查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1597208

AI 商店管理工具市場報告：2030 年趨勢、預測與競爭分析

AI Store Manager Tool Market Report: Trends, Forecast and Competitive Analysis to 2030
出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3個工作天內

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

簡介目錄

AI Store Manager工具趨勢與預測

預計到 2030 年，全球人工智慧店長工具市場將達到 3.25 億美元，2024 年至 2030 年複合年成長率為 25.3%。該市場的主要驅動力是對人工智慧主導的庫存管理的需求不斷增加，電子商務的成長推動了人工智慧工具的採用，以提供個性化的客戶推薦和業務效率，以最佳化商店營運，人工智慧的採用率最高。全球人工智慧商店經理工具市場的未來前景廣闊，庫存管理、POS 系統、員工調度和任務管理市場都有機會。

  • Lucintel 預測，按類型類別，軟體將在預測期內呈現高速成長。
  • 從應用來看，庫存管理預計將在預測期內實現最高成長。
  • 從地區來看，亞太地區預計將在預測期內實現最高成長。

AI店長工具市場的策略成長機會

人工智慧商店管理工具市場在各種應用程式中提供了多種策略成長機會。透過專注於這些機會，企業可以利用人工智慧技術推動創新、改善商店管理並滿足不斷變化的消費者需求。

  • 人工智慧驅動的客戶分析：投資人工智慧驅動的客戶分析可以透過提供對客戶行為和偏好的深入洞察來提供成長機會。這些工具分析購買歷史記錄、瀏覽模式和人口統計資料，以提供個人化建議和有針對性的行銷策略。這種方法增強了客戶參與並增加了銷售的可能性。
  • 自動化庫存管理：自動化庫存管理系統透過最佳化存量基準和減少體力勞動提供顯著的成長機會。人工智慧工具可以預測需求、即時追蹤庫存並自動化補貨流程。這種效率可以節省成本並提高存貨周轉，使其成為重要的投資領域。
  • 智慧門市佈局最佳化：根據客流模式和銷售資料最佳化門市佈局的人工智慧工具具有巨大的成長潛力。透過分析顧客如何在商店中移動，這些工具提案最佳的產品佈局和商店設計。這種最佳化可透過提高產品可見度和可近性來改善購物體驗並增加銷售量。
  • 推動能源效率解決方案：人工智慧驅動的能源效率解決方案是一個不斷成長的市場領域。這些工具透過基於即時資料的自動化照明、暖氣和冷氣系統來管理商店的能源消耗。投資節能技術使零售商能夠降低營運成本並支持永續舉措，從而提供策略性成長機會。
  • 商店中的機器人和自動化：機器人和自動化在商店管理中的整合帶來了巨大的成長機會。人工智慧驅動的機器人可以執行諸如給貨架補貨、與客戶互動以及管理庫存業務。這種自動化降低了人事費用，提高了業務效率，並改善了整體購物體驗。

這些策略性成長機會透過增強客戶分析、自動化庫存管理、最佳化商店佈局、提高能源效率和整合機器人技術，正在塑造人工智慧商店經理工具市場。透過專注於這些領域，公司可以推動創新、改善商店營運並滿足不斷變化的消費者需求。

AI 商店管理工具市場促進因素/挑戰

人工智慧商店管理工具市場受到影響其成長和開拓的各種促進因素​​和挑戰的影響。這些因素包括技術進步、經濟狀況和監管因素，這些因素影響人工智慧工具在零售管理中的採用和有效性。

推動人工智慧商店經理工具市場的因素是：

  • 技術進步：人工智慧和機器學習技術的快速進步正在推動人工智慧商店管理工具市場的成長。預測分析、自然語言處理和自動化方面的創新將增強商店管理工具並提高業務效率和客戶體驗。
  • 對效率的需求不斷增加：零售公司正在尋求提高業務效率和降低成本的解決方案。 AI 商店管理工具提供自動化、進階分析和最佳化的庫存管理來滿足這些需求。對效率的日益關注正在推動人工智慧技術在零售環境中的採用。
  • 消費者對個人化的期望：消費者越來越期望個人化的購物體驗，人工智慧工具正在幫助零售商滿足這些期望。透過分析客戶資料，人工智慧系統可以提供個人化建議和有針對性的行銷，以提高客戶參與和滿意度。這一趨勢是採用人工智慧工具的關鍵驅動力。
  • 與全通路零售整合：人工智慧店長工具與全通路零售策略的整合增加了其吸引力。人工智慧技術實現線上線下通路的無縫協作，改善跨平台的庫存管理和客戶互動。這種整合正在推動市場成長。
  • 注重資料主導決策：零售企業越來越依賴資料主導決策來最佳化營運和策略。 AI 商店經理工具透過進階分析提供寶貴的見解，使零售商能夠就庫存、促銷和客戶參與做出明智的決策。對資料的關注正在推動人工智慧工具的採用。

AI店長工具市場面臨的挑戰如下：

  • 高實施成本：人工智慧商店經理工具的實施成本可能成為一些零售商的障礙。獲取和整合先進人工智慧技術的成本以及專業培訓的需求可能會限制其採用，特別是對於預算有限的中小型企業。
  • 資料隱私和安全問題：資料隱私和安全問題是人工智慧商店管理工具市場的關鍵問題。零售公司必須確保客戶資料受到保護，其人工智慧系統符合資料保護條例。解決這些問題對於維護消費者信心和遵守法規至關重要。
  • 與現有系統整合：將人工智慧商店管理工具與現有零售系統和基礎設施整合可能很複雜。相容性問題和客製化要求可能是一個挑戰，需要仔細規劃和執行。成功的整合對於實現人工智慧技術的全部優勢至關重要。

目錄

第1章執行摘要

第2章全球人工智慧店長工具市場：市場動態

  • 簡介、背景、分類
  • 供應鏈
  • 產業促進因素與挑戰

第3章 2018-2030年市場趨勢及預測分析

  • 宏觀經濟趨勢（2018-2023）與預測（2024-2030）
  • 全球人工智慧商店經理工具市場趨勢（2018-2023）與預測（2024-2030）
  • 全球人工智慧商店管理工具市場（按類型）
    • 軟體
    • 服務
  • 全球人工智慧商店管理工具市場（按應用）
    • 庫存管理
    • POS系統
    • 員工排班管理
    • 工作管理
    • 其他

第4章 2018-2030年區域市場趨勢及預測分析

  • AI商店管理工具市場（按地區）
  • 北美AI店長工具市場
  • 歐洲人工智慧商店經理工具市場
  • 亞太人工智慧商店經理工具市場
  • 其他地區AI店長工具市場

第5章 競爭分析

  • 產品系列分析
  • 營運整合
  • 波特五力分析

第6章 成長機會與策略分析

  • 成長機會分析
    • 全球人工智慧商店管理工具市場成長機會（按類型）
    • 全球人工智慧商店管理工具市場成長機會（按應用）
    • 全球人工智慧商店經理工具市場成長機會（按地區）
  • 全球人工智慧商店經理工具市場的新興趨勢
  • 戰略分析
    • 新產品開發
    • 全球AI店長工具市場容量擴張
    • 全球人工智慧商店管理工具市場的併購和合資企業
    • 認證和許可

第7章主要企業概況

  • Zebra Technologies
  • RetailNext
  • Blue Yonder
  • SAP
  • IBM
  • Manthan
  • Symphony Retailal
簡介目錄

AI Store Manager Tool Trends and Forecast

The future of the global AI store manager tool market looks promising with opportunities in the inventory management, pos system, employee scheduling, and task management markets. The global AI store manager tool market is expected to reach an estimated $325 million by 2030 with a CAGR of 25.3% from 2024 to 2030. The major drivers for this market are an increase in demand for AI-driven inventory management, the growth of e-commerce driving the adoption of AI tools for personalized customer recommendations and operational efficiency, and the highest adoption of AI to optimize store operations.

  • Lucintel forecasts that, within the type category, software is expected to witness higher growth over the forecast period.
  • Within the application category, inventory management is expected to witness the largest growth over the forecast period.
  • In terms of regions, APAC is expected to witness the highest growth over the forecast period.

Gain valuable insights for your business decisions with our comprehensive 150+ page report.

Emerging Trends in the AI Store Manager Tool Market

Emerging trends in the AI store manager tool market are reshaping the landscape of retail management. These trends reflect technological advancements and changing consumer expectations, driving innovation and improving operational efficiency in the retail sector.

  • Enhanced Inventory Management: AI tools are increasingly being used for advanced inventory management. Machine learning algorithms analyze sales data to predict demand and optimize stock levels. This trend reduces overstock and stockouts, improving inventory turnover and reducing costs. Enhanced inventory management also leads to more efficient supply chain operations and better customer satisfaction.
  • Personalized Customer Experiences: AI is enabling more personalized shopping experiences through targeted recommendations and tailored promotions. By analyzing customer data and purchase history, AI tools provide personalized product suggestions and marketing messages. This personalization enhances customer engagement and loyalty, driving sales and improving overall shopping satisfaction.
  • Automation of Routine Tasks: Routine tasks in store management, such as restocking and checkout processes, are increasingly being automated with AI and robotics. Automation reduces the need for manual labor, increases operational efficiency, and allows staff to focus on more strategic tasks. This trend is leading to more streamlined operations and cost savings for retailers.
  • Real-Time Analytics and Insights: AI store manager tools are providing real-time analytics and insights into store performance and customer behavior. These tools offer actionable data on sales trends, foot traffic, and customer preferences, enabling retailers to make informed decisions and quickly adapt to changing market conditions. Real-time analytics enhance decision-making and improve overall store management.
  • Integration with IoT: The integration of AI with the Internet of Things (IoT) is creating smarter store environments. IoT devices collect data on various aspects of store operations, which AI tools analyze to optimize inventory, improve customer experiences, and manage energy consumption. This integration enhances operational efficiency and enables more proactive management of store resources.

These emerging trends are driving significant advancements in the AI store manager tool market. Enhanced inventory management, personalized customer experiences, automation, real-time analytics, and IoT integration are transforming retail operations, improving efficiency, and meeting evolving consumer expectations.

Recent Developments in the AI Store Manager Tool Market

Recent developments in the AI store manager tool market highlight key advancements that are transforming retail management. These developments reflect the growing adoption of AI technologies to streamline operations, enhance customer experiences, and improve overall store efficiency.

  • Advanced Predictive Analytics: AI tools now feature advanced predictive analytics capabilities that forecast demand and optimize inventory levels. By analyzing historical sales data and market trends, these tools provide accurate predictions that help retailers manage stock more effectively and reduce costs associated with overstock or stockouts.
  • Integration with Augmented Reality (AR): AI store manager tools are increasingly integrating with augmented reality (AR) to enhance the shopping experience. AR applications allow customers to visualize products in their own space or get interactive in-store experiences, which can boost engagement and sales. Retailers are leveraging this technology to create more immersive shopping environments.
  • Enhanced Customer Interaction Tools: New AI tools are focusing on improving customer interactions through chatbots and virtual assistants. These tools provide instant support and personalized recommendations, enhancing the overall customer experience. By automating customer service and providing real-time assistance, retailers can improve satisfaction and drive loyalty.
  • Energy Management Solutions: AI-driven energy management solutions are being developed to optimize energy use in stores. These tools analyze energy consumption patterns and automate controls for lighting, heating, and cooling systems. This development helps retailers reduce energy costs and improve sustainability efforts.
  • Improved Workforce Management: AI tools are offering advanced workforce management features, including automated scheduling and task prioritization. By analyzing employee performance and store needs, these tools optimize staff allocation and improve operational efficiency. This development addresses challenges related to labor management and enhances overall productivity.

These recent developments are significantly impacting the AI store manager tool market by introducing more advanced predictive analytics, AR integration, customer interaction tools, energy management solutions, and workforce management features. These innovations are enhancing store operations, improving customer experiences, and driving efficiency in the retail sector.

Strategic Growth Opportunities for AI Store Manager Tool Market

The AI store manager tool market presents several strategic growth opportunities across various applications. By focusing on these opportunities, businesses can leverage AI technologies to drive innovation, improve store management, and meet evolving consumer needs.

  • AI-Powered Customer Analytics: Investing in AI-powered customer analytics offers growth opportunities by providing deeper insights into customer behavior and preferences. These tools analyze purchase history, browsing patterns, and demographic data to deliver personalized recommendations and targeted marketing strategies. This approach enhances customer engagement and increases sales potential.
  • Automated Inventory Management: Automated inventory management systems present a significant growth opportunity by optimizing stock levels and reducing manual labor. AI tools can forecast demand, track inventory in real-time, and automate replenishment processes. This efficiency leads to cost savings and improved inventory turnover, making it a key area for investment.
  • Smart Store Layout Optimization: AI tools that optimize store layouts based on customer traffic patterns and sales data offer substantial growth potential. By analyzing how customers navigate the store, these tools suggest optimal product placements and store designs. This optimization enhances the shopping experience and increases sales through better product visibility and accessibility.
  • Enhanced Energy Efficiency Solutions: AI-driven energy efficiency solutions represent a growing market segment. These tools manage energy consumption in stores by automating lighting, heating, and cooling systems based on real-time data. Investing in energy-efficient technologies helps retailers reduce operational costs and support sustainability initiatives, presenting a strategic growth opportunity.
  • Robotics and Automation in Stores: The integration of robotics and automation in store management presents a significant growth opportunity. AI-powered robots can handle tasks such as restocking shelves, assisting customers, and managing inventory. This automation reduces labor costs, increases operational efficiency, and enhances the overall shopping experience.

These strategic growth opportunities are shaping the AI store manager tool market by enhancing customer analytics, automating inventory management, optimizing store layouts, improving energy efficiency, and integrating robotics. By focusing on these areas, businesses can drive innovation, improve store operations, and meet evolving consumer demands.

AI Store Manager Tool Market Driver and Challenges

The AI store manager tool market is influenced by various drivers and challenges that impact its growth and development. These factors include technological advancements, economic conditions, and regulatory considerations, which shape the adoption and effectiveness of AI tools in retail management.

The factors responsible for driving the AI store manager tool market include:

  • Technological Advancements: Rapid advancements in AI and machine learning technologies are driving the growth of the AI store manager tool market. Innovations in predictive analytics, natural language processing, and automation enhance the capabilities of store management tools, improving operational efficiency and customer experiences.
  • Increasing Demand for Efficiency: Retailers are seeking solutions to enhance operational efficiency and reduce costs. AI store manager tools offer automation, advanced analytics, and optimized inventory management, addressing these needs. The growing emphasis on efficiency is driving the adoption of AI technologies in retail environments.
  • Consumer Expectations for Personalization: Consumers increasingly expect personalized shopping experiences, and AI tools help retailers meet these expectations. By analyzing customer data, AI systems provide tailored recommendations and targeted marketing, improving customer engagement and satisfaction. This trend is a key driver of AI tool adoption.
  • Integration with Omnichannel Retailing: The integration of AI store manager tools with omnichannel retailing strategies is enhancing their appeal. AI technologies enable seamless coordination between online and offline channels, improving inventory management and customer interactions across multiple platforms. This integration is driving market growth.
  • Focus on Data-Driven Decision Making: Retailers are increasingly relying on data-driven decision-making to optimize operations and strategy. AI store manager tools provide valuable insights through advanced analytics, enabling retailers to make informed decisions about inventory, promotions, and customer engagement. This focus on data is driving the adoption of AI tools.

Challenges in the AI store manager tool market include:

  • High Implementation Costs: The cost of implementing AI store manager tools can be a barrier for some retailers. The expense of acquiring and integrating advanced AI technologies, along with the need for specialized training, may limit adoption, especially for smaller businesses with limited budgets.
  • Data Privacy and Security Concerns: Data privacy and security concerns are significant challenges in the AI store manager tool market. Retailers must ensure that customer data is protected and that AI systems comply with data protection regulations. Addressing these concerns is essential for maintaining consumer trust and regulatory compliance.
  • Integration with Existing Systems: Integrating AI store manager tools with existing retail systems and infrastructure can be complex. Compatibility issues and the need for customization may pose challenges, requiring careful planning and execution. Successful integration is crucial for realizing the full benefits of AI technologies.

Technological advancements, efficiency demands, consumer expectations, omnichannel integration, and data-driven decision-making are driving the AI store manager tool market. However, high implementation costs, data privacy concerns, and integration challenges must be addressed. These factors collectively influence market growth and the adoption of AI tools in retail management.

List of AI Store Manager Tool Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies AI store manager tool companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the AI store manager tool companies profiled in this report include-

  • Zebra Technologies
  • RetailNext
  • Blue Yonder
  • SAP
  • IBM
  • Manthan
  • Symphony Retailal

AI Store Manager Tool by Segment

The study includes a forecast for the global AI store manager tool market by type, application, and region.

AI Store Manager Tool Market by Type [Analysis by Value from 2018 to 2030]:

  • Software
  • Service

AI Store Manager Tool Market by Application [Analysis by Value from 2018 to 2030]:

  • Inventory Management
  • POS Systems
  • Employee Scheduling
  • Task Management
  • Others

AI Store Manager Tool Market by Region [Analysis by Value from 2018 to 2030]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

Country Wise Outlook for the AI Store Manager Tool Market

The AI store manager tool market is evolving rapidly as businesses leverage artificial intelligence to enhance operational efficiency and customer experience. Recent developments reflect a trend towards more sophisticated tools that integrate with various retail operations, streamline inventory management, and provide valuable insights into consumer behavior. These advancements are transforming how retailers manage their stores and respond to market demands.

  • United States: In the U.S., AI store manager tools are focusing on enhancing inventory management and personalized customer service. Companies like Microsoft and IBM are integrating AI with IoT to optimize stock levels and predict demand more accurately. AI-driven analytics are being used to offer real-time insights into consumer behavior, helping retailers to tailor marketing strategies and improve store layout. The emphasis is also on improving workforce management through AI-powered scheduling and task automation.
  • China: China's AI store manager tools are rapidly advancing with a strong focus on automation and customer engagement. Alibaba and JD.com are leading innovations with AI systems that automate inventory replenishment and use facial recognition to personalize shopping experiences. The integration of AI with big data analytics is enhancing predictive capabilities, allowing for more efficient supply chain management and targeted promotions. Retailers are investing heavily in smart store technologies to enhance consumer interactions.
  • Germany: In Germany, AI store manager tools are being adopted to improve operational efficiency and sustainability. Companies like SAP are developing AI solutions that optimize inventory management and reduce waste. The focus is on using AI for data-driven decision-making, with retailers utilizing predictive analytics to forecast demand and manage stock levels effectively. The integration of AI with renewable energy management systems is also gaining traction, helping retailers reduce energy costs and enhance their sustainability efforts.
  • India: The AI store manager tool market in India is witnessing significant growth as retailers embrace digital transformation. Companies like Flipkart and Tata are investing in AI solutions for better inventory management and customer engagement. AI-driven chatbots are being deployed to enhance customer service, while predictive analytics are being utilized to optimize product assortments based on consumer preferences. The emphasis on improving operational efficiency and enhancing the shopping experience is driving the adoption of AI technologies in the retail sector.
  • Japan: Japan's retail sector is leveraging AI store manager tools to enhance automation and customer experience. Companies like SoftBank and Rakuten are at the forefront of integrating AI technologies into retail operations. AI is being used to optimize supply chains, manage inventory, and personalize customer interactions through targeted marketing campaigns. The focus on robotics and automation is also notable, with retailers exploring AI-driven robots for restocking shelves and assisting customers in-store.

Features of the Global AI Store Manager Tool Market

Market Size Estimates: AI store manager tool market size estimation in terms of value ($M).

Trend and Forecast Analysis: Market trends (2018 to 2023) and forecast (2024 to 2030) by various segments and regions.

Segmentation Analysis: AI store manager tool market size by type, application, and region in terms of value ($M).

Regional Analysis: AI store manager tool market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the AI store manager tool market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the AI store manager tool market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

If you are looking to expand your business in this market or adjacent markets, then contact us. We have done hundreds of strategic consulting projects in market entry, opportunity screening, due diligence, supply chain analysis, M & A, and more.

This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the AI store manager tool market by type (software and service), application (inventory management, pos systems, employee scheduling, task management, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?
  • Market Report

Table of Contents

1. Executive Summary

2. Global AI Store Manager Tool Market : Market Dynamics

  • 2.1: Introduction, Background, and Classifications
  • 2.2: Supply Chain
  • 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2018 to 2030

  • 3.1. Macroeconomic Trends (2018-2023) and Forecast (2024-2030)
  • 3.2. Global AI Store Manager Tool Market Trends (2018-2023) and Forecast (2024-2030)
  • 3.3: Global AI Store Manager Tool Market by Type
    • 3.3.1: Software
    • 3.3.2: Service
  • 3.4: Global AI Store Manager Tool Market by Application
    • 3.4.1: Inventory Management
    • 3.4.2: POS Systems
    • 3.4.3: Employee Scheduling
    • 3.4.4: Task Management
    • 3.4.5: Others

4. Market Trends and Forecast Analysis by Region from 2018 to 2030

  • 4.1: Global AI Store Manager Tool Market by Region
  • 4.2: North American AI Store Manager Tool Market
    • 4.2.1: North American AI Store Manager Tool Market by Type: Software and Service
    • 4.2.2: North American AI Store Manager Tool Market by Application: Inventory Management, POS Systems, Employee Scheduling, Task Management, and Others
  • 4.3: European AI Store Manager Tool Market
    • 4.3.1: European AI Store Manager Tool Market by Type: Software and Service
    • 4.3.2: European AI Store Manager Tool Market by Application: Inventory Management, POS Systems, Employee Scheduling, Task Management, and Others
  • 4.4: APAC AI Store Manager Tool Market
    • 4.4.1: APAC AI Store Manager Tool Market by Type: Software and Service
    • 4.4.2: APAC AI Store Manager Tool Market by Application: Inventory Management, POS Systems, Employee Scheduling, Task Management, and Others
  • 4.5: ROW AI Store Manager Tool Market
    • 4.5.1: ROW AI Store Manager Tool Market by Type: Software and Service
    • 4.5.2: ROW AI Store Manager Tool Market by Application: Inventory Management, POS Systems, Employee Scheduling, Task Management, and Others

5. Competitor Analysis

  • 5.1: Product Portfolio Analysis
  • 5.2: Operational Integration
  • 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

  • 6.1: Growth Opportunity Analysis
    • 6.1.1: Growth Opportunities for the Global AI Store Manager Tool Market by Type
    • 6.1.2: Growth Opportunities for the Global AI Store Manager Tool Market by Application
    • 6.1.3: Growth Opportunities for the Global AI Store Manager Tool Market by Region
  • 6.2: Emerging Trends in the Global AI Store Manager Tool Market
  • 6.3: Strategic Analysis
    • 6.3.1: New Product Development
    • 6.3.2: Capacity Expansion of the Global AI Store Manager Tool Market
    • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global AI Store Manager Tool Market
    • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

  • 7.1: Zebra Technologies
  • 7.2: RetailNext
  • 7.3: Blue Yonder
  • 7.4: SAP
  • 7.5: IBM
  • 7.6: Manthan
  • 7.7: Symphony Retailal