Neural networks in e-commerce

Automated logistics, sales bots, robotic online chats – their appearance is due to technological progress, which literally covers all spheres of modern human life. Artificial Intelligence (AI) is streamlining and simplifying more and more of the processes that humans used to be responsible for.

In addition, it does it efficiently and quickly. For example, not so long ago, e-commerce giant Amazon opened a grocery store without checkouts and filed a patent for the delivery of goods using courier robots and drones.

Neural networks are capable of performing natural language processing (NLP), recognizing and describing an image in a photo, translating texts, and even recognizing speech.

In the foreseeable future, new technologies will become an indisputable competitive advantage for e-commerce projects, but even today their introduction into business has a number of advantages.

A neural network is a “virtual brain center” that serves to automate business processes: fills out documents, approves applications, answers customer questions, etc. Moreover, the larger the database, the smarter the neural network. In fact, it reproduces the work of the human nervous system, including its ability to self-learn, taking into account previous experience. This technique allows the system to make fewer and fewer errors each time.

Neural networks are actively being introduced into online stores and marketplaces, since in e-commerce there is a need not only to consider goods through the eyes of the seller, but also to correctly describe the characteristics that are important for the buyer. Some projects train AI on their own. An example is services in which neural networks describe a product in a photo, add a category and recommend a price based on data from similar products.

Currently, the owners of the smartest and most powerful neural networks that provide commercial user requests and satisfy the needs of corporations are other large companies, such as Google, Facebook, Pinterest.

The main vectors for using artificial intelligence in business include: risk management, cybersecurity, analysis and assistance in making optimal decisions, automation of routine.

Facebook and Pinterest are actively using neural networks to work with images. Using facial recognition technology, Facebook invites you to tag yourself and people you know in a photo, and Google provides users with a “search for similar images” function. In addition, Google uses neural networks in its other services – from searching and filtering mail to translating texts and selecting videos on YouTube.

Tesla uses neural networks in the autopilot system: AI recognizes all objects around the car in real time, classifies and determines their characteristics.

Until recently, neural networks were the privilege of exclusively large companies, but in recent years, a lot of available solutions, technical tools and cloud services have appeared that allow you to adapt AI to the tasks of almost any e-commerce project.

The development of neural networks is a worldwide trend. The main sources of research funding in this area are commercial companies and corporations that provide online advertising services.

At the current stage of development, marketplaces have changed and have gone from a bulletin board, where offers were posted by a relatively small number of people, to a full-fledged network with a huge number of users. The next stage of development will be optimized mobile marketplaces that work even faster.

Neural networks in this process not only help to simplify time-consuming moderation, but also make navigation on marketplaces more convenient and understandable for the user.

Another good example of the successful implementation of AI in a business is the Amazon recommendation engine, which provided the company with about 35% of sales. The Brain algorithm for content recommendation, developed by YouTube, also showed a high result: according to statistics, almost 70% of videos viewed on the site were found by users through recommendations, not subscriptions or links.

• Neural networks are able to generate recommendations for products that are most relevant to the interests of the user. Algorithms based on machine learning analyze the user’s history, determine his tastes, evaluate behavior on the site and compare with millions of other users, after which they offer products based on the information received. The system works in such a way as to most likely determine which product you will buy.
• The neural network allows you to automate the process of checking content and reduce the number of employees involved in it. In addition, the use of AI makes it possible to improve the quality of moderation in general.
• While humans tend to err, there is much less error in machines. That is why evaluation and filtering of user content using neural networks are practiced by Google Photos, Disqus, Pinterest, etc.
• Machine learning helps identify potential fraud in many areas and industries. For example, PayPal uses AI to combat money laundering. The system compares millions of transactions and identifies suspicious ones among them.
• Neural networks in e-commerce are used to calculate LTV (the total profit of a company from one client for the entire period of cooperation) and perform the functions of other business metrics. So, the technology allows you to build long-term strategies for the development of online stores and predict the real revenue from each client.

• The system allows you to monitor and evaluate the productivity of company employees, to identify early KPI fulfillment or, conversely, negligence in their duties. The robot collects and processes data from video surveillance, computers and other sources in a matter of seconds.
• The neural network correctly classifies and distributes customer requests. When a user calls or writes to technical support, artificial intelligence analyzes all the data: text, layout of a chat message, images, sounds, etc. After that, the request is forwarded to a specialist who knows the client’s language and can solve his problem.
• In the field of lending, algorithms automatically collect and analyze all parameters of a potential borrower, after which they approve or reject the application.
• Natural language neural networks can be used to create chat bots that help customers get the information they need about a company’s products. In particular, this allows you to significantly reduce the costs of the call center.

IT solutions based on artificial intelligence technologies are very popular with commercial and government enterprises. There are several typical tasks that neural networks are able to solve today:

• Forecasting and risk assessment. AI helps in predicting demand, sales volume and frequency, average ticket, etc.
• Search for trends, correlations and trends. The neural network can predict the further development of the system and indicate possible changes.
• Recognition of photo, video, audio content. An example is the numerous applications and online services based on recognition technology.
• Machine learning to communicate with customers. This function is used to automate the work of operators in online chats, telephone operators and instant messengers.

The technology provides companies with the necessary flexibility, the ability to adapt to any customer needs and respond quickly to external changes.

When implementing neural networks, our team is guided by three main principles:

• Data structuring

Any organization works with several different sources and types of data that are necessary for daily operations. That is why, at the initial stage, we structure the approach to access and data management.

• Conducting A / B tests

AVADA MEDIA specialists create several models of personal recommendations and conduct A / B tests. It is an important marketing tool that measures the effectiveness of project innovations.

• Detailed analytics

The full implementation of artificial intelligence in business processes can take a long time (up to 6-12 months). That is why experts carefully study the dynamics and analyze the results. We track the progress in training the neural network, which should optimize processes and bring profit to the company, and draw up reports based on the data received.

There is a vast area in AI development – machine learning. It is dedicated to creating programs that can independently analyze data and draw logical conclusions based on them. In addition to the services of experienced developers and neural network engineers, our company offers courses in which we train machine learning specialists.

Experts in the field of artificial intelligence draw up algorithms by which a machine works with data: processes the information received, builds causal relationships, makes logical conclusions, assimilates new information, and improves its own process of “thinking”.

As the trends in machine learning applications gain momentum, experts in this field will never be out of work.

It is almost impossible to successfully manage a company without using modern computer technologies. AVADA MEDIA develops and trains neural networks that help businesses make forecasts and analyze data, automate and optimize processes and, as a result, make high-quality decisions faster, increasing their efficiency in the market.