Costco Leads Canada Grocery—AI Lessons for Retailers

Costco just ranked as Canada’s top grocery retailer for the second straight year in dunnhumby’s Retail Preference Index—an index that evaluates the $115B Canadian grocery market across 28 major banners representing 97% of market share. That’s not a “nice brand moment.” It’s a signal.

Canadian shoppers are still in savings mode. Even with inflation and interest rates easing, affordability is the daily filter Canadians apply to every basket decision. When value becomes the main storyline, retailers don’t win by being louder. They win by being more precise: tighter availability, fewer pricing surprises, faster fulfillment, and smarter targeting.

This post is part of our AI in Retail and E-Commerce series, where we look at how retailers (including many in Ireland) are using AI for customer behavior analysis, recommendations, pricing, and omnichannel execution. Costco’s position in Canada gives us a practical springboard: what does “winning on value” look like when AI is part of the operating system?

What Costco’s Canada ranking really tells you about shoppers

Costco’s #1 spot is about trust and consistency, not just low prices. The dunnhumby results also put Maxi, Food Basics, and Real Canadian Superstore in the next tier—banners that consumers associate with savings and predictable value.

Here’s the blunt takeaway: “Value” is now a product feature. It has to be delivered reliably across shelf, app, pickup, and returns.

Value isn’t a promotion strategy anymore—it’s a systems problem

When shoppers are anxious about budgets, they punish friction:

• Out-of-stocks on staples
• Price jumps between channels
• Substitutions that don’t make sense
• Couponing that feels like a scavenger hunt
• Loyalty offers that ignore what they actually buy

That’s why value-forward retailers keep rising. They’re not perfect, but they’re usually more consistent.

The omnichannel angle people miss

Costco is still strongly warehouse-led, but customer expectations aren’t. Even “store-first” shoppers now behave omnichannel: they check inventory online, compare basket totals, look for pickup windows, and scan social proof before trying new items.

Ranking #1 in grocery preference is increasingly an omnichannel achievement, even if the retailer’s identity is physical.

The AI playbook behind “value you can feel”

AI doesn’t create value by itself. It helps retailers stop leaking value through forecasting errors, waste, poor targeting, and inconsistent service. If you’re trying to compete with Costco—or defend against a value player entering your category—these are the AI capabilities that matter.

1) AI-driven demand forecasting that’s sensitive to real life

The biggest forecasting mistake grocers make is treating demand as a smooth curve. It isn’t. It’s shaped by:

• Weather shifts
• Local events
• Pay cycles
• Viral recipes
• Supply constraints
• Competitor promotions

Modern retail AI forecasting models can ingest these signals and adjust faster than spreadsheet-driven planning.

Why this matters for value: The cheapest item is the one you can actually keep in stock without over-ordering and throwing it away.

Practical applications retailers can implement within a quarter:

• Store-level forecasts for top 500 SKUs (start with staples)
• Automated alerts when predicted demand deviates from plan
• Vendor order recommendations with human approval

2) Inventory intelligence that reduces out-of-stocks and waste

Shoppers don’t separate “inventory accuracy” from “value.” They just know whether they got the item they came for.

AI helps by combining:

• POS and loyalty data
• On-hand inventory
• Lead times and supplier reliability
• Shrink and spoilage patterns

That blend enables probabilistic inventory: not “we think we have 12,” but “we have an 86% chance of having at least 8 available through Saturday afternoon.” That’s the sort of confidence you need to make pickup promises and reduce substitutions.

3) Personalization that respects the value shopper

A lot of personalization in grocery is… noisy. Shoppers get offers for items they bought once six months ago, or premium upgrades when they’re clearly trading down.

Personalization works when it’s rooted in customer behavior analysis rather than generic segmentation.

What strong AI personalization looks like:

• Recognizing “pantry loader” vs “fresh top-up” trips
• Detecting price sensitivity by category (someone can be budget-driven in cereal but premium in coffee)
• Tailoring offers to household routines (weekend bulk, weekday convenience)

Opinion: retailers should stop treating personalization as a marketing trick. It should be a margin-and-trust tool. If customers feel understood, they come back. If they feel manipulated, they churn.

4) Smarter promotions that protect margins (even in a price fight)

Most companies get this wrong: they discount without knowing who needed the discount to buy.

AI-powered promotion optimization aims to answer:

• Which customers require an incentive to switch?
• Which would have purchased anyway?
• What’s the cross-basket effect (does discounting pasta pull sauce and cheese)?

Instead of “10% off for everyone,” you can run:

• Targeted offers for switchers
• Basket-building promotions for specific missions
• Time-bound deals that reduce end-of-day waste in perishables

That’s how you compete with value leaders without training shoppers to wait for markdowns.

Warehouse-to-omnichannel: where Costco-like retailers can push next

Costco’s ranking is proof that shoppers reward clear value. The next battlefield is how well that value is delivered across digital touchpoints.

Click-and-collect and last-mile aren’t just logistics—they’re perception

When pickup substitutions are random, shoppers feel like they lost control of their budget. AI helps grocers reduce that by:

• Predicting substitution acceptability (brand loyalty, dietary constraints)
• Ranking substitutes by “customer happiness score,” not just availability
• Learning from past substitution approvals/returns

A simple operational rule I’ve found effective: treat substitutions like recommendations, not like replacements. That mindset shift is where AI earns its keep.

Search and discovery are the hidden profit engines in grocery e-commerce

On most grocery sites, search results are still too literal. If shoppers type “school snacks,” they don’t want a list of random snack SKUs. They want solutions.

Retail AI can improve:

• Semantic search (“quick dinner,” “gluten-free,” “under $20”)
• Personalized ranking (put the customer’s usual milk brand first)
• Bundled suggestions (taco night basket, holiday baking kit)

During December, this matters even more because baskets get larger and substitutions are more common. A better digital experience reduces customer service costs and increases basket size without feeling pushy.

What retailers in Ireland can learn from Canada’s value race

Our series focuses on AI in Retail and E-Commerce in Ireland, but the Canadian grocery story translates well. Irish retailers are dealing with many of the same pressures: price sensitivity, channel switching, and higher expectations for availability.

Here are three practical moves that work regardless of market size:

1) Build a “value truth” dashboard

If value is your brand promise, measure it like one. Combine:

• Price index vs key competitors (by basket, not single SKUs)
• On-shelf availability for high-frequency items
• Substitution rate and substitution satisfaction
• Delivery/pickup promise accuracy

AI is useful here because it turns messy operational data into a weekly narrative you can act on.

2) Start personalization with “next best help,” not “next best product”

Retailers jump straight to recommendations. I’d start with help:

• Remind me when staples run low
• Suggest cheaper equivalents when budgets tighten
• Build a basket from last week in one tap

That’s how you earn permission to recommend higher-margin items later.

3) Treat forecasting as a customer experience function

Forecasting sits in supply chain, but customers experience it as:

• “They always have what I need”
• “They waste less and keep prices stable”
• “Pickup doesn’t mess up my plan”

Put the forecasting team in the same room as e-commerce and store ops at least once a month. AI projects fail when they’re owned by one department.

People also ask: does AI help grocery retailers compete with Costco?

Yes—if you use AI to improve consistency rather than chase flashy features.

• Competing on price alone is a trap. Costco’s model supports price strength through scale and membership economics.
• Competing on precision is realistic. Many retailers can beat Costco on local assortment, convenience, and speed.
• AI supports precision. Better demand planning, fewer substitutions, smarter offers, and more relevant digital journeys.

A line I come back to: “Value is what the customer remembers after the trip.” AI helps shape that memory.

Your next 90 days: a focused AI roadmap for grocery and omnichannel

If you want results quickly (and you’re tired of vague AI talk), run a 90-day plan around three outcomes:

1. Reduce out-of-stocks on top staples (forecasting + replenishment recommendations)
2. Improve pickup quality (substitution intelligence + inventory confidence)
3. Increase loyalty engagement (behavior-based offers, not blanket discounts)

Define success metrics upfront: out-of-stock rate, substitution acceptance, NPS for pickup, promo ROI, and repeat digital orders.

Costco’s Canada ranking is a reminder that shoppers reward retailers who keep their promises. AI doesn’t replace good retail fundamentals—it scales them.

If you’re building your own AI in retail and e-commerce roadmap, where are you seeing the biggest “value leaks” right now: availability, substitutions, pricing, or personalization?