Side-by-side comparison
Frequently Bought Together vs Nosto
Compare Frequently Bought Together and Nosto across pricing, features, and fit for your e-commerce stack.
Frequently Bought Together
Shopify bundle recommendations based on real purchase co-occurrence
FreemiumQuick Comparison
About
Frequently Bought Together
Frequently Bought Together by Revy Apps is one of the most widely installed product recommendation apps in the Shopify App Store. It adds a single widget to product pages showing products that are commonly purchased together by previous customers, derived from actual purchase co-occurrence data rather than manual curation. The bundle can include a combined discount to incentivise the multi-item purchase. For stores with complementary product ranges, the lift in average order value is often measurable within the first week of installation. The app does not require data science setup or a training period in the way enterprise recommendation engines do, because the algorithm only needs a sufficient volume of historical orders to surface meaningful combinations. The trade-off is simplicity: it covers product page bundles well but does not personalise the homepage, cart page, or search results.
Nosto
Nosto specialises in the kind of on-site personalisation that Amazon uses to drive a significant share of its revenue: showing each shopper the products most likely to be relevant to them based on their browsing history, purchase history, and similar customer profiles. This applies to homepage product carousels, category page rankings, search result ordering, and email recommendations. For Shopify brands with broad catalogues, personalisation can meaningfully lift average order value and session depth. The trade-off is implementation complexity. Getting Nosto to learn effectively requires a sufficient volume of sessions and purchases to build meaningful behavioural models, which means it is less impactful for early-stage stores still building traffic. At significant catalogue depth and traffic volume, the automated personalisation often outperforms manually curated product recommendations.
Key Features
Frequently Bought Together
Bundle Recommendation Widget
Displays a frequently bought together section on product pages based on real purchase data. Customers can select which bundle items to include before adding the combination to cart.
Bundle Discount
Apply an automatic discount when a customer purchases the bundle versus individual items. Configurable as a percentage or fixed amount to incentivise the combined purchase.
Automatic Product Matching
Uses order history to calculate which products are most commonly purchased together per SKU. No manual rule configuration required to populate the bundle widget.
Revenue Impact Tracking
Tracks orders and revenue generated through the bundle widget. Shows the contribution of the recommendation feature to total store revenue over configurable date ranges.
Nosto
Behavioural Product Recommendations
Learns from individual browsing and purchase history to serve personalised product recommendations on every page visit. Models update continuously as new data arrives.
Personalised Search
Reranks search results based on the individual shopper's profile rather than a single static relevance algorithm. Products that match their purchasing pattern rank higher.
Email Personalisation
Inserts personalised product recommendations into email campaigns and automation flows. Each recipient sees different products based on their behaviour rather than a static editorial selection.
Personalisation Revenue Attribution
Tracks revenue generated by personalised recommendations versus standard experiences. A/B testing mode measures the uplift from personalisation rather than assuming it.
Screenshots
Frequently Bought Together
Nosto
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