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Yuliia Honcharova
Senior SEO Manager at Gepard
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artificial intelligence eCommerce eCommerce trends

Artificial Intelligence In eCommerce: Redefining The Future

8 min read
December 15, 2021

As online shopping, especially mobile commerce, became a dominant way people shop in the last decade, regular retail businesses realized that they couldn’t compete and needed some form of an online presence.

As eCommerce continues to grow, so do advancements in other technologies, such as smart chatbots, personalized product recommendation engines, voice searches, and more. Most of these technologies can be regarded as artificial intelligence.

What Is Artificial Intelligence In eCommerce

In essence, artificial intelligence in eCommerce executes activities that usually require human intelligence. Some AI systems are powered with machine learning or deep learning, and some are simply based on a rule set. Here are a few examples:

  • Reducing cart abandonment
  • Delivering personalized experiences
  • Making search through a store smart

With 70% of online business owners supporting and believing that AI for eCommerce will help their online shops with personalization, there is no doubt that this technology will only grow further.

AI In 3 Minutes: Basics & Definitions

What Is Machine Learning?

Machine learning for eCommerce allows you to uncover data associations without having to follow a rigid manual procedure.

For instance, machine learning algorithms can predict consumer behavior changes and personalize product recommendations. Moreover, knowing a would-be user behavior, such an algorithm can reshape the homepage layout and content placement.

What Is Deep Learning?

Deep learning is a branch of machine learning/AI and principally refers to algorithms in eCommerce that help to discover and track user behavior, providing businesses with actionable insights. For instance, Amazon uses deep learning algorithms for Alexa and other voice assistants.

What Is NLP?

NLP (natural language processing), a branch of machine learning, gives machines the ability to understand human speech and its patterns. As artificial intelligence in eCommerce grows, so does the natural language processing market; in the last five years, revenue generated from it has drastically increased and is projected to rise even further.

For example, NLP can be used in chatbots or voice assistants. Also, NLP is a technology of choice for product categorization or product description personalization.

What Is Computer Vision?

Computer vision equips computers and systems to extract useful data from photos, videos, and any other digital visual inputs. Based on the extracted data, the system can create a personalized offer. This technology helps retailers to stay competitive and enhance customer satisfaction. For instance, computer vision and augmented reality used together work great for creating virtual showrooms.

Technologies Using AI in eCommerce

All of these basic AI technologies have different purposes and uses in powering online shopping.

  • The main applications of NLP in eCommerce are voice-activated payments, virtual conversation, and voice searches.
  • Computer vision allows face detection and identification when it comes to artificial intelligence in eCommerce.
  • Chatbots use deep learning algorithms and NLP, and they can comprehend the second party’s voice and human vocabulary during the interaction.
  • Expert systems, with the help of AI, are able to make a judgment and emulate human behavior as a prime component of fraud prevention and security enhancement in eCommerce.
  • Image recognition allows users to look for products online simply by taking a picture and dragging it into Google search.

How Artificial Intelligence Is Used in eCommerce & Related Business Domains

eCommerce

A smart recommendation engine for online shops works based on user behavior and offers users products they are looking for. The algorithm analyzes the user behavior patterns such as frequent product views, considerations, and purchases. Based on the analyses, the most relevant product suggestions are displayed.

Virtual dressing rooms are a type of software that helps consumers digitally try on clothing. The item can be placed over a live image of the buyer using artificial intelligence technology and is essentially acting as an enhanced shopping assistant.

Retail

Supply chain planning: AI algorithms are capable of processing and analyzing enormously large data volumes, helping retail businesses detect logistical disruptions. Research done by IBM found that 40% of companies that participated in the survey resolve supply chain challenges using AI.

Customer research: AI allows for cutting costs in performing market research and doing it more efficiently. Machine learning software is already capable of performing tasks such as finding survey respondents, analyzing open-ended replies (unstructured data), and determining what follow-up questions to ask.

Warehouse automation: Inventory processing can be powered by AI software that optimizes its operations and automates them. Online retail giant Amazon has reported that AI-powered computers help stock 40% more inventory in its warehouses. Companies such as Swisslog manufacture intralogistics systems that are capable of learning and evolving from human interactions in the plants they are installed at.

Shoppers mood tracking: AI-powered eCommerce technologies can track and detect certain consumer moods and trends, helping online shops to keep a more accurate product stock. The Very Group successfully implemented AI mood tracking technology in their machine-learning chatbot. It detects customers’ tone in messages and adjusts replies based on that information. The AI system eventually became the most used customer support channel of the company.

Manufacturing

Production process control: Combining artificial intelligence with production process control reduces cost overheads and downtime. In market research done by Capgemini, it was determined that 51% of European manufacturers use AI solutions.

Processes automation and improvement: AI technologies help reduce mundane, routine tasks that exist in manufacturing, but most importantly they can also predict accidents by analyzing volumes of data from large factory machinery. Companies such as Canon are leveraging their experience and knowledge of manufacturing automation powered by AI and are even offering consulting services to other businesses.

Equipment diagnostics: AI-powered software can perform equipment diagnostics without human interaction. This can be applied both on a large scale, for example in production lines, or for individual cars. A large number of modern vehicles come with built-in AI tools that perform automatic diagnosis of the engine and other car parts. The most prominent example is Hyundai’s AI engine fault diagnostics system that collects internal car noises, and based on that analysis of the gathered data, it makes a diagnosis with accuracy exceeding 90%.

Where Is AI Used?

Marketing

Personalized offers: AI tools let marketers go beyond traditional customization efforts by examining massive datasets and finding trends in customer behavior. These data findings act as reference points for decision-making during different stages of advertisement planning and help with the integration of personalized AI sales offers.

Orders/purchases management: From SKU availability checks to shipping label printing, not so long ago order managers processed these tasks practically manually. Today numerous AI-powered solutions do this task for you. Industry leaders, such as Retalon, use artificial intelligence to provide systems that do the planning, merchandising, and inventory management.

Ads automation: The process of running ads often requires collecting data from initial marketing campaigns and running them again with a more narrowed down audience targeted. Thanks to AI software, all this can now be performed automatically. Solutions such as Adext utilize machine learning algorithms that automatically are able to perform audience segmentation, budget planning, and more for Google, Facebook, and Instagram ad campaigns.

Virtual shopping assistants / virtual conversations are additional AI solutions that are assisting buyers and increasing their purchasing efficiency while also assisting businesses in gaining the insights they want in finance areas and risk management.

Payments

With 3.25 billion voice assistant devices in global use, voice-activated payments are transforming the way personal banking is done. It efficiently reduces the time it takes to do financial operations, such as signing in and activating cards, as well as making transfers and paying bills.

Supply Chain

From retail to manufacturing, transportation to storage and supply chain, efficiency influences every business. In many countries, it became a norm for shoppers to expect to get their purchases on the same day. This is possible to achieve thanks to AI implementation in the transportation industry, especially in flight delay prediction technology that is powered by AI.

Cybersecurity

An unusually high amount of login attempts often indicate a cyberattack, whereas a significant increase in credit card transactions in a short period can indicate fraud use. Due to eCommerce machine learning technologies, online shops can perform threat analysis and prevent financial cybercrime. Moreover, AI helps to prevent fraud and data theft.

How Brands & Retailers Use AI

With AI in eCommerce, personalization and automation revolutionized the shopping experience for consumers. Global brands understand this point and use it to their advantage.

Amazon Go – Automated Offline Stores

Amazon rolled out its automated checkout technology to full-size supermarkets, marking a huge step toward changing the way consumers shop for groceries.

Amazon Go planned to establish 3,000 autonomous stores by 2021, where customers may shop without having to interact with anybody. The stores, according to Amazon, do not utilize face recognition, but rather picture recognition, which is cross-referenced with weight sensors that determine which goods have been taken from a shelf.

Nike – AI For D2C

Nike has put a lot of money into its direct-to-consumer marketing. Nike’s D2C (direct-to-consumer) initiatives seek to develop “more personal ties” with customers. These initiatives heavily rely on personalization in eCommerce intelligence.

The company has improved its eCommerce presence as well as its NikePlus membership program, which provides clients with a variety of bonuses —such as early access to new products, member-only items, and free 30-day returns.

AI In eCommerce FAQ

How AI Is Used in eCommerce?

AI is used in eCommerce by leveraging acquired business and customer data to make better business decisions and more accurately forecast the future. Artificial intelligence in eCommerce can help today’s online merchants create an optimal consumer experience both online and offline.

How To Use AI For Personalization

What Are The Examples Of AI In eCommerce Apps?

AI is used in eCommerce apps when shoppers use voice search, find product descriptions that are created and personalized automatically, and have search results that are individually tailored to them.

What Are The Benefits Of Artificial Intelligence In eCommerce?

The strongest benefits of AI in eCommerce come down to what generates the most revenue. Personalized product recommendations account for up to 31% of eCommerce. Of course, other benefits can’t be excluded, such as predictive marketing support, AI-powered fraud detection software that helps reduce losses, and chatbots that also save overhead costs.

How AI Is Used In Shopping?

Online retailers use AI to enhance demand predictions, price choices, and product positioning. Predictive analytics with eCommerce intelligence can assist you in the correct inventory management so that your online shop has just the right amount of certain products.

What Challenges Can Gepard Solve for Your Business?

While shopping online, visitors often make a buying decision to abandon a cart. What often causes them to stop the purchase is the cost of delivery and slow checkout processes. But another reason, which also acts as a big cause for the high abandonment rate and is often overlooked, is the lack of accurate product information. The bigger inventory an online shop has, the harder it is to manage it. The product details updates (description, images, rich content, packaging info) are frequently missed due to human error, especially when they are done manually.

These errors that have a significant impact on the revenue of a business can be easily corrected with an automation solution that Gepard PIM offers. Our unique product content optimization software simplifies the process of collecting, enriching, and pushing product information to multiple sales channels.

Equipped with the understanding of the importance of AI in eCommerce and accurate product information, you may want to work with a well-grounded solution like the one Gepard offers.

Reach out to our team of specialists to request a personalized demo of Gepard PIM.

How To Automate Product Data Delivery

Yuliia Honcharova
Written by Yuliia Honcharova
Senior SEO Manager at Gepard
17+ years in Digital Marketing, SEO, SEM. Driving the strategy, planning, and execution of the company's search marketing initiatives to achieve its international business objectives. Created and implemented Digital marketing and SEO strategies for businesses in varied domains including eCommerce.

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