This week we take a look at some recent developments in the realms of personalized shopping and artificial intelligence (AI) in ecommerce. Retailers, digital marketplaces, social networks and department stores are all trying to figure out the best way to deliver personalized, data-driven customer experience.
Many companies see artificial intelligence as the answer to improve the shopping interface and user experience, while other marketers turn to personalized targeting methods and omni-channel strategies. In exploring these technological advances, it must be understood that not all innovations are profitable. These ideas have promises and risks, and their efficacy will ultimately be tested and decided by the customer.
eBay Uses Artificial Intelligence to Make It Easier for Shoppers to Discover Products
Last week, eBay acquired Expertmaker, a Swedish company that focused on artificial intelligence, machine learning and big data analytics. This is all part of eBay’s structured data initiative, which aims to better organize product data and improve product searches.
While not yet mandatory for sellers, eBay has been strongly encouraging sellers to provide accurate product data. According to their 1Q 2016 earnings report, 60% of listed items on eBay currently use structured data rules, a 37% increase from 4Q 2015.
The online marketplace aims to build better user experiences by simplifying inventory and improving product relevance and discovery. As with other tech giants looking for innovative ways to improve the customer experience, eBay is pushing for customer-centric and data-driven intelligence that better targets shoppers and help them discover similar products.
1-800-Flowers Introduces Digital “Gift Concierge” to Help Customers Find the Perfect Gift
In lieu of their bot platform launch on Facebook Messenger, 1-800-Flowers launched “GYWN” just in time for Mother’s Day last week. GYWN (Gifts When You Need) is a digital shopping expert powered by IBM’s artificial intelligence system.
Instead of browsing through the entire gift inventory or filling out a website search form, you can simply chat with GWYN. Based on your conversation and past shopping behavior, GYWN will offer customized gift suggestions and product recommendations. Unlike other product recommendation engines, GWYN will ask a number of contextually relevant questions about the occasion, sentiment and recipient in order to best tailor the gift suggestion.
From live support on Messenger to Amazon’s Alexa integration, the specialty gifts retailer has been constantly spending on technological developments to enhance the customer experience, providing ease of purchase to ultimately win brand loyalty. Only time will tell if these investments succeed.
Instagram Offers Retailers New Ways to Drive Sales and Target Consumers
Items from your previously abandoned shopping cart will now show up on your Instagram feed. The “subtly creepy” yet “slyly effective” Facebook product ads are now being rolled out as dynamic ads on Instagram. This retargeting program aims to remind users of products they might have been interested in or have forgotten to purchase.
These sponsored posts appear to be effective in helping retailers better reach their target audience. A joint study by Facebook and Instagram showed that 60% of Instagram users discovered new products through the app, while 75% reported that a sponsored post inspired them to take action. People also spend 54% of their time using mobile apps, making these apps an excellent marketing channel.
Sponsored posts and dynamic ads are catered to you based on your web consumption, browsing behavior and demographic. While retargeting can certainly capture shoppers who have forgotten to complete their purchases, sponsored posts can sometimes feel invasive and annoying if the user has already made the purchase or is no longer interested in the product. Retailers must learn not to overuse this retargeting tool, to prevent sullying the customer experience.
Personalized Recommendations Can Be Cool, But Some Find Them Downright Creepy
Department stores are trying out different ways to customize the shopping experience, from personalized promotional offers to product recommendations from a personal shopper. While some consumers find these services to be cool, others reacted to them negatively.
Accenture surveyed more than 10,000 smartphone users who shopped digitally and in-store. According to the study, 53% of US respondents found it creepy when a sales associate knew what was in their digital basket or wishlist. Only 21% found it cool. Similarly, 42% of respondents found it creepy when an in-store sales associate picked items based on their customer’s profile, budget and purchase history.
In the same vein, 46% of consumers found it invasive when retailers showed feedback left by their friends on products they were considering. Retailers looking to innovate in the realm of social commerce and personalized service must be sensitive to how their customers feel. Many consumers don’t consider corporate brands as friends, so retailers have to draw the line when it comes to using data-driven intelligence to personalize the shopping experience.
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