Dublin, April 15, 2019 (GLOBE NEWSWIRE) -- The "In-store Analytics Market by Application, Component, Deployment, Organization Size, and Region - Global Forecast to 2023" report has been added to ResearchAndMarkets.com's offering.
The global in-store analytics market size is expected to grow from USD 1,126.9 million in 2018 to USD 3,239.4 million by 2023, at a CAGR of 23.5% during the forecast period.
In-store analytics, an advanced analytics solution, is useful for store retailers to measure and analyze the real-time behavior of their customers, examine store operations, devise effective campaigns, and prevent retail losses. It can be applied to the end-to-end operations of retail stores to transform their business with stronger customer relationships, more profitable growth, and unique competitive advantages. Hence, it enables retailers to gain deep insights into retail operations, customer behavior, and marketing campaign effectiveness.
In-store analytics has gained major market traction across the globe, due to its capability of analyzing huge data volumes flooding the retail industry. Today's in-store retail environment is more competitive than it was a few years ago. The increasing significance of eCommerce has compelled retail stores to leverage big data and analytics technologies for remaining competitive and catering to customers in a better manner.
The vendors in the in-store analytics market have adopted various organic as well as inorganic growth strategies, such as new product launches; product upgradations; partnerships, collaborations, and agreements; and business expansions, to expand their offerings in the market.
Key Topics Covered:
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Market Opportunities in the In-Store Analytics Market
4.2 Market By Application (2018-2023)
4.3 Market By Organization Size (2018-2023)
4.4 Market Share Across Regions
5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increased Competition From Ecommerce Players
5.2.1.2 Need for Better Customer Service and Enhanced Shopping Experience
5.2.1.3 Rising Data Volume Around In-Store Operations
5.2.2 Restraints
5.2.2.1 Data Security and Privacy Concerns Over New Advanced Technologies
5.2.2.2 Lack of Skilled Personnel
5.2.3 Opportunities
5.2.3.1 Advent of Cloud-Based Analytics
5.2.3.2 High Growth Potential in Emerging Economies
5.2.4 Challenges
5.2.4.1 Reluctance of Retailers
5.3 Industry Trends
5.3.1 Use Cases
5.3.1.1 Use Case 1: Increasing Profits By Leveraging Store Inventories
5.3.1.2 Use Case 2: Understanding Customer Behavior to Enhance Revenue and Profitability
5.3.1.3 Use Case 3: Tracking Engagement Metrics and Monitoring Customer Behavior in Real Time
5.3.2 Impact of AI and ML on the In-Store Analytics Market
5.3.3 In-Store Analytics Process
6 In-Store Analytics Market By Component
6.1 Introduction
6.2 Software
6.2.1 Need for Leveraging Distinct Data to Enhance Customer Retention and Store Profitability
6.3 Services
6.3.1 Professional Services
6.3.1.1 Support and Maintenance Services
6.3.1.1.1 Complexity of Operations and the Need for Regular Assistance During the Software Lifecycle to Foster the Growth of Support and Maintenance Services
6.3.1.2 Consulting Services
6.3.1.2.1 Need for A Strategic Outlook Exploring New Avenues for Improving Business Performance to Drive the Growth of Consulting Services
6.3.2 Managed Services
6.3.2.1 Need for Monitoring and Maintaining Software Operations and Reducing Overhead Costs
7 In-Store Analytics Market By Application
7.1 Introduction
7.2 Customer Management
7.2.1 Customer Footfall Analysis
7.2.1.1 Monitoring and Measuring Footfalls to Identify Various Sales Opportunities
7.2.2 Customer Behavioral Analysis
7.2.2.1 Understanding Customer Behavior to Discover Pain Points Affecting Customer Behavior
7.2.3 Customer Service
7.2.3.1 Assisting Customers in Enhancing Customer Experience and Improving Customer Retention
7.3 Marketing Management
7.3.1 Campaign Management
7.3.1.1 Improving Customer Experience Through Customized Campaigns
7.3.2 Loyalty Management
7.3.2.1 Initiating Loyalty Programs to Target the Mass Market
7.3.3 Cross-Sell and Upsell and Point of Sale
7.3.3.1 Generating Additional Revenues and Increasing Customer Lifetime Value
7.3.4 Market Basket Analysis
7.3.4.1 Identifying Correlation Among Products to Provide Real-Time Recommendations
7.4 Merchandising Analysis
7.4.1 Space Planning and Optimization
7.4.1.1 Optimizing Spaces to Improve Operational Efficiency
7.4.2 Product Category Analysis
7.4.2.1 Categorizing Products of Similar Nature and Attributes
7.4.3 Store Layout Analysis
7.4.3.1 Optimizing Store Layout for Maximum Utilization of Floor Space
7.5 Store Operations Management
7.5.1 Workforce Optimization
7.5.1.1 Scheduling Tasks and Utilizing Workforce to Improve the Overall Efficiency
7.5.2 Top-Performing Categories and Product Identification
7.5.2.1 Predicting Customer Demands and Top Performing Categories to Drive Sales and Profitability
7.5.3 Inventory Management
7.5.3.1 Managing Inventory to Identify Non-Performing Products and Prevent Out-Of-Stock Situations
7.6 Risk and Compliance Management
7.6.1 Fraud Detection
7.6.1.1 Real-Time Recognition of Suspicious Activities to Safeguard Confidential Information
7.7 Others
8 In-Store Analytics Market By Deployment Model
8.1 Introduction
8.2 Cloud
8.2.1 Improved Flexibility and Scalability to Drive the Growth of Cloud-Based In-Store Analytics Software
8.3 On-Premises
8.3.1 Data Security and Privacy Requirements to Remain Factors Dominating On-Premises In-Store Analytics Solutions
9 In-Store Analytics Market By Organization Size
9.1 Introduction
9.2 Small and Medium-Sized Enterprises
9.2.1 Demand for Analytics Software With Low Operational Costs
9.3 Large Enterprises
9.3.1 Need for Leveraging Voluminous Data to Stay Competitive
10 In-Store Analytics Market By Region
11 Competitive Landscape
11.1 Microquadrant Overview
11.2 Competitive Benchmarking
11.3 Market Ranking
12 Company Profiles
12.1 Introduction
12.2 RetailNext
12.3 Mindtree
12.4 Thinkinside
12.5 Happiest Minds
12.6 SAP
12.7 Celect
12.8 Capillary Technologies
12.9 Inpixon
12.10 Scanalytics
12.11 Retail Solutions
12.12 Dor Technologies
12.13 SEMSEYE
12.14 InvenSense
12.15 Walkbase
12.16 Amoobi
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