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AI realm is burgeoning with possibilities. No industry is untouched by its Midas touch. When AI takes over, the business speeds up, forgets its jet lag and gets back on track. It’s not like the businesses were not able to function while AI was not there, just that they started functioning extra well. It does tag some challenges along with it, but the overall benefits cloud the disparate, intermittent things that crop in between.
The Story That Goes Behind
In earlier days, people used to go to their nearby store to buy groceries. They used to carry a long list of items that they wished to purchase. While the shop helpers fetched the items, they kept standing on the counter gossiping. It usually took 1 – 1.5 hours (in the case of a monthly grocery list) in the process. As time passed, things shifted slightly and people started making use of apps on their smartphones to order grocery online. With the advent of AI such on-demand grocery apps have become smarter. Not only grocery delivery apps, but apps across the business industry have become smarter. How?
AI enables product recommendations. It has the potential to analyze user behavior and preferences to suggest products. It analyzes market trends, competitor prices, and customer behavior to automatically adjust prices in real-time. It predicts inventory needs to avoid overstocking and stockouts. AI can analyze data, detect anomalies, and monitor transactions in real time to identify unusual activity. It can automate repetitive tasks, provide personalized experiences, and offer real-time assistance. It also helps marketers (1) build better products, (2) deliver more relevant advertising, and (3) understand customer data patterns.
AI is a machine, or robot that works on algorithms or human-made instructions. It is trained to do work faster than humans with accuracy. It does not repeat unless told otherwise. This removes redundancy.
How does AI work?
When a user shoots a query with raw data, it is pre-processed and interpreted. The AI systems interpret the context and intent behind the user’s query. Based on the search results and user context, AI generates personalized product recommendations. The device then displays the generated product recommendations to the user.
Types of AI technology used in e-commerce
Fundamental technologies: (1) Natural Language Processing (NLP), (2) Machine Learning (ML), (3) Computer Vision (CV), and (4) Data Mining are four models or technologies used in Ecommerce App Development with AI.
Applications of AI in e-commerce
- To detect online fraud by identifying purchase patterns and ways of making payments.
- To respond to customer’s queries.
- To help businesses focus on demand, identify patients, and automate restocking to maintain optimal inventory levels.
- To help merchants manage product listing prices to gain a competitive edge.
- To categorize customers into subsets based on shared demographic and psychographic information.
- AI-powered analytics makes use of machine learning to find patterns and relationships in data and automates tasks that are normally done by a data analyst.
- AI-powered websites are able to scan fraud reviews so that customers are able to make honest opinion about products.
- AI can predict market trends and future sales by analyzing historical data and studying current and upcoming trends.
Benefits of AI in e-commerce
AI-based applications offer personalized product recommendations, dynamic pricing, customer churn prediction, predictive shopping, Personalized discounts and offers, a Seamless checkout process, and AI image creation for product visualization.
First off, AI can help in improving customer experiences and operations based on customer’s purchase history, buying preferences, and frequency of purchase. This can help in improving customer loyalty and increasing sales.
Artificial Intelligence automates simple tasks like emailing, order fulfillment, customer service, and payment processing.
It helps businesses gain insights from customer data to make better decisions. It analyzes customer reviews to improve product design and marketing strategies.
AI comes in various forms (1) chatbots to handle customer inquiries, and reduce human effort; (2) inventory management to track levels of inventory, predict demand, and restock decisions; (3) sales forecasting to analyze historical sales data, pricing, promotions and predict future sales; (4) to make recommendations to help customers in finding relevant products from a large catalog; (5) in voice search to search faster; (6) in natural language processing to help humans understand how to use language; (7) AI is used in virtual assistants, AI-powered tools to help customers with product recommendations, order tracking, and personalized styling advice.
Challenges of AI in e-commerce
But despite all the good things that we hear about Artificial Intelligence (AI), it does fog human decision-making.
- We conclude by writing an entire blog. That conclusion is the crux of all the research that we do while writing the blog. Similarly, AI algorithms research and skim vast amounts of data to make accurate and timely recommendations. But the results might not be unique.
- We know a simple mathematical formula – the product of mean is the product of extremes. Where does it fit into this context? AI collects data, cleans, and ensures data privacy, but the data is still sourced from the existing similar information. So the quality of the result might differ.
- It is not easy to handle customer data and simultaneously ensure compliance with regulations like GDPR and CCPA.
- AI might not integrate well with legacy e-commerce systems.
- AI solutions can be expensive owing to the cost of hiring data scientists, purchasing hardware, or acquiring or building AI models. Because not all AI solutions are free.
- AI algorithms can inherit the biased results present in training data. This can potentially lead to unfair outcomes which are often discriminating.
- AI models may or may not support the scalability of the application, due to restrictions in the technology infrastructure and AI models. There might be restrictions with various regional and industry-specific laws, which are essential to avoid legal and reputational risks; moreover, the return on investments (ROI) of AI implementations can be challenging. Results might take some time to come off, but some AI projects may not deliver the expected benefits. Of course, every e-commerce app cannot become Amazon. The businesses that adopted AI earlier are growing, but new ones have competition.
Understanding AI in eCommerce with an Example
Specifically about Amazon, they have their presence in more than 100 countries and regions, including 131 countries for international shipping. But Amazon does not ship to Cuba, Iran, North Korea, Sudan, and Syria. USA has the most number of active Amazon users.
To engage customers, Amazon’s market strategies are targeted to suit local audiences. AI can detect buying behavior, but they float strategies to increase the number of clicks, with a very high chance of leading them into purchase. AI-powered tools extract information from product pages and convert them into dynamic deals, discounted offers, and video flashes, which are complete with voice scripts and human presenters.
AI Benefits in E-commerce
E-commerce giants like Amazon have a fully functional Amazon Bedrock (A Generative AI platform) based on foundation models from leading companies like Anthropic, AI21 Labs, Cohere, Mistral AI, Meta, Stability AI, and Amazon via single AI, consisting of a broad set of capabilities required to create generative AI applications that are secure, responsible, and private. E-commerce companies embrace artificial intelligence services in varied ways to improve their operations and enhance the customer experience. Here are other benefits of using AI in eCommerce applications:
- Virtual shopping assistants/Chatbots
- Dynamic pricing
- Logistics optimization
- Fraud Detection
- Inventory Management
- Voice and visual search
- Personalized Product Recommendations
- Supply Chain Optimization
- Fraud Detection – Blocking suspicious account activity
- Customer service – to answer all the questions about products, place, orders, weather, traffic conditions, delivery delay, estimated time of arrival, and more.
- Image and video analysis
- Predictive maintenance – to check in advance when equipment are likely to fail.
Additionally, AI also helps analyze customer reviews to improve product design and marketing strategies.
Conclusive: How powerful can AI make eCommerce?
AI can be stretched to become multimodal, rich, and interactive. It combines numeric data, text, images, and video to achieve accurate, timely, and enhanced results that enhance user experiences. While there are many AI trends to look out for – Generative AI, Multimodal AI, AI democratization
This is a rundown of what we have researched and listed so far. AI imparts a plethora of benefits to the ecommerce industry. One of them is personalization (which is customizing items and offers according to their choice, their buying range, from the companies they love to shop, the color and brand, taking cues from their saved items, and wish lists, and also considering their testimonials, complaints, grievances, and frequency of purchase.
AI e-commerce apps answer customers’ queries on their order history, offer tips, and helpful suggestions, quickly resolve complaints and open up a lot of time for dedicated support agents. AI app development prevents the need to overstock and detects understock, or stock-outs in advance. This saves app development cost in the long run, thereby driving efficiency and increasing customer satisfaction.
