How will smart technology impact retail?
Over the past few years, the retail industry has been revolutionized by technology.
From the way stores operate internally on a day-to-day basis to the way consumers buy and purchase products to marketing strategies, the world of retail is completely different than it once was. While access to the internet, evolving software packages, smartphones and new technologies have had a huge impact on the retail industry so far, smart technologies such as IoT will have a huge impact in the future.
IOT is an acronym for Internet of Things and consists of software, hardware, system integration, data services and access to telecommunications services that are more advanced than ever before. At its core, IoT is centered around how our devices and technologies are interconnected and the way they interact with each other and with us, the users. IoT has the potential to solve countless problems across a range of industries with new innovative solutions, and the retail industry is no exception.
Let’s take a look at how the Internet of Things and other digital technologies will impact the development of the retail industry.
Employee Management
As a retailer, it is crucial to manage your employees as efficiently as possible. If you don't have enough employees to meet your business needs, your retail business will eventually fail. In recent years, it has become increasingly possible to use the Internet of Things to handle employee scheduling for retailers. Business owners can simply create timesheets online and have up-to-date employee timesheets sent directly to employees' mobile devices. Employees can often clock in from their devices using GPS location to prove they are actually at work and ready to work on site. This integration of technology has completely changed the game for retailers when it comes to managing their teams and will continue to play an important role in how retailers manage their retail teams.
Inventory and Supply Chain
Many traditional retail stores already use smart shelf technology to monitor their inventory levels. With this innovative approach, store managers can access real-time details and reports on in-stock products and sales levels. These systems utilize RFID (Radio Frequency Identification) technology to provide the most accurate results. In these systems, each product is attached with an RFID tag, and an RFID reader is used to read the tag’s details and transmit the tag’s details via an antenna to an IoT platform, where the information is then processed. This enables retailers to monitor inventory levels across their entire supply chain, giving them back control over the development of their retail operations.
Targeted Notifications
On the marketing front, retailers are also leveraging IoT technology. Targeted event details, discount coupons and other offers are sent to consumers’ smartphones within a specific geographical area, allowing retailers to directly target consumers who may be interested in their products. When customers receive this information, they are more likely to venture in-store to take advantage of any offers the retailer has to offer. Whether it's discounts, sales, specials, events, contests or live promotions, retailers can directly reach consumers in areas where they are most likely to be interested and take action.
Cashierless Checkout
Many large supermarkets have already implemented cashierless checkout with great success, and it was only a matter of time before this technology started to appear in other types of retail stores. Using a combination of cameras, apps, and point-of-sale systems, customers can proceed to the checkout to complete their purchase without any human assistance. Over time, AI systems will help take this process to the next level, even identifying when shoplifting or other suspicious behavior is occurring in stores and checkouts. These systems will also be integrated with inventory and supply chain management systems to provide retailers with an all-in-one solution centered on IoT technology.
Facial Recognition
Facial recognition software is already used for security purposes in shopping malls and large supermarkets around the world, and the technology is improving all the time. However, in the future, we may see facial recognition systems being used to increase customer engagement through digital signage displays. When a store identifies a specific customer, the display will be able to push different signage that will be more appealing to that person, thereby enhancing their in-store experience and increasing the likelihood that they will complete a sale.
The future of retail will rely on digital technology moving forward
While the retail industry already makes heavy use of digital technology, we can expect it to play an even greater role in retail stores of all shapes and sizes role. With so much to gain from these evolving technologies, such as the Internet of Things, it is only a matter of time before more retailers explore the possibilities that digital technology has to offer.
The above is the detailed content of How will smart technology impact retail?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S

According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
