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ARTIFICIAL INTELLIGENCE APPLIED TO E-COMMERCE

HOW CAN ARTIFICIAL INTELLIGENCE HELP TO OPTIMISE ONLINE SALES COMPANIES?

Applying Artificial Intelligence and Machine Learning to strengthen business is unstoppable. Until relatively recently, when you thought of AI, this was mainly Artificial Intelligence applied to the industrial sector. However, this has changed and today it is inconceivable to get a grip on most sectors without bringing smart technology to its processes.

In this respect, the e-commerce market is no exception. Internet commerce is growing all the time and contexts such as the current pandemic are accelerating its steady development even more. For this reason, digital companies are always looking for new opportunities to improve their scope and profitability.

USE CASES FOR ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPLIED TO E-COMMERCE

The main challenges in the sector focus on improving the three basic areas of the business: consumer needs, the purchasing process and delivery models.

PERSONALISING THE USER EXPERIENCE

It is essential to know the consumers and segment the target audience to design products, campaigns and exclusive messages to suit each customer’s needs. In on-line shopping, users leave an important data trail that outlines their consumption patterns: search histories, interactions, purchases made, similarities with other user profiles, etc.

Processing this data can identify patterns to predict behaviour. Thanks to this, it is possible to offer more personalised and accurate user experiences and recommendations automatically. In the end, the customer perceives a more attractive, comfortable experience that matches their tastes and needs.

For e-commerce companies, personalised product recommendations lead to improved conversion, average value of the orders and revenue.

CUSTOMER SERVICES

In any purchasing process, good customer service is fundamental, even decisive to complete a purchase. On many occasions, in on-line commerce, users require more extensive customer services as they do not have the products (or their salespersons) in front of them to answer queries on quality, materials, instructions for use, etc.

In this respect, Artificial Intelligence and Machine Learning provide e-commerce with natural language processing systems to automatically resolve this type of issue and predict customer needs that might arise in their shopping process.

Chatbots, virtual customer service assistants, are capable of simulating fluid conversations and their learning ability means that they get better every day, offering increasingly accurate interaction.

These Artificial Intelligence technological solutions not only resolve queries or give further information to on-line sales companies, but they are also a great ally for managing orders, guidance during the shopping process and on-line payments.

 DYNAMIC PRICING

STRATEGIES

Applying Artificial Intelligence to optimise e-commerce price strategies is fundamental. AI processes price changes in the market depending on price fluctuations among the competition and the offer and demand. This information makes it possible to predict changes in user behaviour, peak purchasing periods or times of low demand.

 

Using AI and ML in dynamic pricing strategies is essential for on-line sales companies so as not to waste sales opportunities and obtain maximum price margins at each point in time.

IMAGE RECOGNITION

Automatic visual inspection is an Artificial Intelligence solution used in the e-commerce sector to identify the visual characteristics that a customer is seeking in a product and offer them similar products.

On sales platforms that use this technology, users can compare products comfortably, quickly and efficiently, improving their user experience and encouraging sales.

LOGISTICS: INVENTORY AND DELIVERIES

This is a clear Artificial Intelligence and Machine Learning use case applied to e-commerce. Two world famous examples are Amazon and Aliexpress. On-line sales companies invest in AI and ML platforms with learning capacity such as ENAIA to process data, detect consumption patterns, predict demand, and so design strategies for sales and effective restocking.

In addition to anticipating customer decisions with Machine Learning, Artificial Intelligence facilitates the automation of processes with robotics, putting the management of goods and deliveries in the hands of the machines. In this way, companies can automate low value human tasks and invest their human capital in other areas or more useful or strategic tasks.

In short, predicting sales, managing stock and deliveries effectively and even optimising prices make it possible for e-commerce to reduce its costs and considerably increase its benefits.

Multimodal AI applied to Product Classification:

ENAIA, ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR E-COMMERCE.

ENAIA’s accessibility and its ease of integration make it the perfect Artificial Intelligence and Machine Learning multi-task platform for on-line sales companies.