Omni Talk’s Anne Mezzenga and Chris Walton sat down with Lauren Steinberg, EVP and Chief Digital Officer at Loblaw, at Groceryshop 2025 in the VusionGroup booth. Lauren shared how Canada’s largest grocer is leveraging AI across multiple dimensions—from conversational search to agentic personalization—while scaling retail media from a DSP-first approach into comprehensive in-store activation with plans to 10x their digital screen footprint.
From Great-Grandmother’s Grocery Empire to Leading Canada’s Digital Transformation
Retail runs deep in Lauren’s veins—over 100 years deep. Her great-grandmother started what became one of Canada’s largest grocers, Steinberg’s, based in Montreal. Her grandfather and his brothers built it into a multi-billion dollar business until it dissolved in the 1990s. Ironically, Loblaw—where Lauren now works—acquired about 38% of the business and still owns the Steinberg’s IP today.
Lauren’s career began building and designing websites, which evolved into managing websites and driving demand through e-commerce marketing. For the past 12-13 years at Loblaw, she’s been building and growing e-commerce businesses. Today, online grocery represents the largest share at about $2.5 billion, but her portfolio also includes online beauty, apparel, pharmacy, prescription services, and the digital platforms powering PC Optimum, Canada’s largest loyalty program.
🔑 The Strategic Venn Diagram: Digital, Retail Media, and Loyalty
Why These Three Belong Together
Lauren describes her portfolio as a strategic Venn diagram where e-commerce, retail media, and loyalty intersect by design, not organizational accident. The logic is compelling:
- E-commerce needs retail media to be profitable
- Retail media needs loyalty for data-driven targeting, precision measurement, and performance tracking
- Loyalty needs digital because digitally engaged loyalty members spend 2x more, stay 3x longer, and become significantly stickier in the ecosystem
This interconnection allows Lauren to drive meaningful value across all three areas simultaneously. She spends the least time on e-commerce now, having built strong infrastructure and leadership teams there. Most of her time focuses on retail media—partly because she hasn’t replaced the person who left two years ago when she inherited it, but also because it’s emerging, rapidly changing, and offers new challenges for someone who’s never been a salesperson.
Retail Media: Performance-Focused and DSP-First
The European Inversion
Loblaw took a different path than European retailers. While European grocers started with in-store media and gradually expanded to DSPs and third-party marketing, Loblaw did the opposite. Their first retail media move was acquiring a DSP (now called Media Isle, similar to Trade Desk) to run their business. They also implemented RMP (sponsored search on their sites), and now they’re moving aggressively into stores—where 90% of their transactions happen and customers make final purchase decisions.
Currently, Loblaw has about 1,000 screens in stores, largely on the periphery—customers see them entering and exiting but not during their shop. That’s changing dramatically. Lauren plans to more than 10x that number, moving screens to endcaps and in-aisle locations with intelligence built in. Marketers want options, and Loblaw is learning that serving everyone as a grocer who literally serves everyone creates unique challenges in prioritizing and building for diverse CPG needs.
Synchronized Multi-Sensory Experiences
One innovation Lauren highlighted: syncing in-store screens and audio together, creating cohesive multi-sensory brand experiences. These “little things” demonstrate how Loblaw thinks about differentiation without overcomplicating or chasing too many initiatives simultaneously.
Lauren’s philosophy: find what you have conviction will really work, see early indicators (in-store performs when paired with other advertisement types), find the right partners, and execute exceptionally well. No experiment is wasted.
AI Across the Personalization Stack
Four or Five Different AI Types Working Together
When asked about exciting technologies, Lauren pointed to AI—but with specificity about how they’re actually using it. Their personalization efforts combine multiple AI approaches:
- LLM for Customer Profiling: Combining behavioral and transactional customer data, using LLMs to prompt raw data and develop rich customer profiles outlining dietary preferences, lifestyle preferences, and demographic information
- Agentic AI for Merchandising: Running profiles through “merch agents” that determine product types customers would like, then tying those to actual SKUs and connecting SKUs to products in stores
- Preference Layering: Applying filters like vegetarian preferences to show appropriate product versions
- Content Generation: Automatic image generation created on-the-fly for personalized experiences
- Conversational AI for Search: With over 45% of add-to-carts happening through search on online grocery, search keeps Lauren “up at night and wakes me up in the morning excited.” Small improvements create massive impact given the volume.
Composable Infrastructure Enables Rapid Experimentation
Loblaw’s built-in-house composable technology infrastructure gives them flexibility to experiment quickly. When OpenAI announced commerce capabilities with Shopify, Lauren noted that anyone with the right infrastructure, APIs, and product feeds can build similar use cases—which Loblaw is doing, testing everything from turning recipes into carts to enabling apparel and beauty purchases through conversational interfaces.
Her team accomplishes this with just 10 people, more than half of them co-ops. The key is enablement, not massive resources. They place many bets but never go all-in before validation—they didn’t build massive CFCs before launching online grocery, and they quickly moved away from monoliths to create extensibility. When the metaverse hype cycle hit, they dipped their toes in without jumping, avoiding being left behind when interest faded.
Search: The Make-or-Break Battleground
Lauren emphasized that answer engines like ChatGPT and Perplexity are pushing toward more semantic, conversational search experiences, and more commerce will happen in those spaces. The challenge is differentiation—you’ll Google your symptoms, but you’ll still go to a doctor. Each platform has value and purpose. Loblaw’s focus is hanging tightly to their value proposition while letting others do what they do well.
With 45% online grocery market share in Canada (compared to 30-35% for their overall business), Loblaw overindexes in e-commerce. If CPGs grow in e-commerce with Loblaw, they’re growing their total business where it matters most.
The Bottom Line
Loblaw demonstrates that retail media and AI-powered personalization don’t require massive teams or resources—they require strategic thinking, composable infrastructure, and willingness to experiment without overcommitting. By integrating e-commerce, retail media, and loyalty as interconnected value drivers rather than siloed functions, Lauren is building a digital ecosystem that serves Canada’s 2,400 retail locations and millions of PC Optimum members with performance-focused solutions that connect brands to customers in meaningful, measurable ways. With 100+ years of grocery in her blood and a team of 10 (mostly co-ops) driving AI innovation, she’s proving that heritage and agility aren’t mutually exclusive.
🎧 Want to hear the full conversation? Listen via your favorite podcasting platform:
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Be careful out there,
– Chris, Anne, and the Omni Talk team
Music by hooksounds.com
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Omni Talk® is the retail blog for retailers, written by retailers. Chris Walton and Anne Mezzenga founded Omni Talk® in 2017 and have quickly turned it into one of the fastest growing blogs in retail.