Applications of Advanced AI Algorithms on Ecommerce App Development

From grocery to flowers, cakes and spare auto parts, you’ll definitely find an ecommerce store for everything. And with ecommerce capacities and use cases rapidly advancing, businesses are leveraging artificial intelligence to scale the experience – which finds its perfect application in mobile apps. If you are an existing ecommerce business planning to scale, or an aspiring startup founder just entering the market, these use cases from expert mobile app developers in UAE will interest you.

1.      Personalized Product Recommendations

AI algorithms analyze user behavior, purchase history and preferences to provide personalized product recommendations. This enhances the user experience and increases the likelihood of successful conversions.

In fact, these AI algorithms are adaptive – so they keep learning the sensitivities of user actions – after discounts, refunds, etc. The adaption adds to the learning part and makes the recommendations efficient - more accurate and relevant. 

In the longer run, ecommerce stores can expect a significant impact on customers’ lifetime value and average order value because of increased product visibility and strong relevance in product recommendations.

2.      Inventory Management via Predictive Analytics

Advanced machine learning models predict demand patterns and optimize inventory management accordingly. Then they make demand, supply, production and sales forecasts reflecting the buying patterns. This helps in maintaining optimal stock levels, reducing overstocking or stock outs and improving overall supply chain efficiency.

This function significantly improves the e-commerce shopping experience by reducing the likelihood of ‘out-of-stock’ encounters and promoting smooth buying journeys.

3.      Dynamic Pricing Optimization

Well-trained AI algorithms analyze market trends, competitor pricing and customer behavior to adjust product prices dynamically. Retailers and ecommerce business owners can then optimize pricing strategies in real-time to maximize profitability.

In fact, when integrated within the app’s backend, these algorithms also control pricing and make changes in real-time for price-sensitive products based on peak hours, seasons, weather, users’ interest in availing discounts and so on.

4.      Chatbots for Customer Representation

AI-powered chatbots are popular in the ecommerce industry. In fact, businesses have the option to integrate ready-made APIs or build custom, sensitive to their business. These chatbots started with responding to queries, forwarding, placing and confirming customer orders and resolving complaints.

They are actually transforming customer support by promptly attending to queries, providing personalized product recommendations and updating on the availability of stock. This automated, yet fully personalized customer service is helping businesses reduce cart abandonment ratios and simplifying buying journeys.

Voice and Visual Search with Image Recognition

You must have noticed the camera and speaker icons on the right side of the search bar. These ecommerce apps encourage users to capture or upload images and then recommend the closest, matching products.

These AI algorithms are typically trained for years and years to identify attributes like color, fabric, texture, accessories and so on. Now this trend highlights the shift from text to voice and images and facilitates a more convenient shopping experience – especially for buyers who are on the go – and this is a normal trend in subways in the Middle East.

Fraud Detection and Prevention

Machine Learning algorithms identify the patterns of transactions, reviews, ratings and refunds. The patterns in these factors are typically indicative of fraudulent activities like scams, privacy theft etc.

When cracked, these codes can help prevent fraud and protect: buyers, sellers and businesses from financial, reputational and data losses.

The analysis produced by these algorithms further helps with strengthening the security of the mobile app, filtering and flagging accounts. Overall, these security measures impact the trustworthiness and brand reputation.

Customer segmentation and Ad Targeting

Ecommerce apps collect and process huge volumes of data. AI algorithms analyze the customer profiles and then segment based on demographics, choices, sensitivity to prices and discounts, preferences, professions, shopping frequency, app usage and spending ranges.

These segments help with targeting profiles for recommendations – and more importantly for advertisements and promotions.  It’s a win-win because businesses get high ROI on ad spends and marketing efforts, while customers view ads relevant to their interests. 

Virtual Try-Ons

Augmented Reality is empowering in-app shopping experiences across the globe. Take the examples of brands like Sephora. This brand encourages users to upload an image of their facial features, then users can test the look of specific beauty products such as lipsticks, foundations, brightening creams and so on.

While these virtual try-ons provide an immersive buying experience and more informed decision-making opportunities, they also reduce the chances of returns, exchanges and refunds.

Automated Email Marketing

Building onto the part of user behavior analysis, segmentation and personalized recommendations, generative AI can actually send brand awareness and promotional emails – that too in sequences as follow-ups leveraging users’ FOMO.

Sentiment Analysis

This is an advanced branch of user behavior analysis, where algorithms suggest users to leave feedback. Later on, positive feedback becomes the input for more, similar product recommendations helping with upselling and cross-selling.

Business can leverage the sentiment analysis to improve the product development, pricing strategy and customer support.

Conclusion

Launching ecommerce branches is as important for retail brands as their brick-and-mortar stores. With 90% of product and service searches happening online – through websites and mobile apps, ecommerce apps have become all the more relevant for buyers – let alone impulsive, casual shoppers. So as businesses grow and the niches become more competitive, technologies like AI still hold the power to transform the user experiences.