Boost your bottom line with suggestive selling (and let AI help)
If you've ever walked into a store determined to buy one thing—a string of lights for your Christmas tree, or a tasteful holiday-themed serving platter—but left with that thing plus a 12-foot inflatable Santa for your lawn, then you've experienced the phenomenon of suggestive selling.
Suggestive selling, otherwise known as upselling and cross-selling, involves strategies that motivate shoppers to buy more of something or spend more during a single shopping excursion. The goal, from the store owner’s perspective, is to increase the average order value of someone’s purchase by subtly suggesting other items they might like, want or need.
Suggestive selling is nothing new—it’s been around for as long as people have been selling stuff to other people. But now, with the emergence of artificial intelligence (AI), suggestive selling has gone to the next level. Let’s explore all of the ways how.
Start (suggestive) selling with an online store from Wix.
What is suggestive selling?
Suggestive selling uses persuasive techniques to upsell and cross-sell products and services to your customers. It’s a deliberate, but subtle, strategy for increasing the average value of a single sale. When you start a business or have an online store, you can use various suggestive selling approaches as one of your eCommerce strategies to achieve three primary goals:
Sell more of the same item (e.g., buy five pairs of underwear and get 15% off)
Sell a higher-value item (e.g., buy the deluxe version of this candle and we’ll throw in a free candle warmer)
Sell similar items (e.g., we saw you bought our 12-foot inflatable Santa, here’s a 20% off coupon for an inflatable snow globe to go with it)
Learning how to sell online requires more than just learning how to make a website and how to drive traffic to it. It requires a deep understanding of sales techniques that reach customers while they’re actively shopping. The key to being successful at suggestive selling is to keep it low key. This isn’t an in-your-face strategy, but an understated way to introduce products or offers that resonate with consumers who are actively shopping.
Another thing to keep in mind with suggestive selling is that the products or services you’re trying to upsell and cross-sell should complement the main purchase but be of somewhat lesser value. This is why stores like Amazon and Newegg might suggest a laptop case to go with the Zenbook in someone’s cart versus a flat screen TV.
Understanding your customers, including who they are, what they want and what problems they come to you to solve is the only way to make suggestive selling work. Luckily, technology can help with this.
Enter AI: Why use AI for suggestive selling?
Suggestive selling coupled with artificial intelligence might be the future of eCommerce. That’s because AI-driven personalization tools focus on exactly the things that resonate with online shoppers the most—custom product recommendations, personalized offers, smart product pairing, etc. All of this contributes to the goal of getting shoppers to spend more.
The benefits of using AI for suggestive selling include:
Reduced cart abandonment: The average eCommerce shopping cart abandonment rate is 70%, according to data from Baymard Institute. AI-powered suggestive selling helps reduce this by serving up personalized product recommendations, sending cart reminder emails and even chatting with customers (via intelligent chatbots) when they reach out with a question after hours.
Increased average order value (AOV): McKinsey has good things to say about the impact of cross-selling and upselling on eCommerce businesses, noting it can increase profits by as much as 30% and sales by 20%. Since AI-fueled suggestive selling makes it easy for even small online retailers to effectively cross-sell and upsell, it has the potential to significantly impact both sales and revenue.
Improved customer experience: AI and machine learning use a customer’s past and present shopping behavior to customize recommendations and suggestions. This makes it an excellent tool for improving customer experience. Consumers, for their part, expect this kind of personalized shopping experience—nearly 90% of U.S. shoppers surveyed by Statista said that personalization motivates them to continue shopping.
Increased customer loyalty: Retaining customers is as crucial as acquiring new ones. AI-powered suggestions can help here, too. Again, it’s all about providing a good online shopping experience. By consistently delivering relevant product recommendations and personalized offers, you’re demonstrating that you understand your customers. This increases trust which increases the likelihood that people will visit your online store again and again.
Improved organizational efficiency: By automating product recommendations, personalizing content and using social proof (among other tactics), AI tools improve organizational efficiency. Look, the robots are coming whether we want them to or not, we may as well delegate the boring and time-consuming stuff like data management and analysis to machine learning algorithms. AI makes data-driven suggestive selling scalable, freeing you (and your staff) to focus on more creative and high-value tasks.
Ways businesses are using AI for suggestive selling
Using some real-world examples, we’ve outlined some tangible ways that any type of business (but especially an online store) can benefit from using AI for suggestive eCommerce selling.
01. “Related product” recommendations
AI-powered product recommendations are a common eCommerce feature in online stores of all sizes. That makes sense since about half of U.S. consumers want personalized product recommendations when they shop online. They’re nearly as popular in other countries including Ireland, Spain and Australia, according to Statista.
Product recommendation tools use AI and machine learning to recommend “similar products”—products that share similarities to what a user is looking at—based on behavior and user data (e.g., what a shopper is looking at in the moment, what they have in their cart, etc.). They can also recommend similar items that other people are buying or what’s popular and trending.
Let’s say (hypothetically) you're looking at a Christmas-inspired candle because you (also hypothetically) love Christmas scents and cute Christmas-themed décor. When you reach the product page for this (adorable) candle, you're presented with a few similar holiday-themed candles below the list of product reviews. That is suggestive selling in action.
Real-world example: Wix merchant and fitness wear retailer Love Her Shop shows a “Related Products” gallery at the bottom of each product page. You can add this AI-powered feature to your own Wix store to recommend related or “best selling” products to your customers.
02. “Bought together” recommendations
Grouping products via labels like “Bought together” or “Complete the look” is a product recommendation approach that focuses on displaying a complementary item (or items) along with the product a shopper is viewing. This is a common technique used for electronics like cameras, laptops and mobile phones, which come with a lot of accessories. But it works across many retail categories.
Real-world example: Amazon’s “Frequently bought together” section is practical and understated. The recommendations are prominently located beneath the item a shopper is viewing, offering the ability to add some or all of the related products to your cart. It also displays the price for each and total for everything bundled together.
Pro tip: Wix merchants can install the ReConvert Upsell & Cross-Sell app to integrate with their online store. The app instantly boosts AOV and sales by adding product upsells or cross-sells to your checkout page. There’s also the Twik Store Personalization app, which uses AI to personalize your online store experience, menus and product catalogs to each individual shopper.
03. Comparison shopping recommendations
Providing a list of similar products for comparison is another suggestive selling strategy that many online store owners employ. This is a useful way to reduce choice paralysis and help shoppers who may be new to your store or just not sure exactly what they want. This strategy is also a nice way to showcase your product selection, while (unobtrusively) upselling higher-end products using a side-by-side comparison approach.
Real-world example: Wayfair’s “Compare Similar Items” feature helps refine a shopper’s choices based on their browsing activity. When a shopper visits a product page, a list of similar items appear alongside the current item. The most important information including price, star ratings and a brief product description appear with the product image. More detailed information like product dimensions and materials is available if you scroll a bit.
04. Social proof
Social proof, a psychological phenomenon where humans look to other humans to guide their decisions, is a powerful suggestive selling strategy. Social proof elements on eCommerce websites focus on product recommendations and reviews.
They often feature user content from social media—typically people wearing or using the product, and FOMO elements that display how many people have an item in their cart.
Real-world example: thredUP, an online thrift store, has a target audience of young adults aged 18 to 30. They use social proof to convey urgency, for example, by flagging items as popular and likely to sell soon. This is a particularly useful strategy since every item on thredUP is one of a kind.
When a shopper clicks on a thredUP item, the product page displays various social proof elements including the number of people who’ve “favorited” the item and how many carts it’s in (if any). If the item is popular, this is flagged with a flame icon and the text “This item is popular! It’s likely to sell soon.”
Adding the item to your thredUP cart prompts a popup featuring a countdown clock giving you an hour to make the purchase before the item is removed from your cart and made available again. thredUp also has a "People who shop X also shop Y" section which displays similar items from different thredUP sellers.
05. Email recommendations
Suggestive selling isn’t limited to your website or app, it’s also an incredibly effective email strategy. Suggestive selling email approaches include:
Cross-selling emails: Cross-selling products via email is a suggestive selling approach that goes straight to a shopper’s inbox. This is a good strategy for recommending complementary products, sending “back-in-stock” notifications and providing after-purchase coupons. In fact, any product recommendations approach you implement on your website can be mimicked in an email.
Upselling emails: Sending existing customers or subscribers notifications about your latest and greatest product is an effective upselling technique used by brands like Apple, Microsoft and Petco. Computers, smartphones, fitness trackers and cars are examples of products that eventually need to be upgraded. It works well for non-electronic categories to introduce new products, like the Petco example below.
Abandoned cart reminder emails: The abandoned cart reminder notification is a classic move; reminding shoppers that they have an item in their cart is a suggestive selling technique with proven results. Multiple data sources reveal that about 70% of online shopping carts, on average, are abandoned. This means there’s a huge opportunity to reactivate an incomplete sale.
Milestone emails: Email is a great way to stay in touch with past customers, particularly when you time your campaign around an event or milestone. For example, online pet store Chewy sends out cards when a customer’s pet has a birthday. They include a coupon for a “birthday” box of treats and food for the animal. Human birthdays, customer anniversary dates and rewards milestones can all serve as catalysts to send out email with suggestive selling messaging.
Real-world example: Like most big retailers, Petco regularly adds new products and product lines to its vast selection of items. The company send announcements like the one below, introducing the availability of Ollie’s, a nutritious and healthy brand of dog food, treats and supplements.
Petco’s email isn’t overly promotional, but it does contain a lot of information. In addition to announcing the new product line, Petco includes a reminder to “get closer to your next reward,” a link to a survey for shoppers who want help selecting an Ollie’s product, a 35% off coupon to sign up for repeat delivery and other various promos at the end of the email.
06. Product ratings
Product ratings are so important for eCommerce sales that they’re worth dropping a statistic or three. According to a 2023 Power Reviews survey of over 8,000 consumers, 77% of shoppers seek out websites with ratings and reviews and 74% say they're the primary way they learn about new (to them) products.
Ratings and reviews are the most important consideration for consumers when buying online, with 91% of respondents saying they always read reviews. We could go on, but our point is this: include reviews on your website if you want to sell more things.
Real-world example: Duluth Trading Company includes the star rating and number of reviews beside the main product image along with other important information like the price, color and size. If a shopper clicks on the “reviews” link, they’re transported to a list of reviews that have more information, including customer photos if they’re available.
Reviews can make or break a sale. They’re an important suggestive selling tool, but keep in mind that bad reviews can and will happen and it’s important to stay on top of all reviews so you can follow up with customers as needed.
07. Intelligent chatbots
Intelligent chatbot technology is one of the main ways that AI is transforming business right now. Chatbots use AI and machine learning algorithms to respond to human queries with natural language responses. Often associated with customer service use cases, they can also be used for suggestive selling. They work by combining predictive intelligence and user analytics to make appropriate recommendations.
They can also be programmed to guide customers through the sales process based on real-time information. Plus, they learn your customers’ preferences over time, so they’re in a good position to suggest relevant products based on this information.
Real-world example: Buying makeup and skincare products online is no easy task, but Sephora’s made it much easier with a host of features to help shoppers navigate the many choices. One such feature is their Live Beauty Help chat, which opens with an AI-chatbot that screens users before connecting them with a live agent. When you ask a question, the chatbot searches for a live agent who can address your specific issue (e.g., “I need a shampoo for fine hair”).
This is an example of hybrid approach to chatbot technology which uses a combination of an intelligent chatbot plus human-powered chat to provide good customer service, all with the goal of suggestive selling. Once a product (or multiple products) is suggested, the agent can provide links right in the chat, as is the case with Sephora.
