Of course, the headlines from the past three holiday seasons are the backdrop to the current retailing environment and the upcoming holiday season for businesses. But fortunately, the sense of crisis has faded for U.S. consumers. There’s not even a November election to distract shoppers.   

In some sense, the 2023 holiday season may be the most “normal” in years for online retailers. And that means opportunity to prepare your business for the holiday season and boost holiday sales.  

Prepare your business for the holiday season

According to Digital Commerce 360 research data, over the three-year period 2020-2022, the Top 1000 online retailers in North American generated $75 billion more in ecommerce revenue than they would have if pre-pandemic growth rates had continued.   

So what are retailers doing with all this extra sales revenue prior to November and to boost holiday sales? The Digital Commerce 360 August Strategy Insights, “The 2023 Holiday Planning Report,” digs into what retailers and small businesses are planning for the holiday season. A number of retailers are investing in the ever-buzzy artificial intelligence. Generative AI has taken hold of everyone’s interest, including those in the online retail industry. In “Will AI take over customer service this holiday season?” retailers discuss their investments in generative AI and how they expect it will help this holiday season.   

Communication always is key for online retailers, and especially when holiday-related purchases are in transit to shoppers. In “Keeping customers updated during the shipping process can make or break the experience,” retailers share how they’ve improved their shipping communications so shoppers can be confident that their purchases will arrive when the retailer promises, or that they will immediately be notified of any issues. This is especially important as businesses prepare for the holiday season.    

And, of course, the end note to the holiday season is always returns. This year, online retailers are making their return policies stricter, shortening the window or considering making sales final. “Retailers revisit return policies ahead of the holiday season” discusses this trend and provides examples of retailers opting to enhance their return operations.  

It’s also worth noting that online holiday season sales have slowed in the past few years, according to Adobe Analytics data.   

While the 2022 holiday season brought in the largest online revenue to date ($211.70 billion in web sales in November and December, according to Adobe) that represented only 3.5% growth compared with the 2021 online holiday season.  

So while the above-mentioned investments will likely improve the customer experience, customer satisfaction and customer retention, it may not lead to meteoric online sales growth this holiday season.   

Perhaps the best way online retailers can prepare for this “normal” holiday season is with reasonable expectations of neither a boom nor a bust, but a solid season.   

To read more about how online retailers are preparing for the 2023 holiday season, download the August Strategy Insights “2023 Holiday Planning Report.”

— April Berthene, Editor, Strategy Insights 

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So what are online shoppers thinking about apparel buying online and across channels? Digital Commerce 360 in conjunction with Bizrate Insights surveyed 1,003 online shoppers in June 2023 to see where online shoppers stand.

Seven in 10 online shoppers are buying at least the same or more apparel online

One can’t help but conclude that with one in three online shoppers spending less on apparel in stores year over year that digital is the beneficiary and may be for some time to come.

Shoppers frequent store favorites

Retailers must understand that customer retention has important implications for purchasing apparel, with half of shoppers asserting they have their favorite stores and frequent them. Companies will need to be aggressive to become part of any apparel shopper’s routine, but the good news is that it will be worth the effort.

An understanding of fit and sizing also supports such a notion as 38% will go to retailers where purchases have been made in the past when looking for specific products.

Shoppers acknowledge that they like to get something new (31%) and update their wardrobes seasonally (30%). The web provides an opportunity for 20% to browse trends online and for 19% to look for new brands. When it comes to specifics, 18% shop mostly for special occasions and make purchases for social activities. Just 11% say their purchases are work-related, and work-from-home models may be a factor as wardrobe demands have changed.

Money still matters for 20% as they track retailer markdown strategies and only buy on sale.

I’m surprised to see that a lack of sales associates in stores pushes only 10% of those surveyed to buy online, as it is certainly challenging to hire in today’s employment climate. Additionally, it’s interesting that a lack of in-store inventory drives online buying more by 25%. Just 14% prefer to take advantage of store pickup options. There are many dynamics to monitor as shopper sentiments often shift over time.

Online shoppers use a multitude of features when shopping for apparel/accessories online focusing on targeted information that aids selection

Shoppers like to zero in on products, and it’s efficient to use search filters such as sizing, color or type, as 56% noted. It’s also significant that 46% appreciate the ability to compare products. Fit tools are also valuable, as sizing can be one of the biggest challenges when buying apparel. The fact that 13% find the ability to customize products also important may be a response to that as well.

First and foremost, 66% call out ratings and reviews as being most important. In the same vein, 34% enjoy seeing photos from other shoppers. Zoom is also a standard among apparel shoppers at 54%.

Online shoppers are accustomed to knowing products will be delivered. Additionally, a majority cited accurate delivery windows as high on the list of important website features.

Merchandising was more limited in its value but still had a role to play with new products (34%), product recommendations (29%), top sellers (25%) and trending products (19%) delivering the following importance results. Content was least significant and saw the following lower penetrations with videos (13%), how-to guides (12%), and livestreaming (6%) lower on the importance scale.

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Apparel and accessory shoppers visit stores to see and try on products, save money and get products quickly

While the physical store is seeing sales decline, it still has a role to play for 63% of participants who enjoy trying on products while 59% appreciate seeing the merchandise in person. For 56%, it’s a timing issue when they need items quickly. Store shoppers are also likely to return products to the store (31%) as they prefer seeing a quick credit to their accounts.

Some shoppers want to have guaranteed inventory availability while the same number prefer to pick up in store (19%).

Money-savings always comes up strong. 45% cited their interest around in-store sales or promotions. Along the same lines, 43% don’t want to pay for shipping.

It’s nice to see that 28% of online shoppers want to support local/small businesses. There also appears to be a trust issue as 28% feel more confident about store purchases.

Online shoppers buy from a variety of retailers with Amazon attracting the most apparel, accessory and shoe shoppers

The ecosystem of players in this category is complex. Like many categories, Amazon manages to find itself dominating. 74% of our survey participants shopped for apparel on it.

Amazon is No. 1 in the Top 1000. The database is Digital Commerce 360’s ranking of the largest North American online retailers. Amazon is also No. 3 in the Online Marketplaces database, which ranks the 100 largest global marketplaces.

Department stores play a strong role in this category as well at 47%. Brands are also an integral online destination for 37%, along with specialty retailers at 36%. Mass merchants Walmart (at 46%) and Target (32%) are also entrenched sellers.

Marketplaces are also significant; 30% providing selling opportunities for large and small sellers alike. Price-sensitive sellers like warehouse clubs and off-price retailers are neck and neck at 23%. Resellers only saw 20% penetration, though gains are likely to come in the next couple years.

To bring Amazon’s impact further into focus, four in 10 apparel buyers purchased 26% or more of their online apparel purchases in the past year on Amazon. It certainly feels like this dominance just might continue into the foreseeable future.

Each year, we gauge how aggressive shoppers are in adopting online apparel services. In all honesty, I’m surprised at the low penetration of some of these other services given their longevity in the market.

One in four ordered apparel from a company outside of the U.S. Beyond that, 18% say they have purchased custom products online that were designed to their specifications, while 17% have purchased a used/previously owned product from an online consignment seller. Sustainability is seeing inroads, as 15% have purchased apparel from an online retailer based on their sustainability stance.

Two in three apparel buyers find the overall look and feel most important to their online buying

Tastes in online branding have evolved, especially in the past few years. This is powerful. 36% enjoy seeing a presentation of diverse models that mirror the population. The brand’s story and history has always had a role to play, and 34% of respondents find it important. It’s positive to see that in a category like apparel, 25% find a brand’s sustainability practices important. Beyond that, it’s charitable giving (17%), social and political views (17%), and diversity stance (16%). Fair trade views are of lesser importance.

Seven in 10 online shoppers care about sustainability, though their buying strategies vary

Looking further into sustainability, just 21% say they seek sustainably minded retailers, with 9% already buying and only 12% willing to pay extra. Half of the respondents care about sustainability, but they simply are not willing to pay the price. Of those, 17% won’t pay more and 33% do not seek it. The 29% who have no interest in sustainability may be hardest to move into a more positive camp. Hopefully, these shifts will begin to take place in the near term.

Four in 10 online shoppers avoid retailer customer service departments

Email and in-store interactions topped the list of those touchpoints most likely to drive conversion at 22%, with a phone call to customer service (at 19%) and live chat with a human being close behind (at 17%). Interesting to note that people were a factor, so I will be watching to see if more recent tactics like social media and bots become conversion drivers in greater numbers as one might expect.

Social media is not part of the shopping process for three in 10 online shoppers. It does, however, prompt advertising clicks, get shoppers inspired and allows them to learn from others and follow products.

40% of online shoppers purchase apparel and accessories on social media platforms. This, too, suggests that time will be required for revenue growth via social media platforms.

Getting on the customer’s “favorite” list

Online apparel and accessory buying is still poised for growth, though we shouldn’t count out physical stores just yet. These categories are served by a broad ecosystem of traditional retailers and brands, though Amazon once again manages to dominate. Branding along with the features and tools retailers make available are powering positive shopping experiences, though finding the right size remains an issue. There are certainly stories still to be written from sustainability to social media. Positive customer service is always in fashion and will serve all retailers — apparel/accessories and otherwise — well.

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Julien Hervouet

Since last summer, we’ve seen a boost in the availability of AI capabilities to the world, with the democratization of ChatGPT and generative AI models.

Today, powerful large language models (LLMs) are accessible to all, pushing the boundaries of natural language generation. This breakthrough in technology is a turning point, multiplying human efficiency and transforming customer experiences, while delivering substantial cost savings.

As businesses are urged to do more with less in challenging economic conditions, generative AI opens up new opportunities for growth. This continued growth is poised to be a game changer for businesses, transforming the way companies operate and serve their customers.

Conversational AI is ready to meet all-time-high buyer expectations

Mike de la Cruz

Conversations are changing: 73% of consumers believe AI can have a positive impact on their customer experience.

On their e-commerce journey, 53% of adults in the US are likely to abandon their online purchase if they can’t get a quick answer to their question. They expect instant responses at any time. Specifically, they expect resolution in (under two minutes for phone calls and less than one minute for messaging (source: BVA 2022).

As a striking 80% of customers admit they’ll switch brands after just one bad experience), brands have no choice but to deliver and meet those expectations to grow their business.

For the first time, it appears conversational AI is able to deliver on its promise to offer a high-quality user experience—and consumers are ready to adopt.

Generative AI will become a strategic competitive advantage for businesses

Facing the ongoing conversational AI revolution and ever-increasing CX expectations, brands have a great opportunity ahead.

Florent Gosselin

By designing customer journeys that place conversation at the center of the experience, and leveraging AI technology to positively impact their consumer and employee experience, they can gain a competitive edge, while improving their cost-efficiency and profit margins.

When brands choose to undergo this digital transformation, the business outcomes can be huge.

By deploying differentiated conversational experiences to impact their customer journey at scale, from discovery to purchase and support, in a unified and consistent UX across all messaging channels, they create a positive and sustainable experience gap over their competitors.

There are limitations: Brands need trusted generative AI

Despite the huge potential of generative AI, it is crucial to acknowledge its limitations.

Brands need to overcome three major challenges to harness the potential of these technologies and make it truly operable and trusted for enterprise businesses:

1 – Customize It

Generative AI is generic and global in nature, being trained by huge amounts of common-knowledge data available across the internet. To be successful, brands would need to provide business-specific data, like processes & policies, products & services, legal constraints, etc.) to train the bot. Brands would also need to train the bot to communicate in a way that aligns with its core values, like tone of voice and ethical considerations.

Generative AI is also creative and tends to improvise when it doesn’t have the answer, which can lead to inaccurate communication or biased responses. Brands need to provide a safe, trustworthy experience to their customers which requires them to create and define AI policy controls and safeguards.

2 – Connect It

Generative AI is a powerful technology but is still relatively isolated, which is a mistake. Brands have the opportunity to connect it to their ecosystem in order to amplify the value by:

• Connecting it to their business and knowledge data
• Leveraging it consistently to positively impact both consumer and employee experiences
• Making it omnichannel, available on any messaging touchpoint their customers are using
• Empowering it to escalate to human-led interactions when necessary

3 – Control It

Finally, generative AI tends to be a black box for its end users, but brands need complete transparency and control.

A new generation of AI monitoring capabilities need to be developed to evaluate the impact of generative AI across various areas, like business outcomes, customer & employee experience, adherence to policy controls, and so forth.

These new analytics capabilities will enable brands to continuously optimize both the performance of their generative AI and the way they operate as an organization.

Conversational generative AI will revolutionize the buyer and agent experience

According to a study last summer by technology research and advisory firm Gartner Inc., only 1.6% of worldwide customer interactions were automated through the use of artificial intelligence. But by 2026, that figure will increase to 10% and continue growing sharply over the next several years, Gartner projects.

By making automated conversations smoother and more efficient, generative AI can revolutionize online commerce, allowing brands to serve customers in new, innovative ways.

This year, we’ll see an explosion of fully automated and high-quality conversational experiences in ecommerce.

Every online shopper will eventually get access to their personal AI CoPilot, providing instant and trustworthy answers to guide them from product discovery to purchase to post-sales support around the clock.

Alongside transforming online shopping experiences, we believe this exponential growth of conversational AI will profoundly reshape the role of human customer service agents.

AI will not compete with humans; it will complement them. Agents will gradually see their roles reshape into AI-augmented super experts, intervening in high-value conversations that require unique nuance and expertise or to establish strong emotional connection with the customer.

Humans will always play a critical role in helping control and continuously fine-tune AI models, interacting themselves with AI CoPilot assistants to gain efficiency and ensure a seamless, trustworthy consumer experience.

Join the generative AI and conversational revolution

The transformative impact of generative AI on the future of ecommerce and customer experience is indisputable.

We’re at an inflection point where generative AI will be a massive enabler to accelerate brands conversational digital transformation, combining the best of AI and Human intelligence.

By implementing generative AI, businesses will unlock the immense potential to address both consumer and brand pain points that consumers and brands have been facing for years while sustainably increasing revenue.

Mike de la Cruz and Florent Gosselin contributed to this report.

About the authors:

Julien Hervouet is the CEO of iAdvise, an AI-powered conversational technology platform. Mike de la Cruz is the chief strategy officer, and Florent Gosselin is the chief product officer.

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So when Leslie heard about an artificial intelligence chatbot that could negotiate prices with its online shoppers, he was immediately interested. Automated negotiation technology is not widely used in North America, and Leslie knew it could help his small online furniture business of about 50 employees.

“It hits at a time when we are all talking about AI and what it means for so many verticals and for so many functionalities,” Leslie says.

In the furniture industry, the margins are often healthy and prices are sometimes negotiated, Leslie says. Consumers may be used to negotiating for a larger furniture purchase at the store, when interacting with a sales associate. Online, however, some shoppers may be more apt to look for discount codes. Others may try to contact customer service for a discount. As an online merchant, Industry West wants shoppers to have some wiggle room on price — if that’s what it takes to convert. But it doesn’t want to continually broadcast a sale, Leslie says.

“At the end of the day, we’re all trying to preserve our brand and not always saying you are on sale, but with ecommerce you have to be constantly on sale,” Leslie says.

Industry West has a pop-up on its site that offers 20% off for first-time customers who share an email address. It also will send a 20% discount code for shoppers via email for abandon carts. But for all other shoppers, or for shoppers who don’t want to give up their email address, Industry West launched an AI chatbot in February called Nibble.

How the Nibble AI chatbot works at Industry West

On product detail pages that are eligible for promotions, which Leslie says is about 70%-80% of its SKUs, Industry West shows a “Negotiate Price — Instant Chatbot” button underneath the Add-To-Cart button.

If shoppers click on it, they can start to negotiate with the bot, named Nibble. Industry West authorized the bot to agree to a certain level of discount that varies by product, Leslie says without revealing the discount. As part of its negotiation tactics, Nibble is trained to offer “proof points” of the value of Industry West’s products, such as its quality materials and its warranty program, Leslie says. If shoppers suggest $20 for a $500 product or even $250 for a $500 product, Nibble can be cheeky with its response. For example, it might say, “Low offers like that won’t make me generous.”

If Nibble and a shopper come to an agreement, the bot generates a unique discount code for that shopper that expires within 48 hours. When the shopper adds the item to her cart, that discount code shows up.

If the shopper and Nibble agree on a price, the AI chatbot will create a unique discount code.

Results of using the AI chatbot

Overall, Leslie is happy with the shopper engagement with the AI chatbot. The best news is that the average aggregated discount that shoppers agree to is lower than the 20% pop-up discount. It’s also lower than the maximum discount that Industry West authorized Nibble to offer. Leslie would not reveal how low Industry West programmed Nibble to go, but for some products, it is a higher discount rate than 20%.

Thousands of shoppers have interacted with the chatbot each month. 28% of shoppers who start a negotiation reach an agreement with the bot, Leslie says. Of that 28%, 11% go on to make a purchase. Put another way: 3% of shoppers who engage with the bot go on to make a purchase.

Industry West’s AI chatbot chats with shoppers in real time to reach a negotiated discount.

Leslie suspects more shoppers will use the bot the more Industry West turns it on. For example, during Memorial Day weekend, Industry West ran a sale with a banner ad on its site. That discount was the highest the retailer was going to offer. So, to avoid confusing shoppers about any potential hidden promotions, it turned off the Nibble bot.

The goal with Nibble is to save on some of its product margins. While the early results are encouraging, Leslie hopes to take it further. Eventually, he wants to lower that first-time customer pop-up discount to 10% and maybe have Nibble offer the maximum discount between 15%-20%. Then, if shoppers and Nibble come to an average agreement of 18%, the chatbot could help save the merchant even more margin, while shoppers are happy because they agreed to the discount.

Benefits of the AI chatbot

The benefit of having an AI chatbot is that it can react to scenarios in real time. For example, one shopper told Nibble that she had four bar stools she bought a few years ago, is happy with them and wants a fifth one. But she asked if she could have it at a lower price. The bot, not programmed on this specific scenario, responded with, “Of course, we’re happy to hear you have our product.” The discount was within its allowed range and it generated the code for the shopper. This scenario is exactly how Industry West would want one of its consumer service representatives to handle this scenario, and Leslie was pleased the bot handled this scenario in this way.

Rosie Bailey, CEO and co-founder of Nibble, says the Nibble chatbot is a hybrid of generative and more traditional artificial intelligence.

“We use our own models to create Nibble’s chat and also use generative AI in specific places,” Bailey says. “As a result, Nibble is more secure — and cleverer — than generative AI alone.”

Working with savvy shoppers

Some shoppers are smart and may know that Industry West offers a 20% discount to new shoppers. Those shoppers may try to get a higher discount out of Nibble. That’s fine by Leslie, who wants the chatbot to drive as many sales as possible.

“This person, what they wanted was 20.6%. If that 0.6% was all I needed to gain the sale, that’s amazing. I’m all for that,” Leslie says.

Similarly, Industry West wants the AI chatbot to consider margin rate in the future, which could help drive even more sales. Currently, the AI bot only factors in discount rate. For example, Industry West may be OK with giving a shopper a 35% discount on a certain product if it doesn’t exceed the margin rate it needs to maintain profitability.

Holiday season implications

Industry West has a live chat feature on its website where shoppers can engage with its human customer support team for any questions and issues.

By having this feature for the holiday season, some shoppers may use it to get a discount instead of contacting customer service.

“It will take some pressure off of chat,” Leslie says.

Typically, Industry West will start its Thanksgiving weekend Cyber sales around Nov. 15. But this year with Nibble, it could use different marketing language where shoppers could gain early access to its best discounts via negotiation. For example, Industry West could authorize the chatbot to give the low Cyber discount, but shoppers have to be able to negotiate to it.

“By using Nibble, we can show an early access sale without slapping a banner on our website come November first,” Leslie says.

Bailey says avoiding endless discounting is the main goal of many of its clients.

“Most clients are fed up with the ‘race to the bottom’ and feel discounting is a trap,” she says. “Nibble helps you escape this trap by still offering great value deals one-to-one to valued customers without being stuck in an endless discounting cycle.”

Nibble takes 2% of sales attributed to them, Bailey says. The bot is available as a Shopify app, which only took a day to integrate, Leslie says. Nibble has about 300 clients that are mostly online retailers in discretionary spending categories, Bailey says.

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Mo Abuali, Ph.D., senior director of digital, Wipfli

To gain a better understanding of how manufacturers can leverage AI for ecommerce and their business in general, Digital Commerce 360 sat down with Mo Abuali, senior director, digital, at Wipfli, a Milwaukee -based accounting and advisory firm. Over the course of more than 23 years, Dr. Abuali, who has a Ph.D. in industrial engineering, has helped manufacturers implement digital solutions, such as the Industrial Internet of Things, digital transformation technologies, services and training, as well as apply them within the supply chain. Abuali has worked with such companies as IBM Corp., Procter & Gamble Co., and Toyota Motor Corp.

Digital Commerce 360: How big a lift is it for manufacturers to implement AI across their business?

Abuali: Use of artificial intelligence has been increasing across manufacturing in terms of implementation and is adding value in quite a lot of use cases. When we look at industrial manufacturing, AI is being used to improve production, quality and maintenance, to name a few key areas. The whole idea is to use AI to solve business problems around improving uptime, scrap rates, overall labor efficiency, and operations.

In recent years the advent of ChatGPT and regenerative AI have sprung a new approach of implementing AI, impacting the back and front offices. AI is also starting to cover all areas of manufacturing, including ERP, ecommerce, the planning layer, human resources, and strategic planning, not just the factory. I advise manufacturers always to understand their priorities and the biggest business case for implementing AI. Many tend to start on the manufacturing floor, but some start in other areas, such as ecommerce, sales, and business development.

DC360: What are some of the ways manufacturers can use AI to improve strategic planning and research?

Abuali: In general, strategic planning and research could yield significant savings in time, money, and labor efficiencies. The whole purpose is to identify  your business’s critical processes and how AI tools can automate and streamline your processes.

AI utilizes computing power, the internet, and the cloud, and is able to collect and analyze huge amounts of data in seconds. If you feed AI the right kind of information and requests and connect it to the right places in your business systems, it can quickly generate, evaluate, and benchmark ideas and convert all that data, whether it be structured or unstructured, into insights and recommendations to make informed decisions.

There are many AI tools out there, such as ChatGPT, but there are a lot of other tools that rely on this regenerative AI model. For example, Microsoft has recently released Copilot, which is becoming entrenched in the digital tools we use every day, such as Office, and it allows people to do things faster,  including creating presentations, researching and writing text. Manufacturers now have a wealth of AI tools available, many of which are free to trial, but the questions are always: Do I have the internal skill sets? How can I educate my workforce to use these tools correctly and validate the output of these AI tools?

DC360: What are some of the ways manufacturers can use AI to improve internal communications?

Abuali: One of the frequent use cases in this area is how to automate repetitive tasks. If you have to write a specific email to communicate internally or externally, for example, that email can be automated, personalized, and set up in terms of workflows based automatically on people’s responses. If there are non-responses, the email can be automatically resent. AI can be used to automate workflows that are intelligent to sense, learn and automate repetitive, time-consuming tasks.

Another area is around content creation: using AI to research or summarize very long articles or documents or even create communication documents. But validating the output and making sure that the content is reviewed by a real person is crucial.

A third area where AI can improve communications is through corporate intranets. Many employees go to intranets to access benefits and other company information. In this instance, there are chatbots and AI tools that can answer frequently asked questions and quickly guide the employee, and, if all else fails, can connect the employee to a live person to answer more complex questions. AI can be applied across all communications channels, including social media and websites.

DC360: How can AI be used by manufacturers to improve their ecommerce site?

Abuali: AI tools are good at recognizing patterns, so they can provide insights on what people are buying and understanding the different buyer personas and buyer segments. By understanding the historical data on a buyer’s previous purchase, AI can start to generate predictive insights on stocking, inventory, demand, as well as supply chain issues you could face if certain products are being over-purchased or under-purchased. Those insights could lead to more optimized scheduling and supply chain activities, which is a big issue facing manufacturers.

Another area is recurring activity, such as purchasing the same product over and over. Automating this activity by offering an option to save 5% on a customer’s next purchase by converting a one-time transaction to a subscription, for example, can convert the purchase into an automatically recurring one.

Another way AI can improve the ecommerce experience is using chatbots to handle returns, warranty information, and recalls. AI solutions can easily manage these situations.

DC360: You mention chatbots as a tool that can automate a lot of tasks around customer interactions. Are there concerns that AI-based chatbots may misuse customer information or steer customers in the wrong direction?

Abuali: There are cybersecurity concerns around chatbots, generative AI and Chat GPT in general. Chabot data could be used by third parties without the customer’s knowledge or consent. This is where folks need to read the fine print and agree or disagree to their data being utilized or sold. Many of us don’t take that level of caution when using those tools, but we should.

Data gathered through AI tools can potentially be used for targeted advertising or other purposes through cookies and many users may not be comfortable with that. At Wipfli, we have a cybersecurity team that is evaluating vulnerabilities. One of those vulnerabilities could be AI tools, such as chatbots, and how they could be impacting the user experience in a negative way.

DC360: How can AI be used by manufacturers to improve search and SEO?

Abuali: It comes back to understanding user behavior, what people are searching for, and understanding their search personas and profiles. I can also run an AI search across competitor websites and start tracking their rankings and benchmarking their rankings versus my rankings and potentially capture new keywords that can bridge new content ideas based on those keywords. Companies can use competitive benchmarking  with AI to sense what competitors are doing around search engine optimization and improve their own SEO.

AI can also  generate SEO content briefs faster and, in some cases, fully automate the process as the AI solution learns those SEO content activities. In addition, you can leverage AI to create content that matches SEO needs and improve SEO rankings compared to a competitor’s SEO rankings. It’s a great tool for the marketing department’s strategy to improve inbound and outbound marketing communications.

DC360: What are some of the ways manufacturers can use AI to improve branding?

Abuali: One good thing about branding is the ability to track customer activity around multiple channels, such as the website, mobile apps, social media. The ability to track data across those multiple channels and populate that metadata to understand personas and buying behaviors provides insights into how you can improve those channels’ usability to generate more sales and qualified leads.

Another area is better customer care. Through tracking customer activities across multiple channels, you can then address whether there are concerns with certain products and customers. This technique could improve customer trust in your products and your confidence in leveraging AI over time.

Brand reputation is also a key area. AI tools can help a manufacturer to understand how their online brand is being perceived and take action to improve the online brand, and  gain insights into how their online brand reputation compares to that of their competition. AI tools have also been used to enhance the customer experience, such as in the ease of finding products, reaching customer support, or handling returns and recalls.

The biggest use of AI from a branding perspective is tracking customer activity, monitoring and improving brand reputation, and delivering a better customer experience and customer care.

DC360: What advice would you give to manufacturers thinking about implementing AI solutions?

Abuali: AI solutions have a variety of applications, but it’s important for manufacturers to think big and ask what is their vision for the use of AI, then assess their digital maturity to embrace this technology. Thinking big and having a vision allows manufacturers to start small, pick the right area to start implementation, and pilot the solution in a strategic way while keeping the business case in mind to make sure you deliver your return on investment, then scale. Scaling requires internal resources to be trained and well-versed with these types of solutions, allowing for quicker scaling.

Then go on to the next area or use case. In other words, rinse and repeat in a strategic way.

Bill Boucher

Editor’s Note: Dr. Abuali’s colleague Bill Boucher, national industry leader and partner at Wipfli, will moderate a panel discussion on June 22 entitled, “Digital Strategies For Building Resilient Supply Chains,” at the EnvisionB2B 2023 Conference & Exhibition in Chicago. The panel will discuss AI, IoT and other technologies helping B2B businesses build better connections with suppliers.

Peter Lucas is a Digital Commerce 360 contributing editor covering B2B digital commerce technology and strategy.

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Maeve Condell

There was the world before ChatGPT, and there is the world after ChatGPT.

In fact, ChatGPT’s emergence is being hailed as the next Industrial Revolution. With over a billion visitors per month, this generative AI tool is being rapidly adopted in fields ranging from creative industries like graphic design and content writing to more technical roles such as software development. Its potential has continued expanding into other arenas, including customer support.

No doubt, generative AI is the future of CX. And with 88% of business leaders reporting that their customers’ attitudes towards automation have improved over the past year — it’s no longer a matter of if you should look to automate your support but when.

The benefits for B2B ecommerce brands are clear. Since 80% of customers identify CX as a key differentiator and think it is just as important as products or services, gen AI is a crucial way to improve your customer support offering and get a leg up on your competitors. Yet, because this technology is relatively new, and many B2B companies have more complex product packages and setups, you may still be wondering how, in practice, generative AI can enhance your customer support.

First, let’s take a look at what makes generative AI tools like ChatGPT so much better than their predecessors in simulating human-like conversations. From there, we can better understand how this technology can optimize your customer support.

Generative AI’s technology and how it works

Before we explore some of the best use cases for generative AI in the B2B ecommerce support context, it’s a good idea to understand what the technology is and how it works. Gen AI refers to the particular iteration of artificial intelligence that powers tools like ChatGPT — as well as a growing host of other bots like DALL-E, Google’s Bard, and MidJourney. Gen AI is distinct from previous forms of automation because it enables bots to hold impressively natural conversations. This is because generative AI draws on large language models (LLMs) that, in the case of ChatGPT, have even passed the Turing test, a method of proving machine intelligence.

But what exactly is an LLM and why is it so revolutionary in the AI space? What sets these models apart is the use of “transformers” (as if there wasn’t already something so sci-fi and “Marvel-esque” about this technology). Transformers effectively mimic human conversational style because they can process all inputs simultaneously rather than needing to be fed data sequentially. This means that, in the case of ChatGPT, the bot can process all of the written content on the internet (up until 2022) to generate the answer to a given prompt. This holistic processing capability allows it to produce responses with the context and tone you expect when talking with a regular person.

As you might have guessed by now, this can be especially useful for customer support automation. This is because a virtual agent that uses generative AI can seamlessly mimic your brand tone of voice as well as the conversational style of your human agents. As a result, you can offer an improved conversational experience for customers, make your support agents’ lives easier, and provide your customers with more than ever before.

The top 3 generative AI use cases revolutionizing CX in the B2B space:

1 – A more advanced conversational experience for customers

With generative AI offering such natural and human-like conversations, you don’t have to worry about automation damaging the customer experience with your brand. With the help of generative AI, the virtual agent can instantly pull info from your FAQ pages, knowledge base, help center, or any other company page — and serve this to customers in a natural, conversational way. There’s no training required, and you can get started in minutes.

As long as a topic is covered in your help center, the bot can process all of the articles available to answer customer queries. So, if a customer asks, ‘Where can I find and download my last invoice?’ the bot can instantly provide instructions.

In this scenario, your customers can have their cake and eat it too — by getting the information they need much more quickly through self-service, without losing the conversational format of speaking with a human agent. This will boost your automation rate, while ensuring that your customers still feel supported with high quality customer service.

2 – Assisting support agents

While a virtual agent powered by generative AI may be able to effectively do the work of several human agents, it doesn’t mean that they will be replacing them anytime soon. Rather, automation serves as a tool that can help agents to do their jobs better. For instance, a virtual agent that uses generative AI can offer a more seamless transition from bot to human agent by helping to structure, summarize, and automatically populate tickets so agents don’t have to. This will lead to much faster response times and a cleaner handover to agents in cases the bot can’t fully resolve. In addition, agents can prompt generative AI to offer suggested replies that help them to draft responses more efficiently.

These things can be a major game-changer in the event of an uptick in queries, unexpected or otherwise. This makes automation useful for answering simple questions like order status or requesting a password change. It also helps to free up agents’ time to deal with more complicated issues. For B2B ecommerce brands where queries can be complex and technical, having a primer from the bot allows agents to hit the ground running when addressing customer issues. With the help of generative AI, the bot assists your agents in having better and faster insights into customers’ needs and helps your team work more efficiently.

3 – Understanding your customers and what they’re asking

Lastly, generative AI will help you to educate your customers and offer them even more value than they were expecting from interactions with your support team. Businesses often shop around between different suppliers before making a purchase, so you want them to discover the unique selling point of your product offerings as quickly as possible. This discovery process is where generative AI comes in. It can comb your existing content to offer useful, educational suggestions to answer any pre-purchase questions. It can also provide such content to busy support agents when prompted. Through the transformer model that powers it, generative AI can instantly serve up this information without needing to be manually updated as you publish new content on your site.

Conclusion

Generative AI is the latest and most sophisticated edition of automation technology, and it has real potential to optimize the B2B customer experience. In particular, it has the capacity to mimic natural conversations, assist your agents in structuring support tickets, and provide customers with an enriched support experience — all without hiring any extra agents. It’s a time-efficient, affordable, and scalable solution to mitigating long wait times, depersonalized CX, and clunky self-service offerings. While the technology may be new, the sky is hardly the limit on its potential for supercharging your CX as the number of applicable use cases only continues to grow.

About the author:

Maeve Condell is a solution architect at Ultimate, a customer service automation company. Her focus is on combining AI and conversation design to build personalized virtual agents.

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Kris Harrington

In today’s dynamic business environment, staying competitive requires a more dynamic approach to utilizing your organization’s valuable resources. As an original equipment manufacturer or after-sales leader, your teams should be focused on delivering exceptional products, enriching customer experiences, and driving revenue growth.

However, some companies still rely on outdated practices, operating as mere ‘order-takers’ and spending a significant amount of time on administrative tasks, rather than adding value to their customers. And adding value can make a massive impact for OEMs.

If your organization is more focused on order-taking tasks than creating value for your customers, you may be at risk of falling behind. Here are three telltale signs that your organization operates as an “order-processing center”:

● Customer service teams are spending most of their time responding to customer inquiries for parts identification, price, availability, and order-related tasks.

● The organization is relying heavily on manual workflows and paperwork to manage orders, returns, and warranty claims.

● The organization is not leveraging technology or automation to streamline processes, reduce errors, and improve customer experiences.

So, what can you do to move away from an order-taking culture and start focusing on value-adding activities? Here are five things that OEM and after-sales leaders should consider:

1–Implement a digital self-service platform. One of the most effective ways to reduce the burden of order-taking on your customer service teams is to provide customers with self-service options. This can include customer or dealer portals that allow customers to access product information, place orders, track shipments, and request support without having to engage with customer service representatives every step of the way. By enabling users to self-serve, you can reduce the volume of calls and emails your customer service teams receive and free up their time to focus on more strategic activities.

2–Automate order processing and fulfillment. By integrating EDI and ERP systems, businesses can streamline operations, reduce errors, and improve customer satisfaction. For example, automated order processing and fulfillment allow companies to allocate inventory, generate pick lists, and create shipping labels automatically. This automation helps reduce the burden on customer service teams and will let them focus on more strategic initiatives. Additionally, automation provides real-time visibility into inventory levels, order status, and delivery tracking, which enables businesses to manage their operations and improve customer service proactively.

3–Use data analytics to anticipate customer needs. Rather than waiting for customers to contact you with their needs, you can use data analytics to anticipate their needs proactively. By analyzing customer behavior and buying patterns, you can identify which products or services they are likely to need next and offer them personalized recommendations or promotions that encourage repeat business. This use of analytics can help you build stronger customer relationships, increase revenue, and reduce the need for reactive order-taking.

4–Invest in training and development for customer service teams. While digital self-service and automation can help reduce the burden of order-taking on your customer service teams, they still play a critical role in ensuring customer satisfaction. That’s why it’s important to invest in training and development programs that equip your customer service teams with the skills and knowledge they need to handle complex inquiries, resolve customer issues, and provide exceptional service. By empowering your customer service teams to add value, you can differentiate your organization from competitors and build a loyal customer base.

5–Create a culture of continuous improvement. Finally, it’s important to create a culture of continuous improvement that encourages experimentation, innovation, and collaboration across your organization. This can include regularly reviewing and analyzing customer feedback, identifying areas for improvement, and testing new processes and technologies to drive efficiency and customer satisfaction. By embracing a culture of continuous improvement, you can position your organization for long-term success and move away from a culture of order-takers to a culture of value-creators.

The pressure to deliver more value to your dealers and customers is greater than ever, and organizations that fail to prioritize this customer service strategy risk losing market share. By implementing the steps outlined in this blog, OEM and after-sales leaders can optimize their operations, improve customer experiences, and set themselves up for success in the years to come.

About the author

Kristina Harrington is the co-founder and CEO of GenAlpha Technologies, which provides digital commerce technology for manufacturers. Prior to GenAlpha, Kris worked for more than 10 years in leadership positions at two large multinational original equipment manufacturers, Bucyrus International and Caterpillar, supporting the mining industry. In her various positions, she worked with internal stakeholders, dealers, and customers to deliver business results both in aftermarket and equipment sales. She can be reached at kharrington@genalpha.com.

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Emily Newton

Many new ChatGPT supply chain applications are emerging as generative AI becomes more advanced. So how can industry professionals utilize this technology effectively? They can use ChatGPT in several critical ways, primarily communication and automation.

1. Supply Chain Customer Service

Customer service is one of the most promising applications for ChatGPT in the supply chain. The natural language processing capabilities of ChatGPT are among the most advanced ever developed for popular use. This makes it an ideal tool for navigating the complex communication required in customer service tasks.

Any developer can integrate ChatGPT into their apps today using OpenAI’s official API for the algorithm. ChatGPT’s language processing skills can be applied to any customer-facing application in the supply chain, whether B2B or B2C. For example, a supplier could create a ChatGPT app for its manufacturing customers to track shipments of materials and resources.

2. Translation and International Relations

Succeeding in today’s supply chain requires working closely with partners worldwide. Unfortunately, language barriers make this challenging, potentially hindering organization and efficiency. Luckily, translation is a great way to use ChatGPT in the supply chain.

Research shows that users don’t need to specify the source language of a text passage for ChatGPT to translate it successfully. The algorithm can autonomously detect the source language and translate it in seconds.

ChatGPT’s performance is also on par or better than most digital translation tools available today. The fact that it can process natural language, including advanced technical terminology, gives it a major advantage over competitors. Its accessibility makes it ideal for supply chain applications, which rely on quick turnaround times and clear communication.

Using ChatGPT for translation can strengthen collaboration with international supply chain partners, improving efficiency and organization for everyone involved.

3. Automating Business Tasks

Businesses can use ChatGPT in the supply chain to automate various everyday tasks. For example, it can summarize a sales report, extract the highlights from a spreadsheet or draft an email. These tasks might seem small, but they help supply chain professionals work more efficiently.

ChatGPT can even be helpful for complex logistics tasks. AI is already making advances in logistics. For example, algorithms can automate order processing and help managers identify important insights in their data. This could include tasks like analyzing a list of suppliers to find those with the best rates or assessing various packaging options for the most cost-effective solution.

ChatGPT takes existing applications for AI in robotic process automation a step further. Advanced natural language processing helps it handle more complex content and user requests. Even integrating it into a larger automated system could improve performance.

4. Personalized Employee Training

ChatGPT is a great tool for improving employee training. This is especially helpful today since many supply chain businesses are adapting to new technologies and grappling with labor shortages. Surveys show 57% of supply chain leaders report hiring and retaining employees as their top challenge. Additionally, 41% have issues upskilling or reskilling existing workers.

Supply chain businesses can help alleviate these challenges by integrating ChatGPT into their training programs. It can serve as a multipurpose assistant for trainees by answering questions, explaining complex topics, and creating practice tests and flashcards. Employees can use ChatGPT to get a personalized training experience catered to their needs and learning styles.

Some trainees might quickly grasp a new technology, while others will want more time to explore definitions, technical terminology and other background information. ChatGPT can serve various training approaches, making it a versatile tool for providing more efficient employee training.

5. Data Analysis and Visualization

Data analysis and visualization is a lesser-known application for ChatGPT in the supply chain. Most people think of it as a language-specific AI, but it can also process numerical data.

Rapid and accessible data analysis tools are vital today. Data-driven insights and decisions are a cornerstone of Industry 4.0, which is rapidly reshaping the supply chain. ChatGPT makes basic AI analytics quick and straightforward. Anyone can paste a set of unstructured information into ChatGPT and ask it to summarize or organize it into a table.

Automating this task allows supply chain employees to have a more efficient workflow and leverage data more easily. ChatGPT can’t do complex data analytics yet, but it can handle many basic processes that are helpful for quickly getting an overview of a data set.

6. Idea Generation

Idea generation is a unique application for ChatGPT in the supply chain. Businesses need creative solutions to new challenges as things become more complex. Generative AI platforms like ChatGPT can be surprisingly helpful in the brainstorming process.

An AI might pinpoint unconventional solutions or ideas a human would not have considered. ChatGPT’s suggestions may not always be usable or feasible, but they provide a unique perspective that can spark creativity among team members.

Potential Drawbacks of ChatGPT

ChatGPT may be a powerful tool for certain applications, but it isn’t perfect. Business leaders should know about the drawbacks and challenges of adopting ChatGPT.

For example, ChatGPT has been known to give users inaccurate or completely made-up information. The AI’s language processing skills allow it to convey this false data convincingly, making it challenging to detect accuracy at a glance. Some groups, such as the coding help site Stack Overflow, are even banning ChatGPT due to the spread of misinformation.

This broadcast ofmisinformation is a huge problem in applications where users may be poorly equipped to verify that ChatGPT’s generated text is accurate. For example, using the AI for translating could lead to confusion if ChatGPT misunderstands the input or output language. Similarly, a new employee using ChatGPT for job training might learn incorrect information due to answer errors.

These issues may improve with time. The latest version of ChatGPT, GPT-4, is reportedly 40% more likely to give factual data, according to developer OpenAI. However, it will likely take years for ChatGPT to become a reliable source of information. Even then, there is always a chance the AI could “hallucinate” incorrect conclusions from the given data. ChatGPT’s output should always be fact-checked.

Adopting ChatGPT in the Supply Chain

There are many ways to use ChatGPT in the supply chain today, ranging from translation to employee training to logistics automation. Businesses can improve efficiency and productivity by integrating it into their workflows. OpenAI offers an API any developer can use to build ChatGPT into their app or website. In the years ahead, more supply chain applications will likely emerge as the technology advances.

About the author:

Emily Newton is an industrial writer reporting on how technology disrupts industrial sectors. She’s also the editor-in-chief of Revolutionized, covering innovations in industry, construction, and more.

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