The 7 Best Ecommerce Chatbot Solutions and What Makes Ecommerce Bots Succeed

Written by Dylan Max  on   May 28, 2021

From product recommendations to one-on-one personal shopping and customer support to order management, the use cases for ecommerce chatbot solutions are endless. This is why the eCommerce industry was one of the first industries to embrace chatbots and conversational AI virtual assistants. 

And the need for eCommerce chatbots has never been higher than it is today. Online shopping is one of the most popular activities in the world, and the industry is more competitive than ever. There’s a healthy new pipeline of digital-first retailers built on the idea of customer-obsession and seamless end-to-end experiences. At the same time, traditional brick-and-mortar retailers have accelerated digital innovation in the wake of COVID-19 looking to remove friction while also replicating highly-personalized, one-on-one interactions with customers at scale. In fact, McKinsey reported that in just eight weeks, five years of consumer and business digital adoption occurred during COVID-19. 

All of this comes at a time when people are less loyal. Shockingly only 9% of consumers are brand loyal today. eCommerce companies are competing as much on customer experience as price: 61% have switched brands due to poor customer service and more than half of Americans have scrapped a planned purchase or transaction because of bad service.  Prioritizing customer service, though, can pay off: 78% of customers say the quality of service is fundamental to earning their repeat business and US consumers say they’re willing to spend 17% more to do business with companies that deliver excellent service. 

In this post, we’re diving into the best use cases for an eCommerce chatbot, our favorite eCommerce chatbots of all time and strategies for a successful eCommerce CX automation strategy. 

What are the top use cases for eCommerce chatbots? 

eCommerce companies using chatbots for customer service can streamline the entire customer journey. Here are our favorite use cases: 

1. Immediate responses to common customer service FAQs

Customer service chatbots are one of the most common use cases for AI across industries, but they are especially prevalent in the eCommerce space:  From product care and return policies to warranty information and troubleshooting, eCommerce chatbots can provide immediate answers to common questions. This can save a person from scrolling through pages of an online knowledge base or reaching out on a channel that requires more heavy lifting. 

2. Personal shopping and product discovery

AI-powered chatbots can understand shopper preferences to curate highly personal product recommendations. Chatbots are also used frequently during the holiday shopping season, helping shoppers find the perfect gift for everyone on their list based on price range, interests and other attributes. 

3. Conversational commerce

eCommerce chatbots can provide a seamless add to cart and checkout experience, all within a natural conversational interface across live chat, Facebook and social media pages, messaging apps and SMS. 

4. Return prevention

It’s estimated that over 30% of all online purchases are returned. If a shopper is conducting behavior that indicates a return is likely, eCommerce chatbots can preemptively intervene to prevent a return from ever happening. For example, if a person has checked the size guide and added two of the same item in the cart in different sizes, a chatbot can intervene to help the person find the right size. This not only eliminates a customer from having to go through the hassle of returning an item, but also saves the retailer significant costs related to returns. 

5. Order management

Making small changes to an order or tracking the status of a delivery are mundane tasks that should not require a human agent. Not only is it costly to have humans perform these simple tasks, but often results in wait times and longer resolution times, and increased customer frustration. 


Discover the key questions to ask when scheduling a chatbot demo.


The 7 Best eCommerce Chatbot Solutions of All Time 

From upstarts to some of the most established brands,eCommerce companies have launched chatbots to alleviate friction at various parts of the customer experience. Here are our favorite eCommerce chatbots of all time. 

1. Hewlett-Packard

Why does Hewlett-Packard have one of the best eCommerce chatbots of 2021?

The Hewlett-Packard Company (HP) leverages Netomi’s AI chatbots to eliminate a major pain point in the customer experience: running low on ink. Real-time signals from HP printers alert Netomi’s AI when a person is at risk of running dry and preemptively intervenes, sending a customer a personalized cart with compatible cartridges and providing a seamless reorder experience.  Previously, helping a customer find the right ink cartridge was one of the most costly and time consuming tickets for HP, taking on average, between 7-8 minutes. Leveraging chatbots, HP now does this proactively and instantly. 

2. Sephora

Why does Sephora have one of the best eCommerce chatbots of 2021?

Well regarded for its innovation, Sephora is often recognized for new and innovative CX programs and was one of the first retailers to adopt AI-powered ecommerce chatbot solutions. One of the beauty company’s chatbots enabled customers to book a makeover with a Sephora Beauty Specialist, which had an 11% bump in conversions compared to other channels.  Another conversational AI experience from Sephora was Color Match, which allowed customers to find the best makeup shade for their skin tone and even recommend shades based on other objects like flowers or clothes. One of Sephora’s bots on kik had incredible engagement: an average 10 messages per user per day.   

3. Tommy Hilfiger

Why does Tommy Hilfiger have one of the best eCommerce chatbots of 2021?

The TMY.GRL ecommerce chatbot, from the iconic Tommy Hilfger fashion house, was one of the first conversational AI experiences on Facebook Messenger. During New York Fashion Week, fans could instantly shop the same styles seen by models walking the runway, which used to not be available for weeks or months. The Messenger bot also provided a look at the behind the scenes at the fashion show getting shoppers up close and personal with models like Gigi Hadid. 

4. Harry Rosen

Why does Harry Rosen have one of the best eCommerce chatbots of 2021?

Meet Haily, the innovative chatbot from Harry Rosen, a Canadian retail chain of 17 luxury men’s clothing stores. Haily scales the same high-touch, in-store experience that its customers love online. Haily helps shoppers find the status of their order, request and track returns, and track and redeem loyalty points. Haily is also a personal shopper, offering personalized product advice and answering questions related to fit, style or suitability. 

5. Zinus

Why does Zinus have one of the best eCommerce chatbots of 2021?

Zinus, one of the fastest-growing mattress brands, introduced its chatbot Zuri to remove friction from the customer journey. Zuri provides instant support for the most common customer questions like: Where is my order? Can i modify my recent order? How do I apply for a warranty? Chats are seamlessly handed off to an agent within the same window if needed, providing an experience as satisfying as a Zinus mattress itself.  

6. ebay

Why does ebay have one of the best eCommerce chatbots of 2021?

There are currently over 1.6 billion live listings on eBay, making it one of the biggest global marketplaces. You can literally find almost anything you’re searching for, but sometimes scrolling through pages of listings can seem daunting. That’s why eBay launched ShopBot. The virtual agent messenger bot helps shoppers find the best deals and products. Users text or snap pictures of items they are looking for (i.e. I want red Nike shoes) and the bot will ask questions to better understand what a person is looking for (sizing, budget, etc.)  in order to narrow down the options. 

7. Casper

Why does Casper have one of the best eCommerce chatbots of 2021?

A few years ago, the mattress company launched a bot to engage with customers and keep them entertained when they couldn’t sleep. Named insomnobot3000, the bot is “extra chatty between 11 PM and 5 AM” and is a companion for night owls. According to Casper VP Lindsay Kaplan, “It’s kind of obsessed with pizza and is really on the fence about if it’s too late to eat or it should just wait to eat waffles in the morning.” While insomnobot3000 is not addressing a key part of the customer journey, it’s a creative example of an ecommerce chatbot. 

What are the pillars for a successful eCommerce CX automation strategy?

While there have been many successful eCommerce chatbots, some have failed to deliver. In order to implement a successful AI chatbot, eCommerce companies need to follow a few key strategies: 

  • Leverage Natural Language Understanding (NLU)
    NLU is a key component of any conversational AI. In the eCommerce context, it is used to allow customers to engage in natural and unnatural language. Chatbots that rely simply on keyword matching lead to frustrating user experiences as the bot gets confused easily. 
  • Identify common pain point
    The customer journey is filled with pain points that can be fixed withinwith in the customer journey (i.e. a person running out of ink) and repetitive tasks that can be easily automated. Start with a few key use cases and expand over time. 
  • Deploy deep reinforcement learning
    The accuracy of your chatbot on day 1, 30 and 60 should not be the same. The smartest chatbots learn and improve over time with every interaction. You’ll tweak the algorithms to ensure the bot is classifying a person’s intent correctly and also uncover new use case opportunities to automate. 
  • Give the chatbot an on-brand personality
    Keep the experience fun and engaging, but don’t clutter the interaction with unnecessary back-and-forth chatter. Get to the point quickly. Ask the necessary questions only. And keep everything on-brand. [Learn more about conversational UX design]. 
  • Launch on the channels where your customers are
    Chatbots don’t just have to live on live chat widgets on a website. Interact with your customers at scale on social media pages, messaging apps, SMS, voice platforms and even email. 

Leveraging a live chat software on a website and on social media helps eCommerce companies scale 1:1 interactions with customers, 24/7. Customers today expect effortless, convenient and highly personal shopping experiences and when they reach out for customer support, they demand instant resolutions. As the competition within the eCommerce industry continues to heat up, the companies that prioritize the customer experience will be the ones that drive sales and capture long-term customer loyalty. 

Learn more about the opportunities for eCommerce and retail chatbots with netomi’s chatbot platform.

Find out what your ROI will be if you build an AI chatbot. Try our free chatbot ROI calculator today.

7 Ways eCommerce is Using AI on Black Friday and Cyber Monday

Written by  on   Nov 17, 2020

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

Visual search built in collaboration between Hayneedle and Walmart Labs

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

References 

  1. CNBC: https://www.cnbc.com/2020/09/15/deloitte-estimates-2020-holiday-retail-sales-will-rise-1-to-1point5percent-.html 
  2. Today.You.Gov: https://today.yougov.com/topics/consumer/articles-reports/2019/11/12/them-or-me-why-black-friday-sometimes-about-gifts 
  3. T-Sciences: http://www.t-sciences.com/news/humans-process-visual-data-better 
  4. Pinterest: https://newsroom.pinterest.com/en/post/celebrating-one-year-of-pinterest-lens 
  5. enGadget: https://www.engadget.com/2018/03/09/asos-visual-search-tool-available-all-shoppers/ 
  6. TechCrunch: https://techcrunch.com/2018/12/18/walmart-is-testing-its-own-in-house-visual-search-technology-on-hayneedle/ 
  7. PSFK: https://www.psfk.com/2020/05/uniqlo-stylehint-personalized-social-commerce.html 
  8. Reuters: https://www.reuters.com/article/us-ikea-ab-apps-exclusive-idUSKCN1SX1DV 
  9. Businesswire – ViSenze: https://www.businesswire.com/news/home/20180829005092/en/New-Research-from-ViSenze-Finds-62-Percent-of-Generation-Z-and-Millennial-Consumers-Want-Visual-Search-Capabilities-More-Than-Any-Other-New-Technology
  10. Shopify: https://www.shopify.com/retail/what-is-visual-search 
  11.  Gartner: https://www.gartner.com/smarterwithgartner/gartner-top-strategic-predictions-for-2018-and-beyond/ 
  12.  WSJ: https://www.wsj.com/articles/retailers-use-ai-to-improve-online-recommendations-for-shoppers-11604330308 
  13.  Personalization.com: https://www.perzonalization.com/blog/personalized-product-recommendations-in-eCommerce/ 
  14.  Big Commerce: https://www.bigcommerce.com/blog/eCommerce-ai/#the-future-of-ai-retail-and-roi 
  15.  Medium: https://medium.com/@Countants/how-artificial-intelligence-is-transforming-the-e-commerce-industry-countants-scalable-custom-73ae06836d35 
  16. CNBC: https://www.cnbc.com/2019/12/19/online-returns-this-holiday-season-to-hit-record-41point6-billion.html 
  17.  CBRE: https://www.cbre.us/about/media-center/cbre-reverse-logistics-2019
  18.  Navar: https://see.narvar.com/rs/249-TEC-877/images/Consumer-Report-Returns-2018-4.3.pdf  
  19.  Retail Dive: https://www.retaildive.com/news/out-of-stocks-could-be-costing-retailers-1t/526327/  
  20.  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