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In-store Analytics Market by Application, Component, Deployment, Organization Size, and Region - Global Forecast to 2023

  • ID: 4761594
  • Report
  • Region: Global
  • 125 Pages
  • Markets and Markets
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Global In-Store Analytics Market to Grow from USD 1.1 Billion in 2018 to USD 3.2 Billion by 2023, at a CAGR of 23.5%

FEATURED COMPANIES

  • Amoobi
  • Celect
  • Happiest Minds
  • InvenSense
  • Retail Solutions
  • SAP
  • MORE

"In-store Analytics Market by Application (Marketing Management, Customer Management, Merchandising Analysis, Store Operations Management, and Risk and Compliance Management), Component, Deployment, Organization Size, and Region - Global Forecast to 2023"

"Need for leveraging distinct data to enhance customer retention and store profitability, to drive the adoption of in-store analytics across the retail industry"

The author estimates the global in-store analytics market to grow from USD 1.1 billion in 2018 to USD 3.2 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 23.5% during the forecast period. The in-store analytics market is growing rapidly with the increasing competition of brick-and-mortar retailers from eCommerce players, growing need for better customer service and enhanced shopping experience, and rising data volume around in-store operations. However, the reluctance of traditional retailers to adopt newer technologies would limit the growth of the market.

"Merchandising analysis segment is expected to grow at the highest CAGR during the forecast period"

Brick-and-mortar retailers have witnessed intense competition from various eCommerce websites, which has led to a decline in their growth. Merchandising analysis software provides analytical insights for building a localized strategy on the basis of strong and weaker-performing stores. It also explores incremental revenue opportunities with flexible ad-hoc analysis. The adoption of such applications helps improve the operational efficiency of the enterprise by meeting changing conditions for each selling season.

"In-store analytics market in Asia Pacific is projected to grow at the highest CAGR during the forecast period"

The high growth of the market in Asia Pacific (APAC) is attributed to the high growth potential, growing retail market, and increasing digitalization in the region with the rising need of businesses to remain globally competitive. Furthermore, the inclination of countries across the region toward emerging technologies such as Artificial Intelligence (AI) and advanced analytics, is also expected to fuel the growth of the in-store analytics market. However, the lack of technological awareness, privacy issues, and limited technical expertise in advanced technologies remains the biggest hurdle in the in-store analytics adoption across the region. The cloud-based in-store analytics software presents an optimal solution for these countries by minimizing integration complexities, and installation costs.

"Large enterprises to hold the largest market share during the forecast period in the in-store analytics market"

Organizations have been gradually recognizing the importance of in-store analytics software, and have started deploying them, as per their needs and available resources. The adoption of in-store analytics software and services among large enterprises is high due to the voluminous data generation due to the widespread customer base. Large retailers need to correlate voluminous data with customer behavioral information exhibited across the stores to gain meaningful insights and help support revenue generation.

In-depth interviews were conducted with the Chief Executive Officers (CEOs), Chief Technology Officers (CTOs), Chief Operating Officers (COOs), Vice Presidents (VPs), Managing Directors (MDs), technology and innovation directors, and related key executives from various key companies and organizations operating in the in-store analytics market.

  • By Company - Tier 1-10%, Tier 2-25%, and Tier 3-65%
  • By Designation - C-Level-25%, Director Level-50%, and Others-25%
  • By Region - North America-40%, Europe-30%, and APAC-20%, RoW - 10%

The in-store analytics market comprises major solution providers, such as RetailNext (US), SAP (Germany), Thinkinside (Italy), Mindtree (India), Happiest Minds (India), Celect (US), Capillary Technologies (Singapore), Scanalytics (US), Inpixon (US), Retail Solutions (US), Dor Technologies (US), SEMSEYE (Lithuania), InvenSense (US), Walkbase (Finland), and Amoobi (Belgium). The study includes an in-depth competitive analysis of these key players in the in-store analytics market with their company profiles, recent developments, and key market strategies.

Research Coverage

The in-store analytics market revenue is primarily classified into revenues from software and services. Software revenue is associated with software offerings while services’ revenue is associated with support and maintenance services and consulting services. The market is also segmented on the basis of application, deployment model, organization size, and region.

Key benefits of the report

The report would help the market leaders/new entrants in this market with the information on the closest approximations of the revenue numbers for the overall in-store analytics market and the subsegments. This report would help stakeholders understand the competitive landscape and gain insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on the key market drivers, restraints, challenges, and opportunities.

Note: Product cover images may vary from those shown
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FEATURED COMPANIES

  • Amoobi
  • Celect
  • Happiest Minds
  • InvenSense
  • Retail Solutions
  • SAP
  • MORE

1 Introduction
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
    1.4 Years Considered for the Study
    1.5 Currency Considered
    1.6 Stakeholders

2 Research Methodology
    2.1 Research Data
           2.1.1 Secondary Data
           2.1.2 Primary Data
                    2.1.2.1 Breakup of Primaries
                    2.1.2.2 Key Industry Insights
    2.2 Market Breakup and Data Triangulation
    2.3 Market Size Estimation
    2.4 Market Forecast
    2.5 Microquadrant Research Methodology
           2.5.1 Vendor Inclusion Criteria
    2.6 Research Assumptions
    2.7 Limitations

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
     10.1 Introduction
     10.2 North America
             10.2.1 United States
                        10.2.1.1 Notable Technology Spending and Presence of A Large Number of Retailers to Bolster the Growth of Market in the United States
             10.2.2 Canada
                        10.2.2.1 Demand for Comprehensive Marketing, Footfall Measurement, and Enhanced Customer Engagement to Propel the Market Growth
     10.3 Europe
             10.3.1 United Kingdom
                        10.3.1.1 Increasing Technology Adoption and Various Government Initiatives to Fuel the Growth of Market in the United Kingdom
             10.3.2 Germany
                        10.3.2.1 Need for Maintaining A Competitive Edge to Drive the Adoption of Advanced Technologies, Such as In-Store Analytics, in Germany
             10.3.3 France
                        10.3.3.1 Expansion of In-Store Analytics Vendors in France to Open New Avenues for In-Store Analytics
             10.3.4 Rest of Europe
     10.4 Asia Pacific
             10.4.1 China
                        10.4.1.1 Steady Income Growth and Growing Retail Market to Drive the Implementation of In-Store Analytics in China
             10.4.2 Japan
                        10.4.2.1 Expansion of the Retail Industry and Its Inclination Toward Emerging Technologies to Fuel the Growth of In-Store Analytics Market in Japan
             10.4.3 India
                        10.4.3.1 Partnerships of Brick and Mortar Retailers With Leading Analytics Solution Providers to Further Bolster the Adoption of In-Store Analytics in India
             10.4.4 Rest of Asia Pacific
     10.5 Middle East and Africa
             10.5.1 Middle East
                        10.5.1.1 Price Consciousness and High Purchasing Power of People to Fuel the Growth of Market Among Retailers in the Middle East
             10.5.2 Africa
                        10.5.2.1 Making Well-Informed Business Decisions to Increase Basket Size and Footfall Driving the Growth of Market in Africa
     10.6 Latin America
             10.6.1 Mexico
                        10.6.1.1 Need to Curb Decreasing Roi and Increase Profitability Fueling the Growth of Market in Mexico
             10.6.2 Brazil
                        10.6.2.1 Need for One-Step Pricing and Customer Engagement Solution to Propel the Growth of Market in Brazil
             10.6.3 Rest of Latin America

11 Competitive Landscape
     11.1 Microquadrant Overview
             11.1.1 Visionaries
             11.1.2 Innovators
             11.1.3 Dynamic Differentiators
             11.1.4 Emerging Companies
     11.2 Competitive Benchmarking
             11.2.1 Strength of Product Offerings of Major Players in the Market
             11.2.2 Business Strategy Excellence of Major Players in the In-Store Analytics Market
     11.3 Market Ranking

12 Company Profiles
(Business Overview, Products Offered, Recent Developments, SWOT Analysis & View)*
     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

*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis & View Might Not Be Captured in Case of Unlisted Companies.

List of Tables
Table 1 United States Dollar Exchange Rate, 2015-2017
Table 2 Factor Analysis
Table 3 Evaluation Criteria
Table 4 In-Store Analytics Market Size and Growth Rate, 2016-2023 (USD Million, Y-O-Y %)
Table 5 Market Size By Component, 2016-2023 (USD Million)
Table 6 Software: Market Size By Region, 2016-2023 (USD Million)
Table 7 Market Size By Service, 2016-2023 (USD Million)
Table 8 Services: Market Size By Region, 2016-2023 (USD Million)
Table 9 In-Store Analytics Market Size, By Professional Service, 2016-2023 (USD Million)
Table 10 Professional Services: Market Size By Region, 2016-2023 (USD Million)
Table 11 Support and Maintenance Services: Market Size By Region, 2016-2023 (USD Million)
Table 12 Consulting Services: Market Size By Region, 2016-2023 (USD Million)
Table 13 Managed Services: Market Size By Region, 2016-2023 (USD Million)
Table 14 In-Store Analytics Market Size, By Application, 2016-2023 (USD Million)
Table 15 Customer Management: Market Size By Region, 2016-2023 (USD Million)
Table 16 Marketing Management: Market Size By Region, 2016-2023 (USD Million)
Table 17 Merchandising Analysis: Market Size By Region, 2016-2023 (USD Million)
Table 18 Store Operations Management: Market Size By Region, 2016-2023 (USD Million)
Table 19 Risk and Compliance Management: Market Size By Region, 2016-2023 (USD Million)
Table 20 Others: Market Size By Region, 2016-2023 (USD Million)
Table 21 In-Store Analytics Market Size, By Deployment Model, 2016-2023 (USD Million)
Table 22 Cloud: Market Size By Region, 2016-2023 (USD Million)
Table 23 On-Premises: Market Size By Region, 2016-2023 (USD Million)
Table 24 Market Size By Organization Size, 2016-2023 (USD Million)
Table 25 Small and Medium-Sized Enterprises: Market Size By Region, 2016-2023 (USD Million)
Table 26 Large Enterprises: Market Size By Region, 2016-2023 (USD Million)
Table 27 In-Store Analytics Market Size, By Region, 2016-2023 (USD Million)
Table 28 North America: Market Size By Component, 2016-2023 (USD Million)
Table 29 North America: Market Size By Service, 2016-2023 (USD Million)
Table 30 North America: Market Size By Application, 2016-2023 (USD Million)
Table 31 North America: Market Size By Deployment Model, 2016-2023 (USD Million)
Table 32 North America: Market Size By Organization Size, 2016-2023 (USD Million)
Table 33 North America: Market Size By Country, 2016-2023 (USD Million)
Table 34 Europe: In-Store Analytics Market Size, By Component, 2016-2023 (USD Million)
Table 35 Europe: Market Size By Service, 2016-2023 (USD Million)
Table 36 Europe: Market Size By Application, 2016-2023 (USD Million)
Table 37 Europe: Market Size By Deployment Model, 2016-2023 (USD Million)
Table 38 Europe: Market Size By Organization Size, 2016-2023 (USD Million)
Table 39 Europe: Market Size By Country, 2016-2023 (USD Million)
Table 40 Asia Pacific: In-Store Analytics Market Size, By Component, 2016-2023 (USD Million)
Table 41 Asia Pacific: Market Size By Service, 2016-2023 (USD Million)
Table 42 Asia Pacific: Market Size By Application, 2016-2023 (USD Million)
Table 43 Asia Pacific: Market Size By Deployment Model, 2016-2023 (USD Million)
Table 44 Asia Pacific: Market Size By Organization Size, 2016-2023 (USD Million)
Table 45 Asia Pacific: Market Size By Country, 2016-2023 (USD Million)
Table 46 Middle East and Africa: In-Store Analytics Market Size, By Component, 2016-2023 (USD Million)
Table 47 Middle East and Africa: Market Size By Service, 2016-2023 (USD Million)
Table 48 Middle East and Africa: Market Size By Application, 2016-2023 (USD Million)
Table 49 Middle East and Africa: Market Size By Deployment Model, 2016-2023 (USD Million)
Table 50 Middle East and Africa: Market Size By Organization Size, 2016-2023 (USD Million)
Table 51 Middle East and Africa: Market Size By Sub Region, 2016-2023 (USD Million)
Table 52 Latin America: In-Store Analytics Market Size, By Component, 2016-2023 (USD Million)
Table 53 Latin America: Market Size By Service, 2016-2023 (USD Million)
Table 54 Latin America: Market Size By Application, 2016-2023 (USD Million)
Table 55 Latin America: Market Size By Deployment Model, 2016-2023 (USD Million)
Table 56 Latin America: Market Size By Organization Size, 2016-2023 (USD Million)
Table 57 Latin America: Market Size By Country, 2016-2023 (USD Million)

List of Figures
Figure 1 Market Segmentation
Figure 2 Regions Covered
Figure 3 Global In-Store Analytics Market: Research Design
Figure 4 Market Estimation and Forecast Methodology
Figure 5 In-Store Analytics Market Overview
Figure 6 Market to Witness High Growth During the Forecast Period
Figure 7 Market By Component (2018 vs 2023)
Figure 8 Market By Deployment Model (2018-2023)
Figure 9 Increasing Need to Analyze Consumer Data in Real-Time for Making Informed Decisions to Drive the In-Store Analytics Market Growth
Figure 10 Merchandising Analysis Segment to Grow at the Highest CAGR During the Forecast Period
Figure 11 Large Enterprises Segment to Hold A Higher Market Share During the Forecast Period
Figure 12 North America to Account for the Highest Market Share in 2018
Figure 13 Drivers, Restraints, Opportunities, and Challenges: In-Store Analytics Market
Figure 14 In-Store Analytics Process
Figure 15 Services Segment to Grow at A Higher CAGR During the Forecast Period
Figure 16 Managed Services Segment to Grow at A Higher CAGR During the Forecast Period
Figure 17 Consulting Services Segment to Grow at A Higher CAGR During the Forecast Period
Figure 18 Merchandising Analysis Segment to Grow at the Highest CAGR During the Forecast Period
Figure 19 On-Premises Segment to Grow at A Higher CAGR During the Forecast Period
Figure 20 Small and Medium-Sized Enterprises Segment to Grow at A Higher CAGR During the Forecast Period
Figure 21 Asia Pacific to Grow at the Highest CAGR During the Forecast Period
Figure 22 North America: Market Snapshot
Figure 23 Asia Pacific: Market Snapshot
Figure 24 In-Store Analytics, Competitive Leadership Mapping, 2018
Figure 25 Ranking of Key Players in the In-Store Analytics Market, 2018
Figure 26 RetailNext: SWOT Analysis
Figure 27 Mindtree: Company Snapshot
Figure 28 Mindtree: SWOT Analysis
Figure 29 Thinkinside: SWOT Analysis
Figure 30 Happiest Minds: SWOT Analysis
Figure 31 SAP: Company Snapshot
Figure 32 SAP: SWOT Analysis
Figure 33 Inpixon: Company Snapshot

Note: Product cover images may vary from those shown
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  • Amoobi
  • Capillary Technologies
  • Celect
  • Dor Technologies
  • Happiest Minds
  • Inpixon
  • InvenSense
  • Mindtree
  • Retail Solutions
  • RetailNext
  • SAP
  • Scanalytics
  • SEMSEYE
  • Thinkinside
  • Walkbase
Note: Product cover images may vary from those shown
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Note: Product cover images may vary from those shown
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