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4 Integrations For Ecommerce: AR, ML, CV & Predictive Analytics

A woman using an AR headset observes a robotic experiment with a submerged device in a transparent water tank.

Online commerce continues its ceaseless growth. According to the recent BuiltWith data, there are over 26.2 million ecommerce stores, which keeps growing daily.

Although this trend is positive for the industry, rapid growth can pose challenges for individual ecommerce businesses, as it inevitably comes with more fierce and sharp competition. Only those merchants who can provide quality service and customer experience can survive and thrive in such harsh conditions.

Continuous digital transformation, empowered with emerging tech such as AI, ML, and VR, is one of the best ways to stay at the forefront of industry developments. Integrating advanced technology with the help of professional ecommerce developers, a merchant can streamline various aspects of its business, leading to increased competitiveness.

This article covers four emerging technologies that can help a merchant engage customers, provide better service, and become more competitive.

1. AR/VR/MR

Augmented reality (AR), virtual reality (VR), and mixed reality (MR) are all parts of a broader technological concept of extended reality. All these technologies can contribute to an ecommerce business growth at multiple levels.

First, AR, VR, and MR can be used to deliver more outstanding user experiences through advanced immersiveness that helps engage customers emotionally. In the simplest scenario, a merchant can consider creating a virtual try-on (VTO) to grant their clients a realistic experience and accelerate the purchase decision process.

VTOs are AR-powered tools that allow customers to try on clothes, furniture, and other products online before purchasing. Consumers must turn on an AR-enabled mobile app and use a smartphone’s camera to see themselves in a preferred T-shirt or shoes.

By implementing such a solution, a merchant helps consumers make a more informed purchase decision, reducing product return rates. Moreover, a merchant can attract additional web traffic by addressing audiences already accustomed to immersive shopping.

Immersive employee training is another application area for augmented, virtual, and mixed realities. By transforming the traditional learning process, a merchant can significantly improve service quality and overall business efficiency, contributing to greater competitiveness.

For example, employees can undergo VR-based training to improve their communication skills at a merchant’s order pickup point. They can execute various customer interaction scenarios and become prepared to solve real issues and requests, providing better service.

Real-life examples: Adidas and Bohus

Adidas has been using AR technology for several years already – it added a virtual try-on feature in its iOS app in 2019. In 2023, Adidas took another step towards AR by running a marketing campaign with Snapchat to promote the NFT-based Indigo Herz collection. Within this campaign, Snapchat users could access the AR feature via their profiles to try on Adidas clothes in a virtual environment.

In its turn, Bohus, a Scandinavian furniture retailer and ecommerce company, used AR technology to provide employees with gamified training. The project’s main objective was to ensure employees deeply understand the new product line. According to the training course results, 96% of employees noted that AR-based training helped perfect their product knowledge.

2. Machine Learning

Machine learning (ML) is another technology that reshapes the modern ecommerce industry. It has multiple practical applications, from marketing and security to logistics and customer support.

For instance, a merchant can use ML to build a recommendation engine. This system processes past customer requests and purchases and suggests relevant products when people browse an ecommerce website or app. This way, a merchant can easily capture users’ attention and increase the average paycheck by making smart recommendations.

Real-life example: Amazon

Amazon has a powerful recommendation engine behind its ecommerce platform. This ML-based system helps provide targeted recommendations based on collaborative and content-based filtering techniques. 

For instance, the engine can analyze customers’ past purchases and browsing behavior to discover similarities among user groups. Then, it can recommend products one user likes to others who share similar interests, thus ensuring recommendation relevancy.

3. Computer Vision

Similarly to machine learning, computer vision represents a branch of a broader concept – artificial intelligence. And like ML, computer vision continues penetrating the ecommerce market – it enables corporate ecommerce software to extract meaning from digital images, which can come in handy in various scenarios.

For instance, computer vision can help a merchant improve product search on its digital store. With the help of technology, an ecommerce company enables customers to search for desired products by uploading photos of a similar product, eliminating the need to make long text requests and streamlining the purchasing process.

Real-life example: ASOS

ASOS can be considered one of the pioneers of computer vision in the ecommerce industry – back in 2017, the company added a search-by-image feature to its mobile app. Since then, ASOS has made advancements in the area, as today, the company uses complex Convolutional Neural Networks (CNNs) to extract meaning from product images and deliver accurate recommendations.

4. Predictive Analytics

Effective decision-making at different levels is critical for establishing a competitive and growing ecommerce business, which is only possible with high-quality analytics. In this context, predictive analytics software and technology become vital, allowing forecasting trends and customer behavior patterns in advance, which helps merchants make more intelligent and data-driven decisions.

Real-life example: Carrefour

Carrefour, an international retail and ecommerce corporation, uses predictive analytics tools to optimize inventory across its warehouses, physical stores, and ecommerce sites. By analyzing customer purchase and behavior data, the company enables sourcing and procurement teams to work more accurately, which helps manage multi-channel distribution effectively and avoid overstocking.

Final Thoughts

The number of ecommerce businesses is growing daily, leading to increased competition between merchants. Those who adopt emerging technology such as AR, VR, ML, and computer vision can engage customers better and provide more quality service, leading to increased competitiveness.

However, adopting emerging tech can be challenging, requiring well-rounded and deep technological expertise. In addition, digital transformation typically implies workflow optimization, which could disrupt business.

Companies can engage ecommerce experts in their projects to ensure smooth technology adoption. Consultants can help determine the viability of a particular technology regarding the company’s business case and develop an appropriate implementation strategy.

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