The holiday shopping season has officially begun. Even with the headwinds of economic uncertainty from COVID-19, analysts expect a 35% increase in seasonal online sales this holiday season1. With gift-buying expected to be healthy, analysts also predict a shift back towards traditional gifts from past years’ experience-gifting. This will create a ripe opportunity for eCommerce companies.
Contrary to popular belief, an eCommerce chatbot is just the tip of the iceberg when it comes to how AI can propel companies to a new level of service. This holiday season, retailers are adopting AI to enjoy greater operational efficiency, provide a better customer experience (CX), reduce costs, and unlock new revenue. Here are some of the most exciting and new ways that eCommerce companies are using AI during this prime holiday shopping season and beyond to beat top-notch eCommerce benchmarks.
7 AI Use Cases for eCommerce Companies
1. Virtual Try-Ons and Fitting Rooms: While virtual try-ons have been popular for beauty and cosmetics brands over the years, many traditional retailers and eCommerce companies are rolling out virtual fitting rooms. Whether it’s due to retailers never reopening their physical dressing rooms even as in-person shopping came back during COVID-19, or consumer thirst for new experiences, companies like Macy’s, Adidas and Modcloth are now leveraging AI to power these new virtual experiences. With virtual fitting rooms, shoppers either upload their picture to an app or website, or simply add in their dimensions to create a custom avatar. They can then select products to “try-on” from the safety and comfort of their home. This caters to the 21% of Americans who plan to shop for themselves on Black Friday and 18% on Cyber Monday2.
2. Visual Product Search: A preference for visuals is hard-wired into us: the human brain processes images 60,000 times faster than text, and 90 percent of information transmitted to the brain is visual3. Visual search is a fast-growing area with billions of searches per month across social, search and shopping platforms. There are over 600 million visual searches on Pinterest every month4.
To help shoppers find gifts similar to what they’ve seen, numerous retailers like ASOS5, Walmart’s Hayneedle brand6, Uniqlo7 and IKEA8 are rolling out visual product search. Visual product search uses AI to help customers find stylistically similar products to those in an image that they show the AI. Consumers are rapidly adopting visual product discovery: in one study, 62% of Millennials reported a desire to visually search over any other new technology9. The results for eCommerce companies are significant: visual search results in 50% faster checkouts10, compared to keyword search. Visual search also results in a 20 – 30% increase in conversion. Gartner predicts that by 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%11.
3. Targeted, Contextual and Personalized Search: Retailers like Wayfair, Etsy Inc. and Pinterest are harnessing their sea of customer data to build predictive, AI-powered recommendation engines and provide unique product discovery search results12. By feeding historical data into these algorithms, retailers can anticipate which products will resonate best with a particular customer based on search and browse history, web behavior (time spent on specific product page) and purchase history. By using AI to recommend products from gigantic online catalogs — Wayfair, for instance, has 37,173 coffee mugs — retailers see a 50% jump in the success rate of in shopping cart additions. For example, when a customer finds an item is out-of-stock. AI can now analyze product color, size, pattern, price, style and other attributes to suggest similar items. AI-powered personalized product recommendations are increasing conversion rates by 915% and average order values by 3%13. This AI-driven personalization will boost profitability by 59% by 203514.
4. Conversational Shopping and Gift Finding: A weariness of shopping in store as a result of COVID-19, has led to 63% of consumers say they are avoiding stores and buying more online this year. In an effort to replicate the knowledgeable store associate, retailers are deploying conversational AI chatbots to act as personal shoppers. Chatbots help people find products and gifts based on who a customer is shopping for, as well as customers’ interests and preferences. These virtual shopping assistants are guiding people to discover products based on a variety of factors – replicating the in-store associate experience of asking a helpful store worker. Consumers are receptive to these conversational AI chatbots: one in every five consumers are willing to purchase goods or services from a chatbot15.
Discover the key questions to ask when scheduling a chatbot demo.
5. Automatically Resolve Customer Service Tickets: With ticket volume increasing 42% on average for retailers during the holiday shopping season, AI-powered customer support chatbots are helping retailers scale up support operations. AI chatbots automatically resolve common, everyday customer service queries. Mattress retailer Zinus, for instance, is using a Netomi-powered AI chatbot to instantly respond to product questions, order management, cancellations, warranties and more. This gives customers faster responses and eliminates the need to talk to a human agent for most questions (they can still do so if the retail bot doesn’t have the answer to a complex question). Leveraging AI chatbots to resolve customer service issues increases customer satisfaction (CSAT), reduces costs and boosts live agent productivity.
6. Preventing and seamlessly managing returns: Following the lucrative holiday shopping season, comes the sobering season of returns. Typically, returns spikes right after Christmas until late January. This year’s “return season” is expected to have more volume and last longer. This is because companies are having longer “Black Friday” season sales and seeing record volumes of online shopping due to COVID-19 as people shun indoor shopping.
According to reports, online shoppers return 15% to 30% of online purchases, compared to 13% for bricks-and-mortar purchases16. Last year, customers returned $41.6 billion worth of merchandise bought online during November and December alone17. Retailers are using AI to help mitigate returns and maintain customer satisfaction during the process in two key ways:
- Mitigating Returns Pre-Sale: Predictive analytics can help identify when a return is likely based on online behavior (i.e., checking size guide) or shopping cart (similar items; same item in multiple sizes). When there’s a signal that a return is likely based, a conversational AI agent can help the person make the best decision from the onset. If concluded from the conversation that an eventual return is intended, and the size of the purchase or the potential lost value of returned items in the cart make it worthwhile, retailers can leverage an AI chatbot to provide an incentive to limit the purchase to one selection.
- Increase Customer Satisfaction During the Return Process: Even if predictive analytics is deployed during the pre-sale process, returns are inevitable. Retailers are leveraging AI to keep customers satisfied throughout the process through automated updates of when a returned item is received and when a refund is issued. This matches customer expectations; 56% of people say they want notifications about a refund status and 50% want to know the status of their return package18. Beyond automated messages, AI agents can cross-sell alternatives to returned items to recover lost profits.
7. Optimized Inventory Management: Currently, retailers are losing nearly $1 trillion in sales because they don’t have on hand what customers want to buy19. To address this, eCommerce companies are tapping into AI to anticipate inventory needs and make smarter product purchase decisions. historic sales, anticipated changes in demand, supply-related issues ,and trend forecasting data are being fed into algorithms to help retailers know which products are likely to sell and how to adjust inventory to ensure the most in-demand products are in stock. For instance, to “…better stock individual stores with merchandise local clientele desires, H&M is using big data and AI to analyze returns, receipts and loyalty card data to tailor the merchandise for each store20.”
Retail and eCommerce Adoption of AI is Booming Across Many Use Cases this Black Friday and Cyber Monday
In this post, we’ve outlined seven of the top ways retailers and eCommerce companies are using AI this holiday season and beyond. As competition increases from traditional and nimble online-only players, eCommerce companies must leverage AI to provide an exceptional customer experience, drive efficiency with operations and planning, and reduce costs.
With Black Friday and Cyber Monday only two weeks away, retailers need to ensure their operations and customer experience won’t be impacted negatively by an increase in demand. It’s not too late for eCommerce companies to adopt AI to get out ahead of seasonal strain.
Continue Reading: Find out about the current state of retail email support in our Customer Service Benchmark Report. Download a copy today.
- CNBC: https://www.cnbc.com/2020/09/15/deloitte-estimates-2020-holiday-retail-sales-will-rise-1-to-1point5percent-.html
- Today.You.Gov: https://today.yougov.com/topics/consumer/articles-reports/2019/11/12/them-or-me-why-black-friday-sometimes-about-gifts
- T-Sciences: http://www.t-sciences.com/news/humans-process-visual-data-better
- Pinterest: https://newsroom.pinterest.com/en/post/celebrating-one-year-of-pinterest-lens
- enGadget: https://www.engadget.com/2018/03/09/asos-visual-search-tool-available-all-shoppers/
- TechCrunch: https://techcrunch.com/2018/12/18/walmart-is-testing-its-own-in-house-visual-search-technology-on-hayneedle/
- PSFK: https://www.psfk.com/2020/05/uniqlo-stylehint-personalized-social-commerce.html
- Reuters: https://www.reuters.com/article/us-ikea-ab-apps-exclusive-idUSKCN1SX1DV
- marketwatch: https://www.marketwatch.com/press-release/new-research-from-visenze-finds-62-percent-of-generation-z-and-millennial-consumers-want-visual-search-capabilities-more-than-any-other-new-technology-2018-08-29
- Shopify: https://www.shopify.com/retail/what-is-visual-search
- Gartner: https://www.gartner.com/smarterwithgartner/gartner-top-strategic-predictions-for-2018-and-beyond/
- WSJ: https://www.wsj.com/articles/retailers-use-ai-to-improve-online-recommendations-for-shoppers-11604330308
- Personalization.com: https://www.perzonalization.com/blog/personalized-product-recommendations-in-eCommerce/
- Big Commerce: https://www.bigcommerce.com/blog/eCommerce-ai/#the-future-of-ai-retail-and-roi
- Medium: https://medium.com/@Countants/how-artificial-intelligence-is-transforming-the-e-commerce-industry-countants-scalable-custom-73ae06836d35
- CNBC: https://www.cnbc.com/2019/12/19/online-returns-this-holiday-season-to-hit-record-41point6-billion.html
- CBRE: https://www.cbre.us/about/media-center/cbre-reverse-logistics-2019
- Navar: https://see.narvar.com/rs/249-TEC-877/images/Consumer-Report-Returns-2018-4.3.pdf
- Retail Dive: https://www.retaildive.com/news/out-of-stocks-could-be-costing-retailers-1t/526327/
- Forbes: https://www.forbes.com/sites/bernardmarr/2018/08/10/how-fashion-retailer-hm-is-betting-on-artificial-intelligence-and-big-data-to-regain-profitability/?sh=9fe938e5b00a