How can I create suggestions for complementary products for my customers?

Suggestions for complementary products are a powerful lever for increasing the average basket, while improving the shopping experience. By anticipating customers' needs, they make it possible to suggest relevant items and thus encourage cross-selling.

In this article, we look at how to identify and implement effective recommendations to boost your sales.

Why offer complementary products?

The advantages are many:

Increased average basket: offering accessories or related products encourages customers to buy more.
Improved customer experience: you guide buyers to useful products, often linked to their initial purchase.
Conversion rate optimization: a well-placed suggestion can speed up the purchasing decision.
Loyalty: a smooth, personalized experience keeps customers coming back for more.

Identify the right products to combine

Before deploying a referral strategy, it's essential to choose which products will be offered together.

Common types of complementary products :

Accessory products

Example: offer a case or headphones when a customer buys a smartphone.

Consumables

Example: offer ink cartridges when a customer buys a printer.

Products in the same range

Example: suggest pants to match a jacket for a complete look.

Products frequently purchased together

Example: display a combined offer for a laptop and a wireless mouse.

Customized packages and bundles

Example: create a "complete office" package with ergonomic chair and additional screen.

Implement an effective cross-selling strategy

1. Use data and algorithms

Analysis of purchasing behavior enables us to create relevant recommendations:

Study sales history to identify the most frequent associations.
Use AI-type algorithms to detect patterns that cannot be detected manually.
Manually define certain rules for products that are highly complementary (e.g. must-have accessories).

To find out more about intelligent automation, see How AI can simplify my product catalog management.

2. Choose the right places to display recommendations

Suggestions should be visible but not intrusive. Here are a few examples:

Product pages: carousel under the main product.
Shopping cart: before checkout.
Home page: recommendations based on history or trends.
Post-purchase emails: associated products to extend the post-purchase experience.

3. Regular testing and optimization

Each audience reacts differently to suggestions. It is essential to :

Run A/B tests on different types of recommendations.
Track key indicators such as click-through rate, suggestion conversion rate and impact on average basket.
Adjust suggested products according to observed performance.

Inspiring examples

Amazon : famous for its "Customers who bought this item also bought", based on the analysis of cross-purchase histories.

Sephora : adapts its suggestions to customers' beauty routines according to their previous purchases.

Decathlon : offers customized packs depending on the sporting activity chosen.

Conclusion

Suggestions for complementary products are an essential lever for developing your sales and improving the customer experience. By combining purchase data, behavioral analysis and well-integrated recommendations, you can optimize your cross-selling strategy and maximize your sales.