marketers and data scientists move from manual assembly to orchestration, governance, and measurement, while empathy and trust become operational standards, not slogans. If you’re ready to trade segments and batch campaigns for moment-level decisions and measurable trust, this conversation is your fast start. Subscribe, share with a teammate who needs to hear it, and tell us: what would you ask your customer advocacy agent to do first?

Curiosity got faster—and a lot more practical. We sit down with Tim Lawton of SightX and Russell Evans of ZS to unpack a partnership that blends expert humans with integrated AI to rethink how insights teams generate ideas, validate concepts, and influence big bets. No bolt-ons, no buzzwords—just a clearer path from question to decision.

We start with the reality that researchers live under a microscope, then show how automation can remove the drudgery without losing the judgment that matters. Tim explains how SightX streamlines end-to-end survey workflows, analytics, and dashboards so small teams can do more with less. Russell shares why ZS sought a partner that treats AI as the core engine, not a layer, and how the combo is helping brands compress months of work into weeks while improving the odds of success.

You’ll hear a concrete CPG case where data-driven concept generation plus rapid, integrated validation shaved time and lifted purchase intent by 29% in a human-in-the-loop process. We break down what separates pilot purgatory from real adoption: leadership “air cover,” incentives that reward experimentation, and new roles that scan the market and align tools to strategy. We also get candid about risk, governance, and where AI belongs in the stack—use it where it accelerates insight and keeps humans focused on meaning and action.

We close with a sharp take on synthetic data: explore it for low-stakes ideation, but mine real, underused signals first—reviews, long-form social, and contact center data—when the decision matters. If you’re ready to scale consumer insights, speed up concept testing, and make better calls with AI you can trust, hit play and tell us where you want to move faster next. Subscribe, share with a teammate who needs air cover, and leave a review to help others find the conversation.