AI and Online Retail: The Future of eCommerce Automation
The eCommerce market is booming. But with this expedited growth comes fierce competition, so the ability to pivot in real-time and make each shopper's journey to the checkout personal and seamless is essential. This is where AI for eCommerce comes in.
With as many as 70% of online business owners already agreeing that AI for eCommerce helps their online shops with personalization, this technology is only expected to evolve and grow further, and quickly. It is believed that the global AI market is expected to reach $23.32 billion within the retail industry by 2027. And the reason for this quick AI growth?
More emphasis on customer experience
- An increased need for automation to compete
- Better access to big data
- Significant improvements in machine-learning technologies
In short, AI tools and technology have become an integral part of the online retail and eCommerce industry.
Ultimately, the future of eCommerce automation is not coming; it's already here. What’s important now is how DTC brands can capitalize on it to drive sales, dominate their niches, and improve logistics.
In this post, we look at the most critical trends and integrations of AI into online retail, and discuss how you can use important advances in technology and eCommerce to build long-term, sustainable growth. We will cover:
- Expanding AI Technologies and eCommerce
- Benefits of AI and eCommerce Automation
- Top eCommerce Uses for AI and Automation
Let’s jump in.
Expanding AI Technologies and eCommerce
Whether it's augmented reality for immersive shopping or smart product sorting and merchandising, there is no doubt that the focus of eCommerce AI is to streamline the shopping experience. This is largely thanks to quickly advancing technology.
Let’s look at the key AI technology advancements pushing the limits of online retail automation.
1. Machine Learning for eCommerce
Machine learning is a subset of AI technology that uses real-time data to make predictions or perform actions. The more data the algorithms get (“learn”) over time, the more accurate their outputs become.
Machine learning is the most widely used eCommerce AI technology, with the machine-learning market predicted to grow at a CAGR of 44% to $9 billion by 2022. Here are the five top ways machine learning is currently being used in the eCommerce industry
- Accurate real-time forecasting
- Optimized search results
- Dynamic real-time pricing
- Sophisticated fraud detection and prevention
- Advanced product sorting
2. Deep Learning for eCommerce
Deep learning AI is a subfield of machine learning that imitates the way humans gain certain knowledge types. An example of this technology being used in eCommerce is Amazon’s voice assistant, Alexa.
3. NLP for eCommerce
NLP (natural language processing) is another subset of machine learning. It’s the AI technology that enables machines to understand speech and patterns. Commonly used in voice assistance and chatbots, NLP technology is set to be worth $48.46 billion by 2026.
NLP for eCommerce’s main applications include virtual conversations, voice-activated payments, and voice searches. Additionally, NLP is currently being used in a variety of eCommerce automation mechanisms and tools, including:
- Semantic-based search and intelligent search functionality
- Chatbots and voice assistants
- Product categorization and description personalization
- In-depth data on shopping habits and behavior
- Automatic site language translations
4. Computer Vision for eCommerce
Computer vision is a new subset of AI that enables a computer to see things as well as users do. Simply put, it collects and uses data from visual inputs such as videos and photos. An example of this technology being used in eCommerce is augmented reality.
Additionally, it has essential applications in backend logistics, with computer vision AI being deployed in cameras and robots for better inventory management. Facial recognition is another adaptation of this technology, with one article stating that leading European retail companies have seen a 90% increase in customer insights by harnessing facial recognition.
Here is a breakdown of a few of the latest computer vision applications in online retail:
- Advanced Warehouse Automation: New computer vision logistics systems can help maintain inventory, count stock, alert merchandising managers, and more to help avoid human error.
- Visual Shopping: Image recognition enables users to search and label products with pictures, or take a photo of a product they like in the moment and buy it with visual search (object recognition).
- AR in eCommerce: Augmented reality is an interactive experience of a real-world environment where real-world products are enhanced by computer-generated perceptual information. Don’t be fooled by its “game-like” impression; a whopping 76% of Snapchat users say they want to use AR in their everyday lives.
Evolving Benefits of eCommerce AI and Automation
How is AI driving change in the eCommerce industry? In every way!
It’s no longer a question of whether or not to invest in AI technology, but how much to invest. The fact of the matter is that within the current eCommerce landscape, online retailers just can’t compete without it.
When McKinsey and the Retail Industry Leaders Association outline their seven imperatives for rethinking retail, all their points are supported by AI. Let’s break down the growing benefits of AI:
- Seamless Front and Backend Automation: With the right AI-powered tech stack, DTC online brands can automate vital eCommerce processes to adapt and optimize to shifting markets in real-time.
- Enhanced Customer Retention: Customer experience and retention are a driving force behind evolving eCommerce AI. Why? The more personalized the experience is, the more likely it is that a customer will buy. In other words, machine learning drives revenue. According to McKinsey, potential revenue and overall customer retention can be lifted by as much as 15% using personalization.
- Effortless Shopping: AI-powered tools continuously gather more personalized data to help move customers through the sales funnels more quickly.
- Laser-Targeted Marketing: With the continued development of AI comes the increased benefit of highly targeted marketing. The most robust PPC management software, for example, harnesses the power of machine learning to promote the right products at the right time to push sales.
- Simplified Operations: With increased eCommerce automation, online retailers can free up bottlenecks behind the scenes, streamline logistics, and optimize brand management.
Top eCommerce Uses for AI and Automation
As we mentioned, with the right 2022 automation tech stack, DTC brands can drive personalization and streamline operations to boost profitability. Simply put, with the right combination of AI technology, store brands can:
- Build innovative product collections beyond personalized product recommendations
- Enhance logistics
- Develop highly accurate sales and demand forecasting
- Establish more personalized customer service
- Harness the power of advanced customer segmentation
- Upgrade digital marketing and advertising to pro-level
All of these play a vital role in optimizing profits. Let’s take a deep look at these top eCommerce uses for AI technology and automation, and some of the newest eCommerce AI trends.
1. Build Smart Product Collections beyond Personalized Product Recommendations
AI has enabled online stores to use customer behavior metrics to present shoppers with personalized product recommendations. In fact, there are very few online retailers who aren’t using machine learning and other AI technologies to personalize the shopping experience with more shopper-centered product pushes.
However, as we head into the first holiday season of 2022, personalization just isn’t enough.
New AI tools like Kimonix take product sorting and online merchandising to a whole new level – beyond simple personalized product recommendations. How? By combining both retail and marketing KPIs to create smart product collections that adapt and optimize in real-time.
Or, more simply put, it uses advanced marketing and inventory optimization metrics to reduce non-moving inventory without disrupting conversion rates.
A brand that has had a lot of success using AI to build intelligent product collections is jewelry retailer Swarovski (IL). In just four weeks, they were able to increase conversion rates by 18% and reduce non-moving inventory by 29%.
You can read more about this case study here.
2. Enhance Logistics
AI-guided logistics is not new, but it’s growing. For example, in 2019, Shopify invested $450 million to expand its AI-powered fulfillment network with 6 River Systems. And since 2019, Amazon has increased its mobile drive units (warehouse robots) from 200k to around 350k.
This growth should not be surprising. By including AI technology into backend logistics, online retailers can streamline productions and processing, all while reducing costs. Machine learning has made it possible to forecast everything from demand levels to shipment delays, and then adapt or correct in real-time accordingly.
Known as smart or intelligent logistics, AI-powered logistics is also helping immensely with supply chain planning, which, as we know from recent delays, has been very cumbersome. IBM research found that as many as 40% of companies in their survey have been successfully resolving supply chain challenges using AI.
Here’s a small window into the different smart logistics powered by AI:
- Warehouse automation
- Equipment diagnostics
- Supply chain planning
- Production control
- Inventory management
- Order/purchase management
3. Develop Highly Accurate Sales and Demand Forecasting
The next area of eCommerce business that is being positively impacted by the power of automation and machine learning is retail forecasting. A McKinsey report found that continued investment in real-time customer analytics is vital in enabling businesses to monitor and react to shifts in consumer demand in real-time.
Demand forecasting AI uses machine learning technology to more accurately predict customer demand in real-time and adjust accordingly, automatically recognizing patterns and capturing signals for demand fluctuation.
Here’s a comparison between traditional and machine-learning forecasting solutions from a Tradecloud study.
4. Establish More Personalized Customer Service
Customer service has been at the forefront since AI first started pushing eCommerce automation. With the boom of chatbot technology and virtual assistants, DTC brands have been able to reduce costs while improving customer service with 24/7 availability and one-click answers.
But the development doesn’t stop there. With advancing AI technology, brands now have access to a host of tools that enable:
- Faster response times
- The ability to capture large amounts of valuable data
- Augmented human customer service
- Digital IVR and voice analytics for call centers
- The ability to build intelligent, customized experiences
- Lower customer wait times
- Automated messaging
- The ability to handle increased query volumes
5. Harness the Power of Advanced Customer Segmentation
Another area of business that benefits hugely from developing AI technology is segmentation. We know that segmented data is the cornerstone of successful marketing and personalization, improving the overall customer experience.
Not to mention increased revenue. According to one case study, the right campaign with advanced segmentation can increase revenue by as much as 760%. This is where AI is king.
Brands that incorporate AI into customer segmentation strategies across all platforms can:
- Explore highly complex options for customer engagement quickly
- Reduce human maintenance
- Read and analyze unlimited amounts of data in real-time to optimize performance
- Remove any human bias and find hidden patterns
- Update segments in real-time automatically
6. Upgrade Digital Marketing and Advertising to Pro-Level
There is no shortage of AI technology when it comes to eCommerce marketing automation. In fact, each marketing platform itself has built-in AI capabilities. However, in such a competitive market, it’s just not enough. Instead, online retailers need strategic tools, services, and built-in functionality that harnesses new technologies to dominate their niche.
With eCommerce marketing AI technology and machine learning, online retailers can:
- Create highly personalized on- and off-site offers
- Automate your entire eCommerce ads strategy
- Boost conversions with real-time virtual shopping assistants
- Add voice-activated payments
- Improve store cybersecurity and better prevent fraud and data theft
- Adjust prices in real-time with AI-enabled dynamic pricing
- Create smart product collections and personalized landing pages for specific ads
Final Thoughts: Seamless eCommerce Automation Integration
There is no denying that AI is positively driving eCommerce automation and technology. However, without real-time data and optimization, it will become more and more challenging to stay competitive. This means that as AI technologies evolve, you will need to invest more in automation.
Whether it's your ads or your product sorting, no matter what eCommerce automation you decide to upgrade first, it is important that you follow these steps to implement artificial intelligence into eCommerce the right way:
- Build a clear strategy
- Drill down your most important optimization needs
- Leverage third-party expertise and services
- Tweak and test to ensure that all your tools work seamlessly together
And that's it. You are well on your way to the future.
Looking to automate and optimize your online merchandising? Reach out to our team here.