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How AI is Transforming eCommerce

Updated: Apr 23, 2023

AI holds a tremendous promise of positive and negative transformation for the entire eCommerce value chain. You can either tap into the 37.3% compound annual growth rate and take your business to the next level or do nothing and get disrupted.


Take a look at these numbers:

  • 270%: The rate at which AI adoption by enterprises has grown over the past four years, according to Gartner.

  • $118.6 billion: The market cap of global AI software revenue by 2025, representing a compound annual growth rate (CAGR) of 37.3% ( from $9.5 billion in 2018), according to Tractica.

  • 180 zettabytes: The amount of data to be processed by AI by 2025, representing an uptick by a factor of 10 from 2020 to 2025, IDC says.

  • $5 trillion: The estimated value of the Metaverse by 2030, according to McKinsey.

These are exciting times.


Regardless of sector or business vertical, AI holds a tremendous promise of transformation with both extremely positive and negative consequences for the industry.


And business leaders already know that.


Case in point: A recent survey by Deloitte found that 58% of businesses are investing in AI to improve process efficiency, while 52% are investing in improving data analysis and decision-making capabilities.


Before excavating how AI is transforming eCommerce, let's look at some historical timelines of AI development.


How AI is Transforming eCommerce


Artificial intelligence is revolutionizing how we shop online.

From personalized recommendations to chatbots and virtual assistants, AI transforms the customer experience and drives sales like never before. eCommerce businesses that embrace this technology stand to gain a competitive advantage.


By adopting AI-driven solutions, such as chatbots, recommendation engines, and personalization algorithms, eCommerce businesses can deliver customers a more personalized and engaging experience.


This section breaks down the ongoing transformations to help you discover how to harness prospects to take your online business to the next level.


You'll learn how to leverage popular AI tools to improve customer engagement, boost conversion rates, and increase revenue. If you're looking to stay ahead of the curve and succeed in the rapidly evolving world of online retail, copy and paste these themes:


#1: Personalization


AI is helping eCommerce businesses personalize service delivery in ways they couldn't have done before, improving the customer experience and driving sales.


Widespread use case examples include:

  • Smart onsite search. Foundational to personalization is onsite search, and with Heyday's intelligent site search, businesses can optimize search results and improve the overall search experience for users.

  • Customized product recommendations. Companies use AI algorithms to analyze customer data and recommend products most relevant to their interests and needs, thus enriching their shopping experience.

  • Intelligent chatbots and virtual assistants. AI-powered chatbots and virtual assistants are becoming increasingly popular in eCommerce. They can answer customers' questions, provide product recommendations, and even process orders, all in real time. That improves the overall customer experience and reduces the workload on customer service teams.

  • Dynamic pricing. AI algorithms can analyze real-time market data, such as supply and demand, competitor pricing, consumer purchasing power, and customer behavior, to adjust prices in real time. With such proactive measures, eCommerce businesses optimize pricing for each customer, maximizing revenue while remaining competitive.

  • Predictive analytics. With AI-generated customer insight, companies can better predict future behavior, such as product preferences, buying patterns, and spending ability – which helps them increase conversions by tailoring marketing and sales strategies to individual customers.

Companies like Amazon, Netflix, Spotify, Amazon, Sephora, LinkedIn, Instagram, Nike, Adidas, and others present vital case studies on the merits of personalizing services. 80% of consumers are more likely to purchase when brands offer personalized experiences.


#2: Dynamic product recommendations


eCommerce businesses using data-filtering systems provide customers with a more fulfilling shopping experience.


Customers spend more when they quickly find products or services they might not have previously thought about. You also make the lives of your marketing and sales team easier by automating the process of product recommendations.


Here's how it works practically:

  • You create lead magnets and systems to collect customer data and other helpful information.

  • Processing and analyzing with AI algorithms, you identify patterns and design frameworks for products or recommendations.

  • AI algorithms use the processed data to create a recommendation engine that suggests products most relevant to each shopper.

  • Your system then displays recommended products and services to customers through various channels, such as product pages, email campaigns, and pop-ups.

  • You measure and improve recommendation effectiveness for better conversion rates.

For example:


Airbnb's recommendation system suggests travel destinations and accommodations to customers using their search history, preferences, and behavior on the platform.


The engine analyzes the location, price range, amenities, etc., of the properties the customer has viewed and shows similar properties the customer might like. That helps customers find the perfect travel destination and accommodation.


American outdoor recreation products company The North Face uses an AI-powered recommendation system called "XPS" (Expert Personal Shopper) to help customers find the right gear for their outdoor adventures. The system asks the customer questions about their activity, location, and preferences, then suggests products suited to their needs.

#3: Inventory and warehouse management


While traditional inventory management could only account for current stock levels, AI-enabled inventory management can maintain supplies based on historical sales patterns, trends, or potential product demand shifts.


AI-augmented inventory management provides real-time insights and automates repetitive tasks. With the advent of automated robots, warehouse management is becoming more efficient as robots can store or retrieve inventory around the clock, and ship ordered items immediately after receiving an online order.


For example:


With AI-powered inventory management, international apparel retailer Zara optimizes inventory levels and lowers waste. Their technology analyzes sales data and forecasts product demand using machine learning techniques. Additionally, it uses RFID technology to track inventory in real-time, enabling the business to replenish bestsellers while avoiding overstocking less well-liked items swiftly.


Leading provider of technology and services, Bosch uses AI-powered inventory management systems to optimize its supply chain. The system analyzes data from multiple sources, such as customer orders, production schedules, and supplier lead time to determine the optimal inventory levels and reorder points.


#4: Chargeback recovery and fraud prevention


Card payment fraud has been rising year after year. One of the growing fraud patterns is a chargeback, where a cardholder asks their bank to reverse a transaction fund. Although chargebacks were supposed to help remediate transaction issues, they've created a loophole for scammers to commit fraud.


Research shows that chargeback fraud has increased by at least 20% globally since the pandemic. As more consumers shop online, fraudsters take advantage of the increased volume of transactions to beat the system and get freebies, resulting in significant financial losses for businesses.


While manual dispute mediation processes can be slow and highly tasking, AI tools like Chargeflow help eCommerce businesses recover chargebacks by autopilot.


AI-powered systems can quickly process vast amounts of data, which helps identify fraudulent patterns and behaviors in real time. The system can flag suspicious activities to identify fraudulent transactions by analyzing patterns and trends.


Using machine learning algorithms, AI systems can monitor customer behavior and transaction history to identify potential fraudsters.


#5: Customer service optimization


Consumers are more connected than ever and need immediate solutions to their questions and complaints. The speed of your response times can make or break your eCommerce business.


According to Forrester statistics, poor customer service causes individuals to forgo planned purchases, costing the US economy $62 billion in lost sales. To combat this, online retailers increasingly use AI customer service technologies to get closer to their prospects and community.


Here are some notable use case examples:

  1. Installing intelligent chatbots, you can answer routine customer inquiries faster and provide 24/7 support to customers, reducing wait times and improving the overall customer experience.

  2. Voice assistants like Amazon's Alexa and Google Assistant use AI to understand and respond to customer inquiries, help customers quickly find information, place orders, and get support.

  3. AI-powered sentiment analysis frameworks can track Social Media and other touchpoints for customer feedback to track areas of improvement and help your company improve its customer service.

  4. With AI-powered predictive analytics, you can better anticipate customer needs, provide proactive measures, and increase brand loyalty.

  5. AI-assisted visual assistance tools help customers troubleshoot issues with step-by-step guidance and visual instructions to reduce the need for human support and improve the speed and accuracy of troubleshooting.

  6. AI can help locate routes with less traffic in peak hours to enhance supply chain management and improve order delivery. It also makes sorting and packaging procedures in warehouses and fulfillment facilities more effective.

While there's been so much work done in leveraging AI to improve the entire eCommerce value chain, challenges and limitations still abound.


Challenges and Limitations of AI in eCommerce


While AI has the potential to transform eCommerce, and you should catch on with the trends, being aware of AI's challenges and limitations helps ensure you can participate in addressing them.


Below are some of the prominent ones:


Data security and privacy


AI relies heavily on customer data, such as purchase history, browsing behavior, and personal information, to make personalized recommendations and improve the customer experience. Correctly handling data to avoid privacy and security risks is crucial.


Customer data can be vulnerable to cyber threats like hacking, phishing, and other data breaches if not secured correctly. It can result in the theft of sensitive customer data, such as credit card information and addresses, for fraud purposes.


That's why HeyDay maintains military-grade data security and is transparent about data collection and usage practices for ethical and legitimate data usage.


Ethical concerns


The potential for prejudice and discrimination in decision-making processes is one of the vital ethical worries associated with AI, as algorithms are only as good as the data they have. Ensure your AI systems are created and taught to be impartial, fair, open, and honest about using customer data. And prioritize consumer data security and privacy to increase trust and customer buy-in.


Implementation costs and complexity


The related expenses and complexity are among AI implementation's main obstacles and restrictions. Large human, hardware, and software investments pose substantial entrance hurdles for small and medium-sized eCommerce enterprises.


Also, the legacy systems used by some companies may not be compatible with AI technology or need significant modification to integrate AI. Such a time-consuming and costly procedure may require high competence.


Skills gap and talent shortage


The twin challenge of talent shortage and skills gap makes AI adoption quite tasking. Smaller eCommerce businesses may need more resources to hire expensive data scientists or AI specialists. As a result, many smaller eCommerce businesses may need help adopting AI-based solutions to help them compete with more prominent, more established players.


Unemployment and job losses


Adopting AI in eCommerce may lead to job losses in specific industries. For example, AI-powered chatbots and virtual assistants can handle customer inquiries and support, reducing the need for human customer service representatives. Similarly, AI-based systems can automate tasks such as inventory management, order fulfillment, and supply chain optimization, which human employees currently perform.


Yet, AI can also create new opportunities for employment and drive business growth. Corporations and governments need to design systems for mitigating the impact of AI on the workforce and ensure that employees have the requisite skills to adapt to the changing demands of the eCommerce industry.

Future of AI in eCommerce: Opportunities for Innovation and Growth


The future of AI in eCommerce is ripe with potential for innovation and Growth.


Undoubtedly, there'll be increased investment in AI-based solutions, leading to more personalization, operation efficiency, and secure shopping experiences.


Below are some thoughts on potential innovation opportunities and growth centers.

  1. Product and Service Personalization. Consumers want more tailored service delivery. As AI technology improves, eCommerce businesses will provide increasingly customized experiences that drive brand loyalty and sales.

  2. Voice Commerce. With more accurate recognition technologies, voice commerce could become a significant sales channel for eCommerce businesses. Statista says the number of digital voice assistants in use globally could reach 8.4 billion by 2024; voice commerce sales could yield $164B worldwide by 2025, according to Voicebot.

  3. Supply Chain Optimization. AI-powered supply chain optimization has the potential to reduce costs, improve efficiency, and enhance the customer experience.

  4. Visual Search. With more improvement in optical search technology, businesses can better help customers search for products using images rather than text, driving customer engagement and more sales.

  5. Virtual & Augmented Reality. With more investment in the Metaverse and Web 3 infrastructure, customers can visualize products in their own space, improving the overall shopping experience and reducing the likelihood of returns.

  6. Autonomous Delivery. With better-equipped AI-powered drones and robots to deliver products directly to customers, businesses can improve the speed and efficiency of product delivery while reducing costs and increasing customer satisfaction.

That said, here's how to improve your onsite search and optimize your conversion rate.


 


About the Author

Tom-Chris Emewulu is HeyDay’s Digital Evangelist. With 8+ years of digital marketing and business development experience, he crafts high-intent, high-converting, data-driven SEO articles that put brands on page 1 of Google search. Forbes, DW, Business Insider, Businessss2Community, and many other publications have featured his works. You can find him on Social Media via @tomchrisemewulu.

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