Product Recommendations: 4 Workable Strategies
By showing product recommendations to customers, businesses can encourage them to make additional purchases and increase their overall order value. This article will tell you what strategies will help you to achieve that and how to upsell.
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Product recommendations are a feature of ecommerce websites and online stores that suggest additional products to customers based on their browsing and purchase history. These recommendations are generated using algorithms that analyze customer data, such as purchase history, items left in their cart, and products they have viewed or clicked on.
Product recommendations can take several forms:
Recently viewed products
Frequently bought together
These are items that are related to the product the customer is currently viewing or has added to their cart. For example, if a customer looks at a laptop, related products may include a laptop, accessories, or software.
These are products that the customer has recently viewed but not necessarily added to their cart or purchased.
These are products that are frequently bought together with the product the customer is viewing or has been added to their cart. For example, if a customer buys a camera, frequently bought together items may include a memory card or carrying case.
These are products that the ecommerce platform suggests based on the customer's browsing purchase history.
Product recommendations and suggestions work by analyzing a customer's behavior and data to suggest other products that may interest them. Here's a general overview of how product suggestions work:
- Collect data: the ecommerce platform collects data on the customer's browsing and purchase history. This can include items viewed, items added to the cart, items purchased, and even items searched for on the website.
- Analyze data: algorithms identify patterns and make connections between different products. This helps the platform to understand what products the customer is interested in and what they are likely to purchase.
- Generate product recommendations: based on the analysis of the customer's behavior, the ecommerce platform generates product recommendations in real-time. These recommendations can take different forms, such as related products, frequently bought together items, recently viewed items, and recommended products.
- Display recommended product: the ecommerce platform displays the product recommendations to the customer in various ways, such as on the product page, in the shopping cart, or an email.
- Update recommendations: The platform collects data and updates product recommendations in real-time as customers browse and purchase products.
Product suggestions use data analysis to understand customer behavior and provide personalized product recommendations. To achieve maximum profit for your business, remember to use Upselling Techniques.
1. Product Recommendation Examples by Page Context
Here are some examples of how to use product recommendations on different pages of your ecommerce site:
- Homepage: you can use product recommendations to showcase your best-selling products or new arrivals on the homepage. Based on the customer's browsing history, this can be done using a "featured products" section or a "recommended product for you" section.
- Product pages: use product recommendations to suggest related products or complementary items on product pages. For example, if a customer sees a pair of shoes, you can recommend matching socks or a shoe care kit.
- Cart page: suggest complementary items or upsell them on the cart page. For example, if a customer has added a shirt to their cart, you can recommend matching pants or a jacket.
- Search results page: on the search results page, you can use product recommendations to suggest similar or related products that the customer may be interested in. This can increase the likelihood of the customer finding what they are looking for and purchasing.
- Category pages: on category pages, you can use product recommendations to suggest popular or best-selling items within that category. This helps guide the customer towards products that are likely to interest them.
- Thank you page: on the thank you page, you can use product recommendations to suggest similar or complementary items to the customer's recent purchase. This can encourage repeat purchases and increase customer loyalty.
2. Product Recommendations Examples by Audience
- New Customers: for new customers, you can use product recommendations to showcase your most popular or best-selling items or products frequently bought together. This can introduce them to your brand and increase the likelihood of a purchase.
- Returning Customers: You can use product recommendations based on their past purchase history to suggest similar or complementary items. This can encourage repeat purchases and increase customer loyalty.
- High-Value Customers: for high-value customers, you can suggest premium or exclusive products tailored to their interests or preferences. This can help to increase their lifetime value and build a stronger relationship with your brand.
- Abandoned Cart Customers: for customers who have abandoned their cart, you can suggest similar or complementary items to encourage them to complete their purchase. This can help to recover lost sales and increase conversions.
- Browsing Customers: for customers browsing your site without making a purchase, you can use product recommendations to suggest items based on their browsing history. This can increase engagement and encourage them to make a purchase.
- Social Media Followers: for customers who follow your brand on social media, you can suggest items that align with their interests or preferences. This can help to build a stronger relationship with your followers and increase the chance of them making a purchase.
3. Product Recommendations Examples by Seasonality
- Winter Season: use product recommendations to suggest items such as winter coats, hats, gloves, scarves, boots, and other cold-weather gear. For example, if a customer is browsing for winter coats, you can recommend matching hats and gloves to complete the outfit.
- Spring Season: offer lightweight jackets, raincoats, umbrellas, rain boots, and gardening tools. For example, if a customer is browsing for gardening tools, you can recommend a raincoat to protect them from the rain.
- Summer Season: suggest items such as swimwear, sunglasses, beach towels, sunscreen, and outdoor games. For example, if a customer is browsing for swimwear, you can recommend matching sunglasses and a beach towel.
- Fall Season: use product recommendations to suggest items such as sweaters, boots, scarves, hats, and pumpkin-related products. For example, if a customer is browsing for sweaters, you can recommend matching scarves and hats.
- Holidays: during holidays such as Christmas, Valentine's Day, and Mother's Day, suggest gift ideas for the occasion. For example, if a customer is browsing for Christmas gifts, you can recommend gift sets, ornaments, and other holiday-themed products.
Using Claspo popups for product recommendations on your website, you can offer your customers a more relevant and timely shopping experience. This can help to increase engagement, boost sales, and build customer loyalty.
4. Product Recommendations Examples by Trending Products:
- Popular Products: showcase your most popular products based on customer reviews, ratings, and sales data. This can help build customer trust and credibility and increase the likelihood of a purchase.
- Seasonal Products: recommend popular products during specific times of the year, such as holiday-themed products or products related to popular events such as the Super Bowl.
- Social Media Trends: use social media trends to recommend products currently popular on platforms such as Instagram or TikTok. For example, if there is a popular fashion trend on Instagram, recommend products that fit with that trend.
- Influencer Recommendations: collaborate with influencers to recommend products to their followers. This can increase brand awareness and drive sales.
- New Releases: recommend products that are new to the market and generate buzz. This can create excitement around your brand and increase the likelihood of a purchase.
The recommended product can also be based on the following:
- Personalization: product recommendations can be personalized based on a customer's browsing and purchase history, search queries, demographics, location, and other factors. By using personalized recommendations, you can offer a more tailored and relevant shopping experience for each customer.
- Upselling/Cross-selling: suggest complementary or higher-priced items to the customer. This can increase the average order value and boost revenue.
- Best-Selling Products: product recommendations can be based on your best-selling or top-rated products. By showcasing your most popular items, you can build trust and credibility with the customer and improve the chances of the purchase to occur.
How do popular brands use the recommended product on their websites? Let’s look at product recommendation examples!
- Amazon uses product recommendations based on customer browsing and purchase history to suggest similar or complementary products. They also use the "Frequently bought together" and "Customers who bought this item also bought" sections to offer more product options to customers.
- Netflix suggests TV shows and movies based on a customer's viewing history and ratings. They also offer personalized recommendations based on trending titles and popular genres.
- Sephora’s product recommendations are based on a customer's purchase history and personal preferences to suggest makeup and skincare products that are tailored to their needs. They also offer product bundles and kits to encourage customers to try new products.
- Spotify suggests music and podcasts based on a customer's listening history and interests. They also offer personalized playlists based on mood, activity, and genre preferences.
- Walmart suggests similar or complementary products based on customer browsing and purchasing history. They also offer "Recommended for you" and "You may also like" sections to recommend products that meet the customer's needs.
Here are some more tips for how to use product recommendations on your ecommerce site:
- Place recommended products prominently: ensure product recommendations are displayed on your website. This can be done by placing them on the homepage, product pages, and in the shopping cart.
- To personalize the product recommendations, use data from the customer's browsing and purchase history. This will help make the recommendations more relevant and increase the likelihood of the customer purchasing.
- Test different recommendation types: experiment with different product recommendations such as related products, frequently bought together items and recently viewed items. Test which types of recommendations work best for your audience and adjust your strategy accordingly.
- Segment your audience: segment your audience based on demographics, interests, or past purchases, and create personalized recommendations for each segment. This will help to ensure that the recommendations are relevant and targeted to the specific interests of each customer.
- To reinforce the product recommendations, use social proof, such as customer reviews or ratings. This can help build customer trust and increase the potential for a purchase.
- Optimize for mobile: make sure your product recommendations are optimized for mobile devices. This can be done by using a responsive design that adapts to different screen sizes and using large, clear images and simple navigation.
- Use A/B testing: use A/B testing to experiment with different product recommendation strategies and see which ones are most effective. This can help to optimize the recommendations and increase their impact on sales.
Use product recommendations to improve the shopping experience, increase engagement, and boost sales on your ecommerce site!