Ecommerce Benchmarks for 2021

Written by Emily Cummins  on   Nov 24, 2020

Overview of our 2021 eCommerce Benchmark Report

  • Results of our eCommerce Benchmark Report which analyzes the world’s 2,000 largest eCommerce companies 
  • Findings reveal how the top eCommerce companies deliver against customer service KPIs: availability, responsiveness, resolution time, and measuring customer satisfaction (CSAT) 
  • Analysis of how users of Zendesk users perform against users of other agent desk platforms

We’re excited to announce the launch of our eCommerce Benchmark Report. While it’s not uncommon to see a company on this list with an eCommerce chatbot – a nice start to address customer needs – this research will evaluate the top brands on a different support channel. In our report, we dig deep into the email customer support of the world’s biggest eCommerce companies. As the eCommerce industry becomes more competitive, prioritizing the retail customer service experience is now required to build and grow a business. Our study revealed that eCommerce companies need to greatly imprcustomove their email support experience, providing quicker responses with higher-quality answers and empowering their human agents to be empathic.

Key Findings of the eCommerce Benchmark Report

  • Only 59% of eCommerce companies have an easily accessible email address.
  • Of the eCommerce brands that have an email address, a staggering 30% ignore emails.
  • The average score for the Support Performance Index (SPI), which measures personalization, empathy, answer quality and responsiveness, is 56.2 / 100 
  • The average score on the Answer Quality Index (AQI), which measures the usefulness and meaningfulness of a response, is only 44.2 / 100.
  • 1 in 2 companies respond to customer inquiries in the first 6 hours 
  • 88% of eCommerce companies personalize responses.
  • 3 in 4 companies do not show any compassion to a customer in need.
  • eCommerce companies in APAC provide the best customer service, resolving tickets almost 1.5X as compared to eCommerce companies in EMEA
  • When it comes to the quality and thoroughness of an answer, Zendesk users scored 53.3 on the AQI, almost 30% higher than other users of other agent desk platforms.
  • In SPI and AQI, Luxury Goods outperform companies while Consumer Electronics companies trail the rest.

Email is not often an option, and often turns into a black hole 

While email remains a preferred channel for customer support to ask for a return, update a delivery address or ask a question about a product, a whopping 41% of global eCommerce companies do not offer email support.


Looking to maximize your CX? Discover what platform may be best for you in our comparison of Intercom vs. Zendesk.


Email inbox or black hole? 

Only 69% of eCommerce companies respond to a generic question about a return policy, meaning 31% of companies ignore emails altogether. Our research also exposed inconsistencies with response rates depending on whether a question was straightforward or contained a special request. While 46% of companies responded to both straightforward questions and special requests, nearly 1 in 5 (17%) only respond to standard questions. Interestingly, 6% of eCommerce companies only responded to special requests. This could signal that agents at these companies focus their time on complex and unique scenarios in the hope that customers will seek out self-serve support for simple, everyday requests.

How eCommerce Companies Measure up on the Support Performance Index (SPI)

 Our Support Performance Index (SPI) holistically compares a response against many key metrics. Overall, the SPI is 56.2 with a 23% scoring in the 70-85 range. Global action sports brand DC Shoes scored at the top of the chart, with an impressive SPI of 104.9, almost 5 points above the 100-point benchmark. The company excelled at all of the key factors, including an average response time of 20 minutes.

1 in 2 eCommerce retailers respond within 6 hours

Global eCommerce companies appreciate the need for speed: more than half of companies respond within 6 hours, and 75% of companies respond within 24 hours. The average response time for global eCommerce companies is 17.3 hours.

Zendesk users provide the best support 

More than all of the other agent desk platforms combined, eCommerce companies that use Zendesk perform higher on the SPI. Zendesk users scored 64.8 points on the SPI, compared to 53.5 for users of other agent desk platforms.

Conclusion

These eCommerce benchmarks highlight the daily deficit between customer expectations and reality. Artificial Intelligence (AI) is one tool that e-commerce brands can use to help lessen the gap during these regular times. The importance of AI is heightened on Black Friday and Cyber Monday when brands must handle a surge in business. In either case, companies have a lot of work to do when it comes to providing support on the most preferred digital channel: email.

Learn more about the state of eCommerce email support by getting your copy of our Customer Service Benchmark Report here.

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

Written by Emily Cummins  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

New eBook: Online Games and the New Imperative for Customer Experience

Written by Emily Cummins  on   Nov 3, 2020

Online game companies are facing greater competition from other game companies and from streaming media companies, both of which seek the attention of users. Sony, Microsoft, Apple, Google, Epic, Steam, Nintendo, and many others compete for gamer attention and dollars – as are Netflix, Hulu+, and YouTube. 

An excellent Customer Experience and stellar Customer Support has become table stakes to attracting and keeping customers. Gamers expect responsive and knowledgeable support and quick resolutions to questions and problems. All of this is now expected in-game, without requiring a gamer to ever leave the platform.

Modern conversational AI can enable game companies and their support teams to dramatically improve the player experience with minimal training and using historical interaction data. Game companies that adopt intelligent and effective conversational AI will gain an unfair advantage in the fight to win, delight and keep customers. 

The Churn Dilemma for Gaming Companies 

Across all subscription services, churn is constant and rapid. Mobile games achieving more than a 4% retention rate after 28 days are doing a great job, according to GameAnalytic’s Mobile Gaming Benchmarks report. 

Respondents frequently cited having a poor experience or service issues as a key driver in decisions to abandon their subscription. Add to this the reality that signing up for a new trial subscription elsewhere often takes less than a minute, and barriers to churn have never been lower. 

In today’s fragmented landscape where people’s attention is fleeting and ever more valuable, games with better support will do a better job of keeping customers, incentivizing them to recommend the game to friends and to post praise for games online. Games that fail to adequately support and sufficiently delight customers also lose revenue; poorly served customers spend less and tend to leave faster. However, providing great CX is hard for gaming companies. 

Video Game Companies Struggle to Deliver Awesome Customer Support and CX

The online game industry faces the greatest customer service challenge for any industry in the world. In no other sector would a company face, quite literally, the rage of hundreds of thousands of angry customers, simultaneously, magnified in the echo chamber of social media platforms. 

There are significant structural reasons that make delivering stellar customer support and a consistently excellent customer experience exceptionally challenging for game companies, including the fact that gamers often support each other in outside forums. Additionally, game experience is dependent on underlying technology systems like cloud computing and the global Internet. Another challenge is that bugs in the code can’t be quickly and easily fixed in every instance. 

These are just some of the numerous challenges faced by game companies as they struggle to maintain high Customer Experience and Customer Support standards. 

The Opportunity to Adopt Conversational AI for Gaming Companies 

Gaming companies are starting to use Conversational Artificial intelligence (AI) technology to transform their customer experience and support. Based on Deep Learning and modern AI that is continuously learning and improving the way it responds to customer feedback and requests, newer AI systems can eliminate the majority of repetitive work for support agents, address many somewhat sophisticated queries, and allow human support agents to only focus on the most complex case for faster resolution of the thorniest problems faced by noisy and VIP customers.

Modern Conversational AI differs from first-generation bots that many gaming companies have deployed. Simple chatbots can answer questions triggered by keywords or by giving users a menu of topics. In contrast, modern AI that actually uses NLP looks beyond keywords and syntax to richer patterns and combinations of words to better comprehend actual intent. Rather than being rule-based, these newer NLP systems are trained from hundreds of billions of data points. This results in a much more meaningful interaction that resolves players issues in the moment. 

Conclusion: Uplevel Your Customer Support To Win The Game

In our new eBook, we touch on the pressures facing game companies to deliver stellar CX. Modern conversational AI technology can improve players’ CX and support experiences significantly, offering immediate resolutions to a range of issues within the game itself. This effortless support plays a key role in retaining gamers, at a time when competition has never been more fierce. 

Download your copy of Pleasing A Tough Crowd: Online Games and the New Imperative for Customer Experience today!