Artificial intelligence (AI) empowers retailers to drive more revenue with personalized experiences. In fact, outerwear retailer Icebreaker found that its shoppers clicked on personalized product recommendations 40% more often than non-personalized ones, leading to 28% more revenue and an 11% increase in average order value.
Icebreaker was able to scale its personalization efforts because of AI, which some retailers still find challenging to implement. But you don’t need to completely overhaul your content creation process or shopper journey to reap the benefits of AI. To get started, you just need to define where AI will have the biggest impact on your shopper experience and develop an easy-to-follow strategy from there.
How can AI be used in retail?
Once you ensure that your channels are ready to handle personalized content, you’re ready to think about the actionable ways you can use AI to offer more personalization to your customers. Here are two easy use cases to help you implement AI.
1. Use AI to personalize your product recommendations
Just like the Icebreaker example above, brands can use AI to collect, organize, and use data to guide shoppers to other content pages and product recommendations based on their behavior. AI takes stock of every customer action: views, taps, add-to-carts, saves, likes, device preference, and locations to immediately start personalizing the experience. Each action builds a profile around the shopper so that AI can align products and categories to their preferences.
This keeps shoppers coming back. According to our “Personalization in Shopping” report, 37% of shoppers who click a personalized recommendation during their first visit return, compared to only 19% who didn’t click a personalized recommendation.
There are four places where AI can personalize the retail experience for shoppers:
- Home page: Surface top-selling and recently-viewed products across your catalog. Start small. If something doesn’t work or your strategy needs further development, you can optimize quickly.
- Category landing pages: Show products specific to a category, landing page, or both. It doesn’t have to be all or nothing — test gradually.
- Product detail page: Incorporate a simple recommendation zone showing products that customers may also like. By recommending products similar to the product they’re viewing, you quickly give them more choices and paths to purchase.
- Checkout: Use the checkout process as an opportunity to recommend complementary products. For example, build abandoned cart emails to remind shoppers of products they left in their cart and make recommendations for similar products.
2. Use AI with site search to improve conversion
Another tool that helps shorten the time to purchase is site search. For “surgical shoppers” — those customers who already know what they’re looking for — search makes it easy to zero in on the perfect product.
Shoppers who both search and click a recommendation convert 3.7x more often than those who only search. Additionally, shoppers who use both convert 2.1x more often than those who only click on a recommendation.
Here are a few best practices to keep in mind:
- Visible search: Encourage shoppers to search for products by placing the search bar in a strategic location they will see when they view your website and product pages.
- Pervasive search: Make the search bar “sticky,” so it stays on the page when a customer scrolls through products. This also reduces friction for mobile shoppers, who are more likely to purchase when they click on a search bar.
- Quality data: The accuracy of personalized search results depends on the quality of the data. If you start with unorganized data with inaccuracies, the insights and personalization will be much less effective.
In our own research on retail trends, we found that half of repeat buyers will make their next purchase within just 16 days, so it’s more important than ever to catch them in those important moments with relevant offers and sophisticated search functionality.