Empower Your Business With The Magic Of Machine Learning!
The future of shopping is consumer defined, and brands that
offer relevancy, convenience, and seamless experiences will
come out on top. Consumers expect their online and in-store shopping to offer
a similar experience. One that is personalized and catered to them. That is the gap that Mobiplus aims to bridge.
Our technology uses e-shops and ERPs shopping Purchase Data and proprietary machine learning algorithms and creates seven eshop specific recommendation engines which connect easily with your e-shop through an API!
After the user makes few clicks he receives recommended products in a front page carousel with 7 products recommended from the cluster that that the user belongs based on clicks, that is, those products he is now looking . In the first entry of the user will recommend the most popular and then after 2-3 click, will go to User Recommendation architecture.
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This carousel with recommended products is placed under the product that the user is visiting. The recommend products are based on content recommendation architecture with word2vec and technologies from the cluster of these products. They are from the same category or close to the current category to help the user find the product he wants!
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Recommended Products are placed over similar Products in product page for guests and for login users under the product they are viewing. The recommended products have the same style and appearance with up to 60% similarity, using mobiplus image shopping recommender to help the user find a products with the same style and design…i.e. special sofas, dining tables, fixtures, clothing, footwear etc. The Recommender Engine is based in Convolutional Neural Network architecture.
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Using user based recommendation architecture we take into consideration the user’s purchase history to date as well as the clicks he has done on the existing session to better understand his needs.
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Recommended Products with item to item recommendation architecture based on the current shopping cart having found the products that are purchased together for your e-shop..i.e. with shoes recommends socks!
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When the consumer browses in the e-shop we use clicks , put items to basket, or favorites in real time for updating the recommendations real time and for continuous training of recommendation engine.
Additionally, the Recommender Engines are trained every week using data from the new products and purchases that were made on the platform.
Model that takes into account products purchased at this time of the year and corresponding seasons in the past and recommends products taking into account seasonality .This model runs on the top of the previous models.
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It is well known that human behavior, and in particular consumer behavior, can be predicted. At present computers posses significant computing power and gather huge amount of data from our digital transactions.
As a result, banks, financial institutions, retailers, political campaigns, hospitals, judges, companies and organizations, have been able to predict the behavior of people.
These efforts, helped win clients, elections and battles against various diseases.
Annie is an Intelligent digital instore Shopping Assistant which offers personal, delightful experience to consumers, helping them find the products they desire and collects rich shopping data that helps you increase your revenue.
Annie Intelligent in store shopping assistant utilizes artificial intelligence and machine learning to provide customers with a personalized shopping experience.
It uses data on customer behavior and preferences to make product recommendations and answer questions in real-time.
It connects with mobiplus shopping recommendation platform for predicting and analyzing the shopping data.
It displays product recommendations in digital display in store and shoppers Smartphone and collects the customer's contact and shipping data, making your store digital!
Customers can interact with Annie through voice, text, and touch on the screen, making it easy to use and accessible for all customers.
Annie provides a unique and innovative solution for retailers looking to personalize the shopping experience for their customers. By utilizing artificial intelligence and machine learning algorithms, the platform provides relevant and personalized product recommendations, answers to customer questions, and an easy-to-use interface, leading to increased customer satisfaction and loyalty.
Read our book and learn why instore personalization and shopping data is the name of the game. The book covers:
Read articles on how to take your company into the new era with shopping recommendations and artificial intelligence in Retail.
Mobiplus recommendation platform enables e-commerce businesses and retail stores to move in the next era of shopping using Artificial...
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Mobiplus recommendation platform enables Undergrounshop to move in the next era of shopping using Artificial Intelligence and shopping data!...
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