In what domains is ML used: E-commerce
All around speaking and buzzing about Machine Learning, but what is that?
ML is a programming sphere which allows to predict or get information about insights based on patterns they identify in data. They can be improved with experience — without human intervention. As companies have access to more data, machine learning enables them to draw insights from the data at scale, at a level of granularity that ranges from a single user interaction to worldwide trends and their impact on the planet.
Note that data science for business is an opportunity to achieve higher results. Its power can often be enhanced by combining internal with external data to drive new insights. It is the reason, why businesses incorporate data science solutions into work processes.
According to a survey of 1000 organizations around the world, 78% of companies are introducing ML in order to increase operational efficiency, 75% to increase customer loyalty, 79% to analyze data and get new ideas.
So we want to provide you with examples how machine learning technologies can be used in different domains.
And the first stop is an E-commerce. Machine learning and artificial intelligence are the top technology trends for it now. They have a great influence on the industry, where the use of data science technologies is very spread nowadays.
In a way to improve customer services e-commerce companies are leveraging data science algorithms. They use ML to equip their websites with recommender systems (RS). They generate offers that attract customers.
RS helps customers to reduce search time and get access to the needed information. Moreover, it can suggest offers they would have never thought about, but can be interested in. Such moments increase brand loyalty and boost sales as a result of better customer experience.
ML and AI algorithms surf the web all the time. They study market by searching and analyse information of your competitors for the same or similar products. Algorithms pay attention to sales, last minute offers, and gathering data about the price history over the last weeks.
According to variety external factors, market demand, and offer, machine learning can automatically adjust and optimize prices.
Customers prefer to look first before to buy something. But sometimes they just don’t know or can’t find appropriate words to describe what they are looking for. The visual search helps consumers to find exactly necessary commodities.
How does it work? User just need to upload an image. It will help to narrow the search down to more accurate items.
Customer Behavior Prediction
Customer behavior prediction gives an opportunity to find out their action during shopping process. It is possible due to data analysis of previous behaviors. Except the prediction, this systems allows to split customers into similar groups and supply each of them with personalized offers.
From time to time customers need some help or consultation. In such cases chatbot became the best friend for your site users. Virtual assistant can answer questions, ease catalog search or advise your buyers some specific offers. All of these add value to your services,boost sales, and improve client retention.
In part 2, we’ll discuss how ML and AI technologies can be used in healthcare, telecom, and connected cars domains.