Recommendations drive sales by making it easier for customers to find the products they want. This can be done by recommending related products, showing best-selling products on the homepage and category pages, or using social proof.
By offering relevant recommendations, businesses can increase average order value and improve customer experience. However, it is important to keep in mind that recommendations must be carefully integrated into your marketing and design.
Recommendations are based on a shopper’s past purchases
Product recommendations are one of the most crucial elements in a high-performing eCommerce website. These features help customers find exactly what they want quickly and easily, reducing site navigation time and increasing average order value. They also create a personalized shopping experience and increase conversions by providing relevant products to each shopper’s needs. In fact, a study by Accenture found that 91% of customers are more likely to shop with retailers who provide them with product recommendations.
Recommendations can be based on any criteria, from a shopper’s browsing history to their location and previous purchases. Some of the most common recommendation types are bestsellers, items with discounts or special offers, and new arrivals. However, it’s important to note that personalizing product recommendations requires a great deal of work. Creating an effective personalization strategy requires a deep understanding of your customer base, product inventory, and business objectives. It also requires a strong data-driven approach to ensure that your recommendations are accurate and effective.
Displaying bestsellers on the homepage is a simple but effective way to introduce first-time visitors to your product line and hook returning shoppers. This tactic can also provide social proof for certain types of products, like electronics, by showing their popularity. Recommendations based on a shopper’s previous purchases are also effective for upselling, as they help shoppers discover additional items that complement or enhance the ones already in their cart.
Many ecommerce customers add multiple items to their cart before checking out. You can boost this figure by displaying relevant cross-selling recommendations during the checkout process. These should align with a shopper’s initial purchase intent, such as recommending a sofa bed to a shopper who has added a chair to their cart.
Recommendations can also be used to promote product bundles or discounts on popular items. These are effective tactics for increasing AOV, particularly for higher-value categories such as apparel or electronics. You can also recommend products that are similar in style or brand to those a shopper has purchased previously. This type of personalization is known as dynamic upselling, and it is proven to increase average order values.
They’re based on a shopper’s search terms
Product recommendations are an integral part of any ecommerce business’s website and can help drive conversions, average order value and repeat purchases. They can also reduce cart abandonment and encourage up-selling and cross-selling initiatives. However, it’s important to understand the shopper’s intent before implementing product recommendations. For example, someone looking for a specific product may want highly-targeted recommendations while a person who’s just browsing might be interested in a wider selection of products.
Personalized ecommerce product recommendations can be used across the site, in emails and even on social media. In addition to driving sales, they can improve the customer experience and build brand trust. This type of personalization is a must-have for retailers that want to compete in today’s marketplace.
A personalized product recommendation engine uses machine learning to analyze a user’s preferences, purchase history and browsing behavior to curate relevant recommendations aligned with their intent. These recommendations are displayed on a variety of pages, including home page, category pages, product detail and cart pages. Recommendations can also be tailored to a user’s location, with prices displayed in their local currency and applicable shipping fees.
One of the simplest ways to implement a product recommendation is to display best-selling items on key pages. Shoppers are drawn to the idea that others are buying a product, so a “best seller” tag is an effective way to drive engagement and conversions. Best-selling products can be featured on the homepage, category pages or in product detail and cart pages.
Another way to leverage product recommendations is by displaying product bundles. These are recommendations that show users products that frequently purchased together and allow them to add them to their cart in a single click. This can be a powerful upselling strategy, but it must be used sparingly because it may lead to higher abandonment rates.
It is important to use a variety of product recommendation strategies in conjunction with each other to maximize results. For example, a site that offers free shipping on all orders can display popular products at the top of a category page. This will not only increase sales, but it will also make shoppers feel like they are getting a better deal.
They’re based on a shopper’s interests
Whether they’re new or returning customers, personalizing recommendations helps shoppers feel that your business understands them. This builds trust and can cultivate brand loyalty. Recommendations can also reduce barriers to purchase, and a well-placed product recommendation can drive up average order value. Recommendations should be tailored to a shopper’s unique needs and presented at the right point in their buying journey. For example, recommend a related accessory to a product someone has already added to their cart or a bundle of products that are frequently purchased together on a product category page.
For first-time site visitors, a recommendation block or popup can be used to promote popular and trending products. These recommendations can be based on their browsing and purchasing history, or on their first-party data (e.g., email address or social media profile). Recommendations based on a shopper’s interests can be highly effective and increase customer satisfaction by reducing the amount of time shoppers spend looking for a product they want to buy.
Recommendations can be triggered when users visit specific pages, search for certain words, or add items to their carts. They can include personalized offers such as free shipping or discounts and can be based on the product’s popularity or how many people have viewed it. They can also be based on other attributes that can be gleaned from a user’s profile, like their skin type or hair color.
For returning customers, you can display dynamic recommendations on your homepage or product category pages based on their purchasing and browsing history. This can encourage them to spend more on a single order or boost their shopping cart total by offering complementary products. Recommendations can also be based on their location and the items that are most popular in their region. These types of recommendations are known as “herd mentality” offers, which leverage a shopper’s natural desire to fit in with the crowd. They can also be based on a shopper’s search terms, which evokes the sense of urgency that is needed to persuade them to make a purchase.
They’re based on a shopper’s behavior
Ecommerce product recommendations are personalized prompts that help shoppers discover products they’re likely to want and need. They’re based on factors such as shopping and browsing behavior, customer segmentation, and purchasing history. They’re one of the best ways to drive average order value, increase conversions, and boost customer retention.
Product recommendations can be global, based on wider consumer trends and sales data, or personalised, based on the user’s individual buying behaviour, browsing history and unique attributes. They can be displayed across every page of the site, from category pages to a customer’s cart and even in email marketing. They can be used to encourage customers to add more items to their basket, re-engage them with items they’ve viewed or bought in the past, or to display a range of relevant products that would complement a product of interest.
TC Straps is a great example of a brand that shows related products to their shoppers on their cart page. This type of recommendation aims to upsell and cross-sell by showing the buyer accessories for a particular item, such as additional straps or extra buckles. It also provides social proof by showcasing popular options that others have purchased.
Amazon is a master of this with its “frequently bought together” recommendations, which show the buyer items that complement their existing purchase. These suggestions are displayed below the item in their cart, on product detail pages and in the cart confirmation.
These types of recommendations can be particularly effective on the homepage of an ecommerce website, as they give first-time visitors a quick and easy way to find what they’re looking for. The more targeted they are, the better. A shopper that is ready to buy will want highly-targeted recommendations while someone who is just browsing might appreciate more general recommendations so they don’t get overwhelmed by too much choice.
Another great use of recommendations is on category pages, where they can be presented alongside specific savings. This is a simple way to boost engagement by incentivising the visitor with relevant offers that fit their needs.
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