Retail Analytics Market Size (2023 to 2033)

Newly-released Retail Analytics Market industry analysis report by Future Market Insights shows that global sales of Retail Analytics Market in 2022 were held at US$ 9,300 million. With 17.5%, the projected market growth during 2023 to 2033 is expected to be higher than the historical growth. In 2023, the market is estimated to surpass a valuation of US$ 10,797.4 million in 2023, and reach US$ 55,247.6 million by 2033.

Attribute Details
Global Retail Analytics Market Size (2023) US$ 10,797.4 million
Global Retail Analytics Market Size (2033) US$ 55,247.6 million
Global Retail Analytics Market CAGR (2023 to 2033) 17.5%
United States Retail Analytics Market Size (2033) US$ 16.8 billion
United States Retail Analytics Market CAGR (2023 to 2033) 17.6%
Key Companies Covered
  • Microsoft
  • IBM
  • Oracle
  • Salesforce
  • SAP
  • AWS
  • SAS Institute
  • Qlik
  • Manthan
  • Bridgei2i
  • MicroStrategy
  • Teradata
  • HCL
  • Fujitsu
  • Domo
  • Google
  • FLIR Systems
  • Information Builders
  • 1010Data

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Revenue of Retail Analytics Market from 2018 to 2022 Compared to Demand Outlook for 2023 to 2033

As per the Retail Analytics Market industry research by Future Market Insights - a market research and competitive intelligence provider, historically, from 2018 to 2022, the market value of the Retail Analytics Market increased at around 15.6% CAGR, wherein, countries such as the United States, United Kingdom, China, Japan, and South Korea held a significant share in the global market. With an absolute dollar opportunity of US$ 37.7 billion during 2023 to 2033, the market is projected to reach a valuation of US$ 47 billion by 2033.

Retail analytics is the most common way of tracking business data, for example, stock levels, buyer conduct, and marketing projections. This incorporates giving experiences to comprehend and streamline the retail business' inventory network, buyer conduct, deal patterns, functional cycles, and general execution. With the present high client expectations for retail, organizations should meet those rising necessities with customized omnichannel offers, effective cycles, and speedy changes to upcoming patterns - all of which require retail analytics.

Retailers should have the option to precisely target and expect client needs to offer the perfect items at the ideal cost brilliantly which needs analytics. Analytics can assist retailers with pursuing the right marketing choices, further develop their business processes, and convey better overall client experiences by uncovering regions for development and advancement. There are some areas of the retail business that can gain profit from analytics. It tends to be utilized to give an exhaustive perspective on the business and evaluate the effectiveness of business processes. For instance, a retailer can utilize prescient investigation to change stock in light of client buying patterns and diminish squandering and related costs.

Retail analytics can further develop advertising strategies. It can assist with focusing on clients by deciding the ideal client in view of data accumulated on current and past clients' area, age, inclinations, buying designs, and other key elements. Customized promotion in the retail business is turning out to be more ordinary and requires a profound comprehension of individual client inclinations. With retail investigation, organizations can foster methodologies zeroed in on unambiguous clients. Retail analytics can be utilized to foresee purchaser necessities and business upgrades to acquire an upper hand. Examining deals data can assist retailers with distinguishing arising patterns and client needs.

Price Optimization Strategy is boosting the growth of Retail Analytics Market. Check How?

The rising need for price optimization strategy is driving the development of the retail analytics market. Clients today are shrewd, knowing how to get the most value for the money. They think about costs online while shopping in stores, have applications that give markdown codes, and are dedicated to retailers who offer the most benefit for their cash. Thus, a sound and rising main concern require areas of strength for an enhancement approach.

In the retail business, evaluating analytics permits organizations to set ideal valuing for specific items, seasons, and stores by breaking down missed deals, stock turn, selling patterns, and different elements. Estimating investigation likewise affects stock, permitting them to more readily deal with their stock in view of stock, request, and occasional varieties.

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Retail Analytics Market Restraints

The retail sector is finding it difficult to get back into business after being in a complete lockdown for months. Like other client-driven sectors, retail also flourishes with client conduct and commitment, and is battling to stay aware of lockdown-prompted changes in client conduct. Alongside falling deals, retail is confronting an information shortage. This information is typically the way to guarantee an improved client experience.

With the evaporating of such critical data in light of deals, the retail area has lost admittance to pertinent bits of knowledge to support client dependability plans, AI-driven items, and administration suggestions. It has additionally impacted systems for promoting and business choices. A wide range of retail associations has been impacted by this absence of information, whether free or chain, blocks, concrete or internet business or start-up or laid out substances.

The global retail and customer merchandise has been adjusting beyond anyone's expectation. Undertakings and clients have begun understanding that computerized change is tied in with adopting an information-driven strategy for each part of their business to make an upper hand. For instance, for a retailer, computerized change may be tied in with giving continuous best proposals while clients are in actual stores or enhancing stock to give a superior on the web and in-store insight.

Advanced change in retail can help client maintenance and fulfillment by offering clients the administrations and items they need. The fourth modern transformation (Industry 4.0) is characterized by arising advances that obscure lines between the computerized and actual universes. Joined with strong investigation instruments, including situation examination, prescient learning calculations and representation, admittance to information is changing the way that organizations perform.

Organizations can now gather tremendous informational indexes from actual offices and resources continuously, execute progressed examinations to produce new experiences, and pursue more successful choices. The computerized upset is changing how items are planned, created, and conveyed to clients. It offers sgnificant ramifications for the retail esteem chain.

Which Region is projected to offer the most promising opportunity for the Retail Analytics Market?

North America is expected to continue its dominance in the market with a projected CAGR of 17.6%. The retail analytics market has been witnessing an expansion in the number of next-generation purchasers, as well as an ascent in the utilization of social and versatile stages for purchasing. Due to these contemplations, shippers are using an abundance of psychographic information and investigation innovations to gather granular information and dig further into buyer requirements and inclinations. Retailers settle on shrewd promoting choices in view of information obtained through different web-based entertainment advancements, for example, offers and informing, that straightforwardly appeal to clients.

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Retail Analytics Market Country-wise Analysis

Which country lies at the center stage of the Retail Analytics Market?

United States held the largest share of the global market and is expected to reach a valuation of US$ 16.8 billion by the end of the forecast period. Conventional improvement options for physical store expansions have been rendered inactive with the boom in the internet. The way merchandising analytics is dealt with has changed because of online stages, provincial combinations, and overall market development.

Retailers entered the market because of furious competition from online platforms, which gave a clearer picture of combination, valuing, advancements, obtaining, renewal, and in-store arranging and execution. This has thusly expanded the development of the retail analytics market in the country.

Category-wise Insights

Which segment is expected to grow the fastest in the Retail Analytics Market?

Market revenue through Retail Analytics Software hold the highest revenue share and is predicted to increase at a CAGR of 17.4% during the forecast period. The capacity of the software to give detailed analytical information on key performance indicators of the business is expected to drive the market in the future years. Furthermore, the Software segment is reliably engaged in experimentation and development which works with the consolidation of new advancements that tackle issues related to retail business effectively. Such factors are expected to drive segment growth during the forecast period

Retail Analytics Market Competitive Analysis

The Retail Analytics industry is fiercely competitive, and top competitors are continually implementing new strategies to obtain market domination. Key players of the industry are Microsoft, IBM, Oracle, Salesforce, SAP, AWS, SAS Institute, Qlik, Manthan, Bridgei2i, MicroStrategy, Teradata, HCL, Fujitsu, Domo, Google, FLIR Systems, Information Builders, and 1010Data.

Some of the recent developments of key players in the Retail Analytics Market are as follows:

  • In March 2021, Trax Ltd. and Roamler partnered to supply consumer packaged goods firms with store auditing services. It aids in increasing product availability on store shelves and allows businesses to access real-time data and make decisions to improve shopper experiences.
  • In June 2020, Microsoft and SAS Institute established a broad strategic relationship in technology and go-to-market. Both firms will transition SAS Institute's analytical products and industry solutions to Microsoft Azure as the chosen cloud provider for SAS Cloud as part of the partnership. Microsoft has teamed up with SAS Institute to bring SAS industry solutions to its customers via the cloud.
  • In Feb 2020, MicroStrategy and Yellowbrick Data, an enterprise data warehouse vendor announced a partnership that would see a Yellowbrick Data warehouse integrated with the Microsoft 2020 analytics platform. The objective of this partnership is to make searches faster and deliver better data insights.
  • January 2023 saw the announcement of a global strategic agreement between Tech Mahindra, a global provider of digital transformation, consulting, and organisational re-engineering solutions and services, and Retalon, a pioneer in the retailing of AI and predictive analytics alternatives. The partnership will enable Retail and CPG businesses to gain deeper consumer insights, improve decision-making, and boost operational effectiveness.
  • In order to support Kroger's commitment to being fresh and in-stock both online and in-store, Retail Insight, a leading provider of store-focused retail analytics techniques, expanded its partnership with Kroger, one of America's leading grocery retail chains with over 465,000 associates and 2,700 stores, in June 2022.

Similarly, recent developments related to companies offering Retail Analytics Market have been tracked by the team at Future Market Insights, which are available in the full report.

Market Segments Covered in Retail Analytics Software Industry Analysis

By Solution:

  • Software
  • Service
    • Training & Consulting
    • Integration and Deployment
    • Managed Services

By Function:

  • Customer Management
  • Merchandising
  • Store Operations
  • Supply Chain
  • Strategy & Planning

By Enterprise Size:

  • SMEs
  • Large Enterprises

By Deployment Model:

  • On-Premise
  • Cloud

By Field Crowdsourcing:

  • On-shelf availability
  • Documentation & Reporting
  • Promotion Campaign Management
  • Customer Insights

By Region:

  • North America
    • United States
    • Canada
  • Europe
    • Germany
    • Spain
    • United Kingdom
    • Italy
    • France
    • BENELUX
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • South Korea
    • Rest of Asia Pacific
  • Latin America
    • Brazil
    • Mexico
    • Argentina
    • Rest of Latin America
  • MEA
    • South Africa
    • Saudi Arabia
    • Rest of MEA

Frequently Asked Questions

What is the Retail Analytics market CAGR for 2033?

The retail analytics market CAGR for 2033 is 17.5%.

How Big Will the Retail Analytics Market by 2033?

The market is estimated to reach US$ 55,247.6 billion by 2033.

Who are the Key Retail Analytics Market Players?

Microsoft, IBM, and Oracle are key market players.

What is the Current Market Valuation of the Retail Analytics Market?

The market is estimated to secure a valuation of US$ 10,797.4 billion in 2023.

Which Region Holds a Significant Share of the Retail Analytics Market?

North America holds a significant share of the market.

Table of Content

1. Executive Summary

    1.1. Global Market Outlook

    1.2. Demand-side Trends

    1.3. Supply-side Trends

    1.4. Technology Roadmap Analysis

    1.5. Analysis and Recommendations

2. Market Overview

    2.1. Market Coverage / Taxonomy

    2.2. Market Definition / Scope / Limitations

3. Market Background

    3.1. Market Dynamics

        3.1.1. Drivers

        3.1.2. Restraints

        3.1.3. Opportunity

        3.1.4. Trends

    3.2. Scenario Forecast

        3.2.1. Demand in Optimistic Scenario

        3.2.2. Demand in Likely Scenario

        3.2.3. Demand in Conservative Scenario

    3.3. Opportunity Map Analysis

    3.4. Investment Feasibility Matrix

    3.5. PESTLE and Porter’s Analysis

    3.6. Regulatory Landscape

        3.6.1. By Key Regions

        3.6.2. By Key Countries

    3.7. Regional Parent Market Outlook

4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033

    4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022

    4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033

        4.2.1. Y-o-Y Growth Trend Analysis

        4.2.2. Absolute $ Opportunity Analysis

5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Solution

    5.1. Introduction / Key Findings

    5.2. Historical Market Size Value (US$ Million) Analysis By Solution, 2018 to 2022

    5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Solution, 2023 to 2033

        5.3.1. Software

        5.3.2. Service

            5.3.2.1. Training & Consulting

            5.3.2.2. Integration and Deployment

            5.3.2.3. Managed Services

    5.4. Y-o-Y Growth Trend Analysis By Solution, 2018 to 2022

    5.5. Absolute $ Opportunity Analysis By Solution, 2023 to 2033

6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Function

    6.1. Introduction / Key Findings

    6.2. Historical Market Size Value (US$ Million) Analysis By Function, 2018 to 2022

    6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Function, 2023 to 2033

        6.3.1. Customer Management

        6.3.2. Merchandising

        6.3.3. Store Operations

        6.3.4. Supply Chain

        6.3.5. Strategy & Planning

    6.4. Y-o-Y Growth Trend Analysis By Function, 2018 to 2022

    6.5. Absolute $ Opportunity Analysis By Function, 2023 to 2033

7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Enterprise Size

    7.1. Introduction / Key Findings

    7.2. Historical Market Size Value (US$ Million) Analysis by Enterprise Size, 2018 to 2022

    7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast by Enterprise Size, 2023 to 2033

        7.3.1. SMEs

        7.3.2. Large Enterprises

    7.4. Y-o-Y Growth Trend Analysis by Enterprise Size, 2018 to 2022

    7.5. Absolute $ Opportunity Analysis by Enterprise Size, 2023 to 2033

8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment Model

    8.1. Introduction / Key Findings

    8.2. Historical Market Size Value (US$ Million) Analysis By Deployment Model, 2018 to 2022

    8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Model, 2023 to 2033

        8.3.1. On-Premise

        8.3.2. Cloud

    8.4. Y-o-Y Growth Trend Analysis By Deployment Model, 2018 to 2022

    8.5. Absolute $ Opportunity Analysis By Deployment Model, 2023 to 2033

9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Field Crowdsourcing

    9.1. Introduction / Key Findings

    9.2. Historical Market Size Value (US$ Million) Analysis By Field Crowdsourcing, 2018 to 2022

    9.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Field Crowdsourcing, 2023 to 2033

        9.3.1. On-shelf availability

        9.3.2. Documentation & Reporting

        9.3.3. Promotion Campaign Management

        9.3.4. Customer Insights

    9.4. Y-o-Y Growth Trend Analysis By Field Crowdsourcing, 2018 to 2022

    9.5. Absolute $ Opportunity Analysis By Field Crowdsourcing, 2023 to 2033

10. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region

    10.1. Introduction

    10.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022

    10.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033

        10.3.1. North America

        10.3.2. Latin America

        10.3.3. Western Europe

        10.3.4. Eastern Europe

        10.3.5. South Asia and Pacific

        10.3.6. East Asia

        10.3.7. Middle East and Africa

    10.4. Market Attractiveness Analysis By Region

11. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        11.2.1. By Country

            11.2.1.1. The USA

            11.2.1.2. Canada

        11.2.2. By Solution

        11.2.3. By Function

        11.2.4. By Enterprise Size

        11.2.5. By Deployment Model

        11.2.6. By Field Crowdsourcing

    11.3. Market Attractiveness Analysis

        11.3.1. By Country

        11.3.2. By Solution

        11.3.3. By Function

        11.3.4. By Enterprise Size

        11.3.5. By Deployment Model

        11.3.6. By Field Crowdsourcing

    11.4. Key Takeaways

12. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        12.2.1. By Country

            12.2.1.1. Brazil

            12.2.1.2. Mexico

            12.2.1.3. Rest of Latin America

        12.2.2. By Solution

        12.2.3. By Function

        12.2.4. By Enterprise Size

        12.2.5. By Deployment Model

        12.2.6. By Field Crowdsourcing

    12.3. Market Attractiveness Analysis

        12.3.1. By Country

        12.3.2. By Solution

        12.3.3. By Function

        12.3.4. By Enterprise Size

        12.3.5. By Deployment Model

        12.3.6. By Field Crowdsourcing

    12.4. Key Takeaways

13. Western Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        13.2.1. By Country

            13.2.1.1. Germany

            13.2.1.2. United Kingdom

            13.2.1.3. France

            13.2.1.4. Spain

            13.2.1.5. Italy

            13.2.1.6. Rest of Western Europe

        13.2.2. By Solution

        13.2.3. By Function

        13.2.4. By Enterprise Size

        13.2.5. By Deployment Model

        13.2.6. By Field Crowdsourcing

    13.3. Market Attractiveness Analysis

        13.3.1. By Country

        13.3.2. By Solution

        13.3.3. By Function

        13.3.4. By Enterprise Size

        13.3.5. By Deployment Model

        13.3.6. By Field Crowdsourcing

    13.4. Key Takeaways

14. Eastern Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        14.2.1. By Country

            14.2.1.1. Poland

            14.2.1.2. Russia

            14.2.1.3. Czech Republic

            14.2.1.4. Romania

            14.2.1.5. Rest of Eastern Europe

        14.2.2. By Solution

        14.2.3. By Function

        14.2.4. By Enterprise Size

        14.2.5. By Deployment Model

        14.2.6. By Field Crowdsourcing

    14.3. Market Attractiveness Analysis

        14.3.1. By Country

        14.3.2. By Solution

        14.3.3. By Function

        14.3.4. By Enterprise Size

        14.3.5. By Deployment Model

        14.3.6. By Field Crowdsourcing

    14.4. Key Takeaways

15. South Asia and Pacific Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        15.2.1. By Country

            15.2.1.1. India

            15.2.1.2. Bangladesh

            15.2.1.3. Australia

            15.2.1.4. New Zealand

            15.2.1.5. Rest of South Asia and Pacific

        15.2.2. By Solution

        15.2.3. By Function

        15.2.4. By Enterprise Size

        15.2.5. By Deployment Model

        15.2.6. By Field Crowdsourcing

    15.3. Market Attractiveness Analysis

        15.3.1. By Country

        15.3.2. By Solution

        15.3.3. By Function

        15.3.4. By Enterprise Size

        15.3.5. By Deployment Model

        15.3.6. By Field Crowdsourcing

    15.4. Key Takeaways

16. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        16.2.1. By Country

            16.2.1.1. China

            16.2.1.2. Japan

            16.2.1.3. South Korea

        16.2.2. By Solution

        16.2.3. By Function

        16.2.4. By Enterprise Size

        16.2.5. By Deployment Model

        16.2.6. By Field Crowdsourcing

    16.3. Market Attractiveness Analysis

        16.3.1. By Country

        16.3.2. By Solution

        16.3.3. By Function

        16.3.4. By Enterprise Size

        16.3.5. By Deployment Model

        16.3.6. By Field Crowdsourcing

    16.4. Key Takeaways

17. Middle East and Africa Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    17.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    17.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        17.2.1. By Country

            17.2.1.1. GCC Countries

            17.2.1.2. South Africa

            17.2.1.3. Israel

            17.2.1.4. Rest of MEA

        17.2.2. By Solution

        17.2.3. By Function

        17.2.4. By Enterprise Size

        17.2.5. By Deployment Model

        17.2.6. By Field Crowdsourcing

    17.3. Market Attractiveness Analysis

        17.3.1. By Country

        17.3.2. By Solution

        17.3.3. By Function

        17.3.4. By Enterprise Size

        17.3.5. By Deployment Model

        17.3.6. By Field Crowdsourcing

    17.4. Key Takeaways

18. Key Countries Market Analysis

    18.1. USA

        18.1.1. Pricing Analysis

        18.1.2. Market Share Analysis, 2022

            18.1.2.1. By Solution

            18.1.2.2. By Function

            18.1.2.3. By Enterprise Size

            18.1.2.4. By Deployment Model

            18.1.2.5. By Field Crowdsourcing

    18.2. Canada

        18.2.1. Pricing Analysis

        18.2.2. Market Share Analysis, 2022

            18.2.2.1. By Solution

            18.2.2.2. By Function

            18.2.2.3. By Enterprise Size

            18.2.2.4. By Deployment Model

            18.2.2.5. By Field Crowdsourcing

    18.3. Brazil

        18.3.1. Pricing Analysis

        18.3.2. Market Share Analysis, 2022

            18.3.2.1. By Solution

            18.3.2.2. By Function

            18.3.2.3. By Enterprise Size

            18.3.2.4. By Deployment Model

            18.3.2.5. By Field Crowdsourcing

    18.4. Mexico

        18.4.1. Pricing Analysis

        18.4.2. Market Share Analysis, 2022

            18.4.2.1. By Solution

            18.4.2.2. By Function

            18.4.2.3. By Enterprise Size

            18.4.2.4. By Deployment Model

            18.4.2.5. By Field Crowdsourcing

    18.5. Germany

        18.5.1. Pricing Analysis

        18.5.2. Market Share Analysis, 2022

            18.5.2.1. By Solution

            18.5.2.2. By Function

            18.5.2.3. By Enterprise Size

            18.5.2.4. By Deployment Model

            18.5.2.5. By Field Crowdsourcing

    18.6. United Kingdom

        18.6.1. Pricing Analysis

        18.6.2. Market Share Analysis, 2022

            18.6.2.1. By Solution

            18.6.2.2. By Function

            18.6.2.3. By Enterprise Size

            18.6.2.4. By Deployment Model

            18.6.2.5. By Field Crowdsourcing

    18.7. France

        18.7.1. Pricing Analysis

        18.7.2. Market Share Analysis, 2022

            18.7.2.1. By Solution

            18.7.2.2. By Function

            18.7.2.3. By Enterprise Size

            18.7.2.4. By Deployment Model

            18.7.2.5. By Field Crowdsourcing

    18.8. Spain

        18.8.1. Pricing Analysis

        18.8.2. Market Share Analysis, 2022

            18.8.2.1. By Solution

            18.8.2.2. By Function

            18.8.2.3. By Enterprise Size

            18.8.2.4. By Deployment Model

            18.8.2.5. By Field Crowdsourcing

    18.9. Italy

        18.9.1. Pricing Analysis

        18.9.2. Market Share Analysis, 2022

            18.9.2.1. By Solution

            18.9.2.2. By Function

            18.9.2.3. By Enterprise Size

            18.9.2.4. By Deployment Model

            18.9.2.5. By Field Crowdsourcing

    18.10. Poland

        18.10.1. Pricing Analysis

        18.10.2. Market Share Analysis, 2022

            18.10.2.1. By Solution

            18.10.2.2. By Function

            18.10.2.3. By Enterprise Size

            18.10.2.4. By Deployment Model

            18.10.2.5. By Field Crowdsourcing

    18.11. Russia

        18.11.1. Pricing Analysis

        18.11.2. Market Share Analysis, 2022

            18.11.2.1. By Solution

            18.11.2.2. By Function

            18.11.2.3. By Enterprise Size

            18.11.2.4. By Deployment Model

            18.11.2.5. By Field Crowdsourcing

    18.12. Czech Republic

        18.12.1. Pricing Analysis

        18.12.2. Market Share Analysis, 2022

            18.12.2.1. By Solution

            18.12.2.2. By Function

            18.12.2.3. By Enterprise Size

            18.12.2.4. By Deployment Model

            18.12.2.5. By Field Crowdsourcing

    18.13. Romania

        18.13.1. Pricing Analysis

        18.13.2. Market Share Analysis, 2022

            18.13.2.1. By Solution

            18.13.2.2. By Function

            18.13.2.3. By Enterprise Size

            18.13.2.4. By Deployment Model

            18.13.2.5. By Field Crowdsourcing

    18.14. India

        18.14.1. Pricing Analysis

        18.14.2. Market Share Analysis, 2022

            18.14.2.1. By Solution

            18.14.2.2. By Function

            18.14.2.3. By Enterprise Size

            18.14.2.4. By Deployment Model

            18.14.2.5. By Field Crowdsourcing

    18.15. Bangladesh

        18.15.1. Pricing Analysis

        18.15.2. Market Share Analysis, 2022

            18.15.2.1. By Solution

            18.15.2.2. By Function

            18.15.2.3. By Enterprise Size

            18.15.2.4. By Deployment Model

            18.15.2.5. By Field Crowdsourcing

    18.16. Australia

        18.16.1. Pricing Analysis

        18.16.2. Market Share Analysis, 2022

            18.16.2.1. By Solution

            18.16.2.2. By Function

            18.16.2.3. By Enterprise Size

            18.16.2.4. By Deployment Model

            18.16.2.5. By Field Crowdsourcing

    18.17. New Zealand

        18.17.1. Pricing Analysis

        18.17.2. Market Share Analysis, 2022

            18.17.2.1. By Solution

            18.17.2.2. By Function

            18.17.2.3. By Enterprise Size

            18.17.2.4. By Deployment Model

            18.17.2.5. By Field Crowdsourcing

    18.18. China

        18.18.1. Pricing Analysis

        18.18.2. Market Share Analysis, 2022

            18.18.2.1. By Solution

            18.18.2.2. By Function

            18.18.2.3. By Enterprise Size

            18.18.2.4. By Deployment Model

            18.18.2.5. By Field Crowdsourcing

    18.19. Japan

        18.19.1. Pricing Analysis

        18.19.2. Market Share Analysis, 2022

            18.19.2.1. By Solution

            18.19.2.2. By Function

            18.19.2.3. By Enterprise Size

            18.19.2.4. By Deployment Model

            18.19.2.5. By Field Crowdsourcing

    18.20. South Korea

        18.20.1. Pricing Analysis

        18.20.2. Market Share Analysis, 2022

            18.20.2.1. By Solution

            18.20.2.2. By Function

            18.20.2.3. By Enterprise Size

            18.20.2.4. By Deployment Model

            18.20.2.5. By Field Crowdsourcing

    18.21. GCC Countries

        18.21.1. Pricing Analysis

        18.21.2. Market Share Analysis, 2022

            18.21.2.1. By Solution

            18.21.2.2. By Function

            18.21.2.3. By Enterprise Size

            18.21.2.4. By Deployment Model

            18.21.2.5. By Field Crowdsourcing

    18.22. South Africa

        18.22.1. Pricing Analysis

        18.22.2. Market Share Analysis, 2022

            18.22.2.1. By Solution

            18.22.2.2. By Function

            18.22.2.3. By Enterprise Size

            18.22.2.4. By Deployment Model

            18.22.2.5. By Field Crowdsourcing

    18.23. Israel

        18.23.1. Pricing Analysis

        18.23.2. Market Share Analysis, 2022

            18.23.2.1. By Solution

            18.23.2.2. By Function

            18.23.2.3. By Enterprise Size

            18.23.2.4. By Deployment Model

            18.23.2.5. By Field Crowdsourcing

19. Market Structure Analysis

    19.1. Competition Dashboard

    19.2. Competition Benchmarking

    19.3. Market Share Analysis of Top Players

        19.3.1. By Regional

        19.3.2. By Solution

        19.3.3. By Function

        19.3.4. By Enterprise Size

        19.3.5. By Deployment Model

        19.3.6. By Field Crowdsourcing

20. Competition Analysis

    20.1. Competition Deep Dive

        20.1.1. Microsoft

            20.1.1.1. Overview

            20.1.1.2. Product Portfolio

            20.1.1.3. Profitability by Market Segments

            20.1.1.4. Sales Footprint

            20.1.1.5. Strategy Overview

                20.1.1.5.1. Marketing Strategy

        20.1.2. IBM

            20.1.2.1. Overview

            20.1.2.2. Product Portfolio

            20.1.2.3. Profitability by Market Segments

            20.1.2.4. Sales Footprint

            20.1.2.5. Strategy Overview

                20.1.2.5.1. Marketing Strategy

        20.1.3. Oracle

            20.1.3.1. Overview

            20.1.3.2. Product Portfolio

            20.1.3.3. Profitability by Market Segments

            20.1.3.4. Sales Footprint

            20.1.3.5. Strategy Overview

                20.1.3.5.1. Marketing Strategy

        20.1.4. Salesforce

            20.1.4.1. Overview

            20.1.4.2. Product Portfolio

            20.1.4.3. Profitability by Market Segments

            20.1.4.4. Sales Footprint

            20.1.4.5. Strategy Overview

                20.1.4.5.1. Marketing Strategy

        20.1.5. SAP

            20.1.5.1. Overview

            20.1.5.2. Product Portfolio

            20.1.5.3. Profitability by Market Segments

            20.1.5.4. Sales Footprint

            20.1.5.5. Strategy Overview

                20.1.5.5.1. Marketing Strategy

        20.1.6. AWS

            20.1.6.1. Overview

            20.1.6.2. Product Portfolio

            20.1.6.3. Profitability by Market Segments

            20.1.6.4. Sales Footprint

            20.1.6.5. Strategy Overview

                20.1.6.5.1. Marketing Strategy

        20.1.7. SAS Institute

            20.1.7.1. Overview

            20.1.7.2. Product Portfolio

            20.1.7.3. Profitability by Market Segments

            20.1.7.4. Sales Footprint

            20.1.7.5. Strategy Overview

                20.1.7.5.1. Marketing Strategy

        20.1.8. Qlik

            20.1.8.1. Overview

            20.1.8.2. Product Portfolio

            20.1.8.3. Profitability by Market Segments

            20.1.8.4. Sales Footprint

            20.1.8.5. Strategy Overview

                20.1.8.5.1. Marketing Strategy

        20.1.9. Manthan

            20.1.9.1. Overview

            20.1.9.2. Product Portfolio

            20.1.9.3. Profitability by Market Segments

            20.1.9.4. Sales Footprint

            20.1.9.5. Strategy Overview

                20.1.9.5.1. Marketing Strategy

        20.1.10. Bridgei2i

            20.1.10.1. Overview

            20.1.10.2. Product Portfolio

            20.1.10.3. Profitability by Market Segments

            20.1.10.4. Sales Footprint

            20.1.10.5. Strategy Overview

                20.1.10.5.1. Marketing Strategy

21. Assumptions & Acronyms Used

22. Research Methodology

Recommendations

Technology

Retail Automation Market

March 2021

REP-GB-5017

July 2023

306 pages

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