Global AI Enabled E-Commerce Solutions Market

Report ID : 1198 | Published : 2022-03-25 | Pages: | Format:

The global AI-Enabled E-Commerce Solutions market size was accounted at USD 3.71 Bn in 2021; It is projected to grow at a compound annual growth rate (CAGR) of 15.7 % from 2022 to 2030.  In the recent years, Machine learning and artificial intelligence technologies are creating complex software development processes easy. Machine learning technology allows software applications to function more accurately in terms of predictive analysis. The recent Covid-19 outbreak has significantly impacted the AI-enabled E-Commerce solutions market as it has created the need for warehouse automation and management. Understanding customers' needs based on shopping history, product searches, and demographic details makes the market more competitive. The AI-based platform enables the seller to optimize their sales target by reaching the right customer with fundamental analysis based on gathered information. E-commerce AI is changing the online shopping field through the features like image search, customer-centric search, retargeting potential customers, virtual buying assistants, and extensive data analysis. AI applications analyze customer data to estimate future shopping trends and make product recommendations based on browsing patterns, ultimately driving the market growth.

Multiple factors that drive the AI-enabled E-Commerce solutions market are rising adoption of advanced technologies, manual error reductions in development processes due to the use of machine learning-based applications, cost-effective procedures, fast implementation of cloud-based platforms, and easy access to real-time data, various government initiatives for the R&D, and increasing awareness regarding advanced technologies. In addition, instant customer services related to product delivery, return, and complaints can be quickly resolved through artificial intelligence-enabled chat boxes. However, factors like the high cost of AI Solutions, shortage of skilled professionals, and complex and time-consuming procedures may downscale the AI-enabled E-Commerce solutions market's growth over the forecast period 2019-2030.

Segmentation of AI-enabled E-Commerce solutions market includes Technology, Applications, Deployment, and Region. The Technology segment comprises Deep Learning, Machine Learning, and NLP. Deep learning is a widely used technology in the market due to its benefits and useful features. In terms of Applications, the market is segmented into Customer Relationship Management, Supply Chain Analysis, Fake Review Analysis, Warehouse Automation, Merchandizing, Product Recommendation, and Customer Service. The Warehouse Automation segment is further bifurcated into Sorting and Placing and Inventory Storage. The Merchandizing segment is divided into Facets and Filter Selection and Multi Device Interaction. The Customer Service segment is subdivided into Chatbots. Out of these applications, customer relationship management, customer service, and product recommendation are the majorly used features. By Deployment, the market is divided into On-Premises and Cloud. Cloud Service has dominated this market. At regional level, the AI-enabled E-Commerce solutions market can be segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa. North America is anticipated to be the major market shareholder of this market over the forecast period, followed by Europe, Asia-Pacific, Latin America, and Rest-of-the-World.

Some of the key players of AI enabled E-Commerce solutions market are Riskified, Reflektion, Inc., Shelf.ai, Osaro, Sift, AntVoice SAS, Appier Inc, Eversight, Inc., Granify Inc., LivePerson, Inc., Manthan Software Services Pvt. Ltd., PayPal, Inc., Sidecar Interactive, Inc., Tinyclues SAS, Twiggle Ltd., Celect, Inc., Cortexica Vision Systems Ltd., Crobox B.V., Deepomatic SAS, Dynamic Yield Ltd., Emarsys eMarketing, Systems AG, Satisfi Labs, Inc., Staqu Technologies Pvt. Ltd., ViSenze Pte Ltd., and Other Prominent Players.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global AI Enabled E-Commerce Solutions Market Snapshot

Chapter 4. Global AI Enabled E-Commerce Solutions Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Technology Estimates & Trend Analysis

5.1. by Technology & Market Share, 2019 & 2030

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 for the following by Technology:

5.2.1. Deep Learning

5.2.2. Machine Learning

5.2.3. NLP

Chapter 6. Market Segmentation 2: by Applications Estimates & Trend Analysis

6.1. by Applications & Market Share, 2019 & 2030

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 for the following by Applications:

6.2.1. Customer Relationship Management

6.2.2. Supply Chain Analysis

6.2.3. Fake Review Analysis

6.2.4. Warehouse Automation

6.2.4.1.  Sorting and Placing

6.2.4.2.  Inventory Storage

6.2.5. Merchandizing

6.2.5.1.  Facets and Filter Selection

6.2.5.2.  Multi Device Interaction

6.2.6. Product Recommendation

6.2.7. Customer Service

6.2.7.1.  Chatbots

Chapter 7. Market Segmentation 3: by Deployment Estimates & Trend Analysis

7.1. by Deployment & Market Share, 2019 & 2030

7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 for the following by Deployment:

7.2.1. On-Premise

7.2.2. Cloud

Chapter 8. AI Enabled E-Commerce Solutions Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America

8.1.1. North America AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2019-2030

8.1.2. North America AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Applications, 2019-2030

8.1.3. North America AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2019-2030

8.1.4. North America AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2030

8.2. Europe

8.2.1. Europe AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Technology, 2019-2030

8.2.2. Europe AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Applications, 2019-2030

8.2.3. Europe AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2019-2030

8.2.4. Europe AI Enabled E-Commerce Solutions Market revenue (US$ Million) by country, 2019-2030

8.3. Asia Pacific

8.3.1. Asia Pacific AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Technology, 2019-2030

8.3.2. Asia Pacific AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Applications, 2019-2030

8.3.3. Asia Pacific AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2019-2030

8.3.4. Asia Pacific AI Enabled E-Commerce Solutions Market revenue (US$ Million) by country, 2019-2030

8.4. Latin America

8.4.1. Latin America AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Technology, 2019-2030

8.4.2. Latin America AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Applications, 2019-2030

8.4.3. Latin America AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2019-2030

8.4.4. Latin America AI Enabled E-Commerce Solutions Market revenue (US$ Million) by country, 2019-2030

8.5. Middle East & Africa

8.5.1. Middle East & Africa AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Technology, 2019-2030

8.5.2. Middle East & Africa AI Enabled E-Commerce Solutions Market revenue (US$ Million) by Applications, 2019-2030

8.5.3. Middle East & Africa AI Enabled E-Commerce Solutions Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2019-2030

8.5.4. Middle East & Africa AI Enabled E-Commerce Solutions Market revenue (US$ Million) by country, 2019-2030

Chapter 9. Competitive Landscape

9.1. Major Mergers and Acquisitions/Strategic Alliances

9.2. Company Profiles

9.2.1. Riskified

9.2.2. Reflektion, Inc.

9.2.3. Shelf.ai

9.2.4. Osaro

9.2.5. Sift

9.2.6. AntVoice SAS

9.2.7. Appier Inc

9.2.8. Eversight, Inc.

9.2.9. Granify Inc.

9.2.10. LivePerson, Inc.

9.2.11. Manthan Software Services Pvt. Ltd.

9.2.12. PayPal, Inc.

9.2.13. Sidecar Interactive, Inc.

9.2.14. Tinyclues SAS

9.2.15. Twiggle Ltd.

9.2.16. Celect, Inc.

9.2.17. Cortexica Vision Systems Ltd.

9.2.18. Crobox B.V.

9.2.19. Deepomatic SAS

9.2.20. Dynamic Yield Ltd.

9.2.21. Emarsys eMarketing Systems AG

9.2.22. Satisfi Labs, Inc.

9.2.23. Staqu Technologies Pvt. Ltd.

9.2.24. ViSenze Pte Ltd.

9.2.25. Other Prominent Players

Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 based on Technology

  • Deep Learning
  • Machine Learning
  • NLP

Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 based on Applications

  • Customer Relationship Management
  • Supply Chain Analysis
  • Fake Review Analysis
  • Warehouse Automation
  • Sorting and Placing
  • Inventory Storage
  • Merchandizing
  • Facets and Filter Selection
  • Multi Device Interaction
  • Product Recommendation
  • Customer Service
  • Chatbots

Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 based on Deployment

  • On-Premise
  • Cloud

Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2030 based on Region

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East & Africa

North America AI enabled E-Commerce solutions market revenue (US$ Million) by Country, 2019 to 2030

  • U.S.
  • Canada

Europe AI enabled E-Commerce solutions market revenue (US$ Million) by Country, 2019 to 2030

  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Rest of Europe

Asia Pacific AI enabled E-Commerce solutions market revenue (US$ Million) by Country, 2019 to 2030

  • India
  • China
  • Japan
  • South Korea
  • Australia & New Zealand

Latin America AI enabled E-Commerce solutions market revenue (US$ Million) by Country, 2019 to 2030

  • Brazil
  • Mexico
  • Rest of Latin America

Middle East & Africa AI enabled E-Commerce solutions market revenue (US$ Million) by Country, 2019 to 2030

  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa

 

Competitive Landscape

  • Company Overview
  • Financial Performance
  • Key Development

Latest Strategic Developments

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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AI-Enabled E-Commerce Solutions Market worth US$ 16.8 Billion by 2030

CAGR of 15.7% from 2021 to 2030.

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