Frequently Bought Together Strategy for Online Grocery Stores

The concept of frequently bought together is one of the most powerful tactics in ecommerce. Originally popularized by Amazon through its ”frequently bought together” feature, this simple recommendation technique has reshaped how consumers shop online.

In grocery e-commerce, where baskets are naturally larger and products are highly complementary, “frequently bought together” strategies can significantly increase basket value, improve customer experience, and drive loyalty.

In this article, we’ll explore what frequently bought together means in the grocery sector, why it matters, and how retailers can implement effective recommendation strategies to stay competitive.

What does “Frequently Bought Together” mean in grocery e-commerce?

At its core, the frequently bought together feature suggests products that are often purchased in the same transaction. Examples include:

• Pasta and tomato sauce
• Milk and cereal
• Coffee and filters
• Chips and dip
• Tortillas, cheese, and salsa

On digital storefronts, this often appears as “customers who bought this item also bought” or “customers also bought,” giving shoppers convenient, complementary options.

Research shows that frequently purchased together recommendations are more than upselling. They reflect natural shopping behavior, saving time and increasing spending.

For example, a study by Barilliance found that product recommendations account for up to 31% of e-commerce revenues.

Why product recommendations matter for grocery stores

For grocers, product recommendations are more than a nice-to-have. They are essential for:

• Increasing basket size through logical pairings.
• Improving customer satisfaction by reducing missed items.
• Driving repeat purchase rates with smarter suggestions.

According to McKinsey, personalized product recommendations can drive 20–30% of total e-commerce revenue. In grocery specifically, where shopping is frequent and repetitive, this effect compounds over time.

By integrating personalized product recommendations, grocery retailers ensure that every customer sees items that are relevant to their lifestyle—whether that’s dietary restrictions, family size, or shopping frequency.

The 5 strategies for “Frequently Bought Together” in grocery

1. Data-driven bundling strategy

Instead of guessing what works, analyze historical sales data to identify the most common pairings. AI-powered product recommendation software can reveal hidden correlations that human merchandisers might miss.

Example: linking cooking oil with flour because they often appear together in baking purchases.

2. Personalization strategy

Generic bundles risk irrelevance. A personalization-first approach adapts recommendations to the shopper’s profile.

Example: bundling gluten-free pasta with gluten-free bread for celiac shoppers, or suggesting multipacks of snacks for families with children.

3. Seasonality & campaign strategy

Successful grocers rotate their frequently bought together bundles around seasons, holidays, and events.

Example: BBQ kits in July, Halloween candy assortments in October, Christmas baking packs in December.

This strategy makes recommendations feel fresh and timely, boosting click-through rates.

4. Cross-channel placement strategy

Where recommendations appear is as important as what they suggest. An effective frequently bought together strategy places suggestions across the customer journey:

• Product detail pages (encourage add-ons early)
• Mini-cart and cart (increase attach rates before checkout)
• Checkout page (last-minute upsells)
• Even outside the site, through email or push notifications

5. Operational alignment strategy

A grocery-specific challenge is ensuring recommendations are fulfillable. This strategy integrates frequently bought together with inventory and substitution rules.

• Example: if strawberries are out of stock, the system automatically suggests blueberries.
• By tying recommendations to live stock data, grocers avoid customer frustration and reduce abandoned carts.

Case example: Grocery adoption vs Amazon

Amazon’s ”frequently bought together” feature is designed for general retail: laptops with cases, cameras with memory cards.

In grocery, the stakes are different. Recommendations must consider freshness, expiration dates, and substitution rules. For example, if strawberries are out of stock, the system should suggest blueberries instead, not unrelated items.

Industry reports show that grocery chains experimenting with smarter frequently bought together logic see higher customer satisfaction scores and reduced cart abandonment. This shows the importance of tailoring the model specifically for food retail, not just copying Amazon’s retail playbook.

Best practices to enhance your strategy

To maximize impact, grocers should layer these five strategies with broader merchandising practices:

• Personalization: Tailor offers to shopper needs.
• Seasonality: Promote bundles that align with seasonal demand.
• Local relevance: Suggest items based on regional preferences and culture.

When implemented together, the result is a recommendation engine that feels relevant, dynamic, and aligned with operations.

Technology behind product recommendation software in grocery

Not all recommendation engines are created equal. Basic systems suggest “recommended products” or highlight “related items,” but advanced product recommendation software uses AI and machine learning to:

• Analyze browsing and buying behavior
• Factor in seasonality and regional trends
• Adjust dynamically based on live inventory

More generic platforms, like Shopify, provide “related products” functionality out of the box, and plugins such as “shopify frequently bought together” replicate Amazon-style bundling. While these can work for general retail, grocery presents unique challenges: short shelf life, substitutions, variable basket sizes, and the need for precise fulfillment. These are areas where generic platforms fall short.

This is exactly where Wave Grocery makes the difference. As a platform built specifically for online grocery, it embeds recommendation logic into every layer of operations, from storefront personalization to picking and delivery.

Unlike Shopify or other general-purpose ecommerce platforms, Wave Grocery ensures that recommendations are not only relevant to the shopper, but also fulfillable in real time, based on inventory, substitutions, and regional product availability.

By choosing a dedicated grocery platform, retailers avoid the compromises of adapting generic tools and instead gain recommendation strategies that align with the complexity of food retail.

Conclusion

The frequently bought together strategy is more than an upsell widget. In grocery, it is a framework of five strategies: data-driven bundling, personalization, seasonality, cross-channel placement, and operational alignment. Together, they transform recommendations into a growth engine for basket size, loyalty, and efficiency.

Ready to see how this works in practice?

Talk with our customer success manager to explore how Wave Grocery powers smarter, grocery-specific recommendation strategies.