6 Cross-Selling Tips & Techniques to Boost Sales

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Each day, Amazon makes millions of highly personalized product recommendations based on what customers are viewing at that very moment. You’ve probably seen these suggestions under titles like “Frequently bought together” and “Customers who bought this item also bought.” Amazon’s strategy is a shining example of what makes cross-selling effective: it’s based on your customers’ proven preferences.

Cross-selling taps into an existing customer’s potential by suggesting products and services related to previous purchases. Since there’s a 70% chance of selling to existing customers, compared to only 20% with new customers, cross-selling is a prime opportunity to increase revenue. 

Here are seven cross-selling tips to help you drive sales and cultivate customer loyalty.

6 cross-selling tips & techniques

Although a cross-selling strategy ultimately aims to increase your bottom line, a subtle approach is far more effective than just another sales pitch. The most important thing is to ensure that your suggested add-ons are relevant to your customers; otherwise, you will add unnecessary friction to the shopping experience.

1. Track customer purchasing behavior

Cross-selling techniques are more likely to convert customers because these recommendations are based on products that they already bought or showed an interest in. Analyzing your customers’ preferences and prior purchases helps you make offers and recommendations that match that interest.

To understand the full scope of a customer’s purchasing behavior, you need to track their buying patterns across channels (email, website, app) and devices (desktop and mobile). This customer data will help you answer questions like:

• What products are often sold together?

• What products do people look at while considering a purchase?

• What products do people come back for after their previous purchase?

• When do customers add products to their carts during the customer journey?

Once you have a good grasp of your customers’ preferences, you can make customized product recommendations that arrive at the right time in the customer journey.

2. Divide existing customers into segments and map out relevant product recommendations

Customer segmentation enables you to identify groups with similar buying patterns so that you can suggest complementary items.

There are many different models for customer segmentation, but some will be more effective depending on your brand and industry. For example, value-based segmentation helps you identify which audience segment has the potential to yield the greatest return on investment. Choosing the right approach to customer segmentation has considerable benefits: DigitalOcean saw a 33% improvement in cost per conversion by using hyper-targeted messaging based on their customer segments.

3. Use auto-triggered messages to pitch at the perfect time

Automated follow-up messages can act as a gentle nudge for customers, encouraging them to keep engaging with your brand.

The best time to suggest complementary products is after a customer has clearly indicated they want to make a purchase. This could look like adding an item to their cart or browsing additional items on your website. Once you’ve identified the best cross-selling opportunities in the customer journey, you can set up marketing automation workflows based on these actions.

For example, every time someone adds an item to their cart, it can trigger an automated popup message that suggests similar items. With a conversion rate of nearly 6% on mobile, popups are a highly effective way to engage already interested customers. Cart abandonment emails are another great way to recommend additional products based on customers' behavior and interests.

4. Limit the number of messages and products you pitch

Although cross-selling seems like an easy way to sell more products, you can easily overwhelm customers with too many suggestions. This could even create a negative experience and deter customers from buying from you at all.

Instead of suggesting a huge list of complementary products every time, limit yourself to three or four recommendations that are personalized for that customer segment. You can share these suggestions:

• On the product page

• In a cart drawer message after a customer adds an item to their cart

• At checkout

• In a post-purchase email drip campaign

This ensures that your cross-selling efforts reach customers who are more likely to convert.

5. Demonstrate a use case for the product you’re pitching in tandem with the original purchase

Even if a product recommendation targets the right customer, they still might not be convinced. Use cases and demos help convince customers of the value of an additional purchase.

Say a customer has added a blow dryer to their shopping cart. You could simply suggest related products like a round brush and a styling mousse. But a video of how to use these products together would clearly illustrate the value of purchasing all three items.

6. Make the offers available for a limited time

A limited-time offer creates a sense of urgency that incentivizes your customers to buy more products so they don’t miss out. One example of a limited cross-selling offer is a temporary discount. If a customer adds sunscreen to their cart, you can give them a discount on a sunhat that expires in a few hours.

Adding a countdown to your promotional messages is another way to create that sense of urgency for your customers. Other limited-time sales techniques include:

• Daily deals

• “Last chance” promotions for returning customers

• Clearance sales

• “While supplies last” discounts

Why customer data is the key to successful cross-selling

To personalize cross-selling, you need to properly track customer data and analyze it with the right tools. Your customer data provides unparalleled insight into your customers’ needs, challenges, and buying preferences.

Imagine that you’re a salesperson behind a brick wall who can’t interact with customers. That’s what happens when you implement a cross-selling strategy without using customer data. If all you know is the item someone wants to purchase – nothing about their demographics, previous purchases, or behavior – it’s difficult to make personalized recommendations.