Retail ecommerce sales are expected to reach $8.1 trillion by 2026. This means more ecommerce players will join the already crowded space.
In other words, even higher competition.
Therefore, retaining customers would become the key differentiator for brands. It will naturally turn into an innovator's game. The one who can innovate faster and offer better customer experiences will more likely be the winner.
So, now more than ever, online retailers and ecommerce brands are looking at improving their ecommerce platforms to retain customers. Artificial intelligence (AI) and machine learning (ML) are key components of the underlying infrastructure that brands and retailers are using to keep customers engaged and offer them the most optimal experience.
AI and ML are expected to generate $360.36 billion in revenue by 2028.
Moreover, ecommerce has come a long way since Amazon first started using AI and ML for its product recommendations around two decades back.
Today AI/ML has become an irreplaceable part of how we shop online. We have finally started moving from AI hype to reality, with many working solutions entering the market.
Based on our research, here we have compiled a list of the top 5 machine learning trends in ecommerce that are likely to define customer experiences in 2023 and beyond.
Knowing these trends would help you focus on what's relevant and how to offer the same expectations to your customers.
Machine learning in ecommerce: Key stats
Let’s look at a few numbers that suggest how machine learning is being adopted in the ecommerce industry:
- 56% of survey respondents report adopting AI and ML in at least one business function. (Source: McKinsey)
- 84% of ecommerce businesses are either actively working at adopting AI/ML solutions or have it as a top priority. (Source: Statista)
- $16.8 billion is the expected market size for AI-enabled ecommerce by 2030. (Source: InsightAce Analytic)
- 25% improvement in customer satisfaction, revenue, and cost reduction will be seen by the majority of organizations using AI and ML for digital commerce. (Source: Gartner)
- 54% of executives say that AI/ML solutions have increased their business productivity. (Source: PwC)
- 58% of customers worldwide look for personalized offers powered by AI/ML. (Source: Salesforce)
- $15.13 billion is the expected market valuation for the ecommerce recommendation engine by 2026. (Source: Mordor Intelligence)
- 40% reduction in logistics errors was reported by Alibaba after using AI/ML. (Source: HBS)
- 95% of all customer interactions are predicted to be powered by AI/ML by 2025. (Source: Servion)
- $13.9 billion is the expected market size for conversational AI by 2025. (Source: Business Wire)
- 41.3% of users in 2020 used chatbots to make a purchase. (Source: Drift)
Top 5 machine learning trends for 2023 and beyond:
Increase in voice-enabled shopping and voice search
As part of ecommerce machine learning trends for 2023, voice-enabled shopping is on top of our list.
AI/ML powered voice assistants like Siri, Alexa, and Google have become household names and are being used by millions of people every day. The smart speaker product category has become insanely popular within a very short time.
As per the new NPR and Edison Research 2022 Smart Audio Report, about 100 million people in the US own at least one smart speaker. This accounts for 35% of Americans over the age of 18 who own a smart speaker.
Moreover, 62% of adult Americans use voice assistants and voice search in some form or the other when smartphones, TVs, cars, and computers with voice assistants are included.
This effectively means that voice search has gone from a gimmick to a useful feature, allowing users to get their queries sorted instantly. By 2023, it's estimated that half of the internet searches will be conducted via voice commands.
Voice search is changing the way we interact with search engines and ecommerce websites as we prefer to speak our queries aloud instead of typing in keywords. It also creates a more casual, engaging, and enjoyable experience than simply typing, making it a preferred option for customers.
Since voice search lends itself to conversational phrases, it helps people find the products they need more quickly and efficiently. Using voice assistants enhances the effectiveness of the checkout process.
As more and more consumers get comfortable with AI assistants, voice-enabled shopping will continue advancing at a steady pace. We are going to see further refinement of natural language processing (NLP) for understanding complex voice queries and providing more accurate results. This will result in surfacing products and recommendations that are more likely to result in a conversion.
In fact, the total worldwide transaction value for ecommerce purchases made through voice assistants is expected to reach $19.4 billion by 2023. This is a 400% growth in just 2 years enabled by the increasing opportunities for voice assistants to purchase items from their smartphones and smart devices.
So, it's clear to see that the trend of voice shopping is only going to become more popular in 2023 with the growing usage of voice assistants and smart devices.
Increased adoption of AI chatbots
AI/ML-powered ecommerce chatbots have been around for a long time now and are nothing new. Yet, in 2023 and beyond, we are going to see these chatbots become more relevant than ever, with many interesting applications likely to come up.
Since customers want to be attended immediately, making them wait to talk to an actual human does nothing for improving the customer experience. They expect 24/7 support and AI chatbots can help deliver it.
That’s why online retailers and ecommerce sellers are increasingly relying on these smart ecommerce chatbots to automate customer interactions, engaging customers at every stage of their journey.
No wonder online retail has the best chatbot adoption rate across industries standing at 34% which is more than any other industry. The graph below highlights the same.
Chatbots are ideal for facilitating conversational commerce and leveraging conversational interfaces to deliver an enhanced shopping experience. So, in the coming years, more and more online storefronts and retail businesses will integrate chatbots because of the convenience they offer.
Use cases of ecommerce chatbots in 2023
According to our research, chatbots will be increasingly integrated into our daily lives to create seamless experiences while online. Some of the most interesting use cases that we will see in the coming year includes reducing long wait times, offering product availability on a store-by-store basis, and providing on-demand assistance and support based on where a customer is in the buying journey.
Chatbots are now being used all over the world as powerful tools that empower human customer agents and support teams by taking some workload away from them so they can focus on business-critical issues that only a real person can resolve. They will only continue to evolve from here.
Increased use of real-time data analytics
Real-time data is the data that's available as soon as it is generated. So, rather than being stored, it's forwarded to the relevant party instantly. This is crucial in supporting live, in-the-moment decision making. That is why we are going to see real-time data become more popular in the coming years.
It will be especially valuable for ecommerce businesses as they can use this data to improve customer service, manage products, or optimize operations. It will also enable organizations to obtain more comprehensive visibility into the performance of their complicated operations.
Forward thinking brands and retailers, looking to improve supply chain management and inventory management will start utilizing real-time data to analyze which products are in demand or which products need to be moved off their shelves.
Data will be aggregated based on what customers are browsing through brand websites and other channels in real time. With machine learning, these data points will then be analyzed to provide actionable insights on important areas for brands to focus on. For example, offering personalized discounts, promotions, or special sales.
On a deeper level, brands will use machine learning to predict more granular trends. For example, using real-time data, brands may realize that a particular kind of round collar t-shirts are all the rage.
So, they will anticipate customer demand and accordingly make inventory decisions. This will not only benefit their brand but also the customers by optimizing their shopping experience.
As real-time data becomes an increasingly valuable source of information for ecommerce businesses, this trend is only going to increase.
One thing to keep in mind though is that it requires more sophisticated analytics infrastructure or in other words, it would be more expensive. However, the benefit is that you can act on information as soon as it happens.
This could involve analyzing data from visitors to your website to work out what offer or promotions to put in front of them or to do on-site personalization for individualized experiences.
Companies with more advanced data strategies will look for more up-to-date and real-time data. That's why real-time data and analytics will be extremely valuable for businesses in 2023.
Personalization throughout the customer journey
Whether you are in B2B or B2C space, your audience expects a level of personalization and specificity. In 2023 and beyond, ecommerce brands and retailers will use data more than ever and leverage data-backed insights to deliver personalized experiences to customers.
Let’s look at two examples.
Stitch Fix is an online fashion company that uses recommendation algorithms, machine learning, and data science to personalize clothing items for its customers based on size, budget, and style.
This California-based fashion retailer can create customized clothing that, in theory, will perfectly match the customer's taste.
Similarly, Nike By You is a service launched by sportswear giant Nike, that allows customers to create a completely customized pair of sneakers or football jerseys matching their individual tastes.
These both are great examples of ecommerce brands capitalizing on the growing demand for personalized and unique products that reflect the personality of the customer or an individual sense of style.
So, in 2023, we are likely to see personalization being adopted at this scale by more ecommerce brands. Since consumers have been shown to respond well to personalization, brands will look at incorporating it throughout the customer journey.
This would include sales and marketing as well. So, personalization will be seen in recommendations, shopping, emails, guides, upselling, after-sales support, etc.
Businesses that will benefit the most from adopting this trend in 2023 will be the ones that will understand how to take the myriad data points available today and create products that appear uniquely tailored to their customers.
Creating personalized touch points across the customer journey will help make customers feel more attached to the brand.
Applying personalization at scale will thus be a key trend in 2023.
Using generative AI in ecommerce
Generative AI is all the rage right now. MIT describes it as one of the most promising developments in the field of AI/ML in the past decade.
It refers to a set of machine learning techniques and algorithms that can read data and use this data to generate synthetic content like images, text, audio, video, etc. It can ensure the creation of high-quality output data by self-learning from a dataset.
A popular technique used in generative AI is called generative adversarial networks or GANs. These are algorithmic architectures that use two neural networks and pit them against each other to generate new, synthetic data.
Let's look at how GANs will be used in ecommerce in the coming years:
Creating fashion models with custom outputs: GANs can be used to create high-resolution images of fashion models with customized outfits and poses. Using generative AI, brands will be able to create images of models that fit with the company's brand. They will be able to create their own 'artificial' social media influencers.
A Berlin-based fashion company called Zalando already uses GANs to produce high-resolution images of virtual fashion models.
Improving product descriptions: GANs will turn out to be a convenient tool for generating marketing texts and rephrasing product descriptions. Similarly, GANs will also be used to convert text to images and generate product images that match the textual descriptions.
Creating personalized marketing content: As discussed before, personalization is extremely popular with customers and the demand for such customized experiences is only going to increase. So, GANs are expected to be extensively adopted in ecommerce to generate personalized images, 3D objects, cartoon characters, video content, and much more.
While still in its early stage, generative AI will definitely be an interesting trend worth keeping an eye on in 2023.
These were some of the top trends we think will dominate ecommerce in 2023. While some of these might be a continuation of current trends, others are new and unique to the coming year.
Also, this was not an exhaustive list by any means. We only talked about the top 5 machine learning trends that we think are likely to make an impact on ecommerce in the coming years.
Since technology never stays dormant, there are many other interesting developments happening in the field of AI/ML. Here are a few other use cases of machine learning in ecommerce that we might witness next year:
- More intuitive and engaging visual shopping experiences
- Smarter upselling and cross-selling
- Improved fraud detection and prevention
- Dynamic pricing powered by machine learning
- Intelligent visual search
- Churn prediction
- Shopping in the metaverse
- Delivery optimization and autonomous vehicles
Regardless of what technology ecommerce companies choose to integrate into their business, what stands out is the fact that the most important aspect is to deliver an excellent customer experience. As long as companies can achieve it, they will find it easy to sustain themselves.