Artificial intelligence (AI – Artificial Intelligence) is a set of algorithms that, in the learning process, can change and adapt to the goal, imitating the unique flexible thinking of the human brain.
AI’s principle is working not just with “cold” data but with accumulated experience, building non-linear relationships between input and output data, and constant self-learning. Based on this, forecasts are made in the future. Similarly, information is organized and interconnected by master data management systems (master data management, or MDM).
The human brain is limited by both operating time and performance. It is not able to process the amount of data that is generated in the information space today.
The International Data Corporation estimates that the amount of information created over the next three years will exceed the amount of data that has emerged over the past three decades. And over the next five years, the world will generate three times more information than in the previous five years. And this will encourage the active use of AI to collect and process information.
The possibilities of artificial intelligence open up the scope for a more efficient and faster search for new knowledge, determining the best-personalized recommendations, and automating business processes.
The main goal of AI is quite transparent – to replace the human ability to analyze, to create a system with intelligent behavior capable of self-learning, which can make predictions, think, understand, and adapt to various tasks in an ever-changing environment.
E-commerce is growing at a tremendous speed and with the help of AI (artificial intelligence) some tasks can be performed more effectively for sales planning, communicating with customers, publishing new products in several sales channels at the same time, automating targeted advertising, personalizing offers for consumers, and providing discounts to regular customers. Let’s take a closer look at how artificial intelligence is helping online retailers.
- Chatbots and virtual assistants
Given the massive amount of data and transactions generated in e-commerce, automation is needed at all stages – communication with the client, processing orders, and accepting payments. Some actions are automated simply using software integrations and APIs. Other parts require more complex solutions.
You can consider such automation using the example of chatbots. Some of them are algorithmic and created based on rules. They determine the user’s query by keywords in a text message and issue pre-programmed responses or perform some action (send links, accept payments, etc.). Artificial intelligence technologies come into play when a chatbot needs to recognize voice commands and choose from a more complex set of keywords and responses. Bots based on artificial intelligence, machine learning, and neural networks are more advanced and “smarter”; they better understand and help the human user.
Examples of such AI-based bots are Google’s Alexa and Google’s Siri. Alibaba uses Tmall Genie and Ali Assistant to process up to 95% of incoming written and voice requests. The use of such automation affects the customer experience in two ways. On the one hand, a robot that does not understand requests quickly enough or does not give a satisfactory answer to them can annoy customers. On the other hand, shoppers can quickly get an answer to their questions at any time of the day, and the ability to reduce the cost of hiring and training operators allows retailers to reduce costs and prices.
Amazon’s Alexa virtual assistant helps users get information, control home appliances, make marketplace purchases, or order food delivery using voice commands. Naturally, this greatly simplifies the buying process and increases the revenue of the IT giant, and Alexa’s style tips are already becoming as good as the opinions of human experts.
- Personalized offers and improved customer recommendations
According to Epsilon, 80% of customers are more likely to make a purchase if they are offered a personalized experience. Based on purchase history, customer preferences, and information about themselves and their behavior on the site, brands can more accurately predict customer behavior and make offers at the right time on the right platform.
Even such an ordinary thing as a product description can be individual. If a shopper wants to control their spending, it makes sense to focus their attention on a sale price or promotion, and for brand loyalists, highlight the name of their favorite brand.
One example of this personalized approach is Shopbot on eBay. It remembers the customer’s preferences, offers customized products in the right size or brand, and can search for products by photos.
Samsung’s Family Hub Refrigerator uses AI and internal cameras to keep track of stored food. Based on this data, it can remind the user when certain products are running out or even order them himself and suggest recipes based on what is at home.
Beauty brand Sephora uses artificial intelligence and augmented reality to help customers choose cosmetics and try on makeup.
The main goal of such innovations is to increase sales in the moment, create a unique user experience wow effect, and increase customer loyalty.
- Predictive Marketing
Suppose with the help of artificial intelligence, it is possible to predict the desires and behavior of one customer. What prevents us from predicting the aggregate behavior of all customers? Artificial intelligence technology made it possible to process vast information from store shelves, showcases on Internet sites, and search engine queries to predict the fall and rise in demand for product categories and individual products. Depending on this, brands and retailers plan, start, and stop marketing activities, advertising promotions, and promotions.
Syntes MDM, our e-commerce data management system, helps you interact with advertising systems automatically and link advertising campaigns with stock balances.
- Filtering Fake Reviews
Reviews play a significant role in users’ purchasing decisions. According to a study by Dimensional Research, 90% of the time, reviews influence a purchase decision.
At the same time, all major marketplaces face the problem of fake reviews, both positive and negative. Fake reviews and inflated ratings reduce customer confidence in websites and marketplaces. But to check them all, it would take a whole army of moderators.
Amazon uses artificial intelligence to analyze and manage reviews. It is based on the ratings of the authors, the reactions of site visitors, and the “naturalness” of the information. The company deletes hundreds of thousands of reviews every month, but the recognition technology still needs to be improved.
- Smart logistics
Recent years have drawn attention to building efficient supply chains. Constant and sudden changes in the existing delivery routes have actualized logistics issues. Artificial intelligence has proved helpful in this area as well. With its help, companies automate warehouse operations and delivery, increase the speed and efficiency of sorting goods in warehouses, and reduce costs.
For example, Amazon and JD.com use robotic assistants to replace manual labor. Due to such operations, the Chinese IT giant reduced the number of employees from 120 thousand to 80 thousand people and significantly reduced its costs.
Alibaba uses artificial intelligence to build the most efficient shipping routes. Smart logistics has reduced vehicle usage by 10% and travel distance by 30%.
Using artificial intelligence, Walmart hypermarkets plan stocks in warehouses, centralize purchases, reduce write-offs, and increase warehouse throughput. Forecasting covers not only the sales volume of a particular product but also what kind of product the buyer wants to see in stores.
E-commerce is a promising direction. In the age of digital progress, more and more people are actively using the Internet everywhere and always. It is estimated that by 2040 up to 95% of purchases will be made online.
Artificial intelligence in this area gives additional competitive advantages. With its help, brands increase the number of initial and repeat purchases, increase conversions, reduce advertising and operational costs, improve user experience, and gain new followers.
Modern technologies of machine learning, neural networks, and artificial intelligence effectively and independently monitor and manage fulfillment processes, predict buyers’ desires and attract them with individual offers, and help solve security problems.
The Syntes MDM platform, designed to manage all e-commerce data, also uses the latest technology, and allows you to set up advertising in semi-automatic and automatic modes. If you would like to discuss Syntes MDM for your business, we invite you to sign up for a demo.
Syntes, an international company, develops a next-generation MDM (Master Data Management) and PIM (Product Information Management) cloud platform and provides brands and manufacturers with services for creating, managing and automating D2C (Direct-to-Customer) sales and marketing channels. Syntes solutions and services are used by the world’s leading brands and manufacturers of consumer and business products such as Razer, Scarlett, Pantone, X-Rite, AVerMedia and others. Syntes is a registered trademark of Syntes, Inc.
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