[250 Pages Report] Newly-released Bot Services Market analysis report by Future Market Insights shows that global sales of the Bot Services Market in 2021 were held at US$ 1.2 Billion. With 18%, the projected market growth from 2022 to 2032 is expected to be slightly higher than the historical growth. The website channel is expected to be the highest revenue-generating segment, projected to grow at a CAGR of over 27.1% from 2022 to 2032.
| Attributes | Details |
|---|---|
| Bot Services Market Size (2022) | US$ 1.6 Billion |
| Bot Services Market Size (2032) | US$ 18 Billion |
| Bot Services Market CAGR (2022 to 2032) | 27.1% |
| USA Market CAGR (2022 to 2032) | 27.4% |
| Key Companies Covered |
|
Don't pay for what you don't need
Customize your report by selecting specific countries or regions and save 30%!
As per the Global Bot Services Market research by Future Market Insights - a market research and competitive intelligence provider, historically, from 2017 to 2021, the market value of the Bot Services Market increased at around 31.6% CAGR. Bots are becoming popular as a result of their applications across many industries. As more industries transition to omnichannel platforms to boost operational effectiveness, capitalize on improved consumer data, and put more emphasis on improving customer experience, the market for bots is anticipated to grow.
One of the primary target industries for the bot services market is the retail sector. In order to more precisely cross-sell and upsell products and better analyze customer behavior, many companies, including Amazon, have made significant investments and developed bots used in retail. According to IBM's most recent reports, Watson Assistant traffic increased by 40% between February 2020 and April 2020. Additionally, in response to rising customer demand, Google in April introduced the Rapid Response Virtual Agent, a particular variation of its Contact Center AI.
Large businesses frequently have too many tasks to complete, such as ordering products, requesting information about them, and paying for supplies. Enterprise-grade chatbots may readily execute these B2B duties, and such chatbot-integrated B2B systems can minimize total effort. Everything is realigned using the instant messaging platform so that the chatbots may fully automate these processes. Chatbots with AI and NLP capabilities can answer all questions about products, bills, payments, and other subjects.
The local government has been altering its service offerings to match public demand as chatbots, WhatsApp, and live chat become more prevalent in daily life. For instance, the UK government debuted a WhatsApp chatbot for the Coronavirus in March 2020. A plethora of knowledge regarding the coronavirus is provided by the chatbot. By adding the phone number as a WhatsApp contact and entering hello in the message field, anyone can access it. Additionally, the market is seeing a rise in the use of chatbots in the licensing industry. For instance, The Driver and Vehicle Licensing Agency added a chatbot to its webchat channel in April 2020 to offer millions of users more effective self-service.
In order to cut expenses, several organizations are automating their repetitive and time-consuming tasks. In order to significantly cut expenses, businesses are primarily focusing on automating customer service and sales. Artificial intelligence-enabled chatbots are becoming more prevalent. Businesses will save a large amount of money by implementing chatbots to automate parts of customer care and sales while significantly reducing labor costs.
Instead of making customers wait days for a response, customer support representatives should respond quickly. Using a chatbot to respond can significantly reduce the chance of losing a customer. Chatbots can be used by e-commerce companies for returns and exchanges. Chatbot adoption can drastically save annual costs by automating roughly 35% of tasks that would otherwise require a person to perform them manually.
Principal Consultant
One of the prominent drawbacks of chatbots is their inability to make timely decisions. Only the information that has been taught to chatbots will be understood by them. They are unable to discriminate between good and bad and cannot comprehend the context of humans, which is a significant gap that is likely to make a client unhappy. AI-powered intelligent bots can comprehend a variety of circumstances, however, they are unable to accurately interpret 40 out of every 100 client interactions. The poor decision-making abilities of chatbots have caused significant harm to several brands. Microsoft's chatbot Tay received significant backlash after its March 23, 2016, introduction. By tweeting offensive Tweets, the chatbot caused Microsoft enormous embarrassment. They were consequently compelled to briefly disable the chatbot.
Despite incorporating AI-produced NLP or ML technologies into their business processes, companies still struggle with a lack of qualified employees, including teams that can analyze data. However, there also exists a demand for experienced experts who have picked up these abilities. Acquisition and retention of technical resources have become key organizational concerns. The requisite skill sets are lacking for the development and execution of AI-based initiatives, which call for complex technologies like NLP and ML.
Data scientists, who have a thorough understanding of computer science, mathematics, and domain experience, are the most qualified analytics specialists. Most of the time, large organizations-or even small and medium-sized businesses-cannot afford to hire competent data scientists since they want high salaries and intriguing projects. As a result, it is projected that the current shortage of skilled labor would make it difficult for the market for bot services to grow.
During the projection period, Asia Pacific is predicted to lead Bot Services Market. China, Japan, and South Korea are the top three Bot Services markets in the Asia Pacific and are expected to account for a valuation of US$ 3 Billion by 2032. The Chinese Bot Services market is expected to account for a market of US$ 1.3 Billion by the end of 2032. Machine learning and chatbot development are being financed by several start-ups.
Due to chatbots' faultless performance, capacity to manage high client volumes, and enhanced customer engagement tactics, small and midsized organizations are swiftly integrating the use of chatbots in their customer care procedures. For Andhra Bank's 50 Million users, Floatbot developed an artificial intelligence chatbot in July 2019 for its core banking servers. It was put through a rigorous testing process including more than 50 Thousand inquiries with the goal of providing automated customer support and digital engagement.
Due to the rapidly expanding information and communications technology infrastructures in the region's prominent economies, notably China and India, the industry is expected to grow even more in the forthcoming years. For instance, AI chatbot firm Yellow Messengers received US$ 20 Million from an investor in April 2020 to fulfill the growing market need. The company provides organizations with an AI chatbot for consumer engagement. Hence, these factors are driving the demand for Bot Services in Asia Pacific.
Get the data you need at a Fraction of the cost
Personalize your report by choosing insights you need
and save 40%!
The USA is expected to account for the highest market of US$ 6.2 Billion by the end of 2032. Also, the market in the country is projected to account for an absolute dollar growth of US$ 5.7 Billion. For instance, in April 2021, Mindsay published AI chatbots on Genesys App Foundry. Agents may quickly engage and leave conversations with customers via the chatbot interface by integrating Mindsay chatbots with Genesys Cloud, responding to requests quickly and around the clock.
Since a large percentage of interactions are voice-based and come from the phone network, the providers are utilizing this opportunity to expand their companies by offering chatbots access to voice and telephony. For instance, PhoneMyBot will be available in December 2020, according to Interactive Media, a renowned manufacturer of customer experience, conversational AI, and telecom software. These factors are likely to increase the demand for Bot Services in the USA.
Market revenue through the website channel is forecasted to grow at a CAGR of over 27.1% from 2022 to 2032. Bots are pre-programmed chat interfaces that allow website visitors to speak with them. Chatbots can help website users by providing the information they require, whereas interactive bots can convert visitors into customers.
Artificial intelligence is used by chatbots to process language and communicates with users. For messaging systems like Skype, Facebook, Slack, and other key social media networking sites, several chatbots have been installed. Developers of chatbots can use these messaging platforms for payment services by directly linking the payment gateways with the assistant. One of the key opportunities in the market includes the chance to earn modest commission fees. Since chatbots allow for direct client connection, they are frequently employed in digital marketing to inform current customers about new goods and services.
Players in the market are constantly developing improved analytical solutions as well as extending their product offerings. The companies in the Bot Services market are focused on their alliances, technology collaborations, and product launch strategies. The Tier 2 Players in the market are targeting to increase their Bot Services market share.
Some of the recent developments of key Bot Services providers are as follows:
Similarly, recent developments related to companies in Bot Services Market have been tracked by the team at Future Market Insights, which are available in the full report.
The global Bot Services Market is worth more than US$ 1.6 Billion at present.
The value of Bot Services Market is projected to increase at a CAGR of around 27.4% from 2022 to 2032.
The value of Bot Services Market increased at a CAGR of around 31.6% from 2017 to 2021.
The demand for bot services through website channel has increased significantly in the recent past, consequently propelling the bot services demand.
The growth of the market for Bot Services in the USA is projected to expand at a CAGR of around 27.1% from 2022 to 2032.
The growth of the market for Bot Services in China is projected to expand at a CAGR of around 26.4% from 2022 to 2032.
While the market in South Korea is expected to grow at nearly 24.9%, the market in Japan is projected to register a CAGR of nearly 25.4% from 2022 to 2032.
1. Executive Summary | Bot Services Market 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 Analysis 2017 to 2021 and Forecast, 2022 to 2032 4.1. Historical Market Size Value (US$ Million) Analysis, 2017 to 2021 4.2. Current and Future Market Size Value (US$ Million) Projections, 2022 to 2032 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Service Type 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Service Type, 2017 to 2021 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Service Type, 2022 to 2032 5.3.1. Framework 5.3.2. Platform 5.3.2.1. Service, Mode of the channel, 5.4. Y-o-Y Growth Trend Analysis By Service Type, 2017 to 2021 5.5. Absolute $ Opportunity Analysis By Service Type, 2022 to 2032 6. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Mode of Channel 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Mode of Channel, 2017 to 2021 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Mode of Channel, 2022 to 2032 6.3.1. Website 6.3.2. Contact Centers 6.3.3. Social Media 6.3.4. Mobile Applications 6.4. Y-o-Y Growth Trend Analysis By Mode of Channel, 2017 to 2021 6.5. Absolute $ Opportunity Analysis By Mode of Channel, 2022 to 2032 7. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Verticals 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Verticals, 2017 to 2021 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Verticals, 2022 to 2032 7.3.1. BFSI 7.3.2. Retail & eCommerce 7.3.3. Healthcare & Life Sciences 7.3.4. Media & Entertainment 7.3.5. Travel & Hospitality 7.3.6. IT & Telecom 7.3.7. Government 7.3.8. Other Verticals 7.4. Y-o-Y Growth Trend Analysis By Verticals, 2017 to 2021 7.5. Absolute $ Opportunity Analysis By Verticals, 2022 to 2032 8. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Business Function 8.1. Introduction / Key Findings 8.2. Historical Market Size Value (US$ Million) Analysis By Business Function, 2017 to 2021 8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Business Function, 2022 to 2032 8.3.1. Sales & Marketing 8.3.2. Finance 8.3.3. Supply Chain & Logistics 8.3.4. Information Technology (IT) 8.4. Y-o-Y Growth Trend Analysis By Business Function, 2017 to 2021 8.5. Absolute $ Opportunity Analysis By Business Function, 2022 to 2032 9. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Application 9.1. Introduction / Key Findings 9.2. Historical Market Size Value (US$ Million) Analysis By Application, 2017 to 2021 9.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2022 to 2032 9.3.1. Customer Engagement & Retention 9.3.2. Workforce Management 9.3.3. Agent Performance Management 9.3.4. Content Management 9.3.5. Appointment Scheduling 9.3.6. Employee Onboarding 9.3.7. Other Applications 9.4. Y-o-Y Growth Trend Analysis By Application, 2017 to 2021 9.5. Absolute $ Opportunity Analysis By Application, 2022 to 2032 10. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Deployment Mode 10.1. Introduction / Key Findings 10.2. Historical Market Size Value (US$ Million) Analysis By Deployment Mode, 2017 to 2021 10.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Mode, 2022 to 2032 10.3.1. On-premises 10.3.2. Cloud 10.4. Y-o-Y Growth Trend Analysis By Deployment Mode, 2017 to 2021 10.5. Absolute $ Opportunity Analysis By Deployment Mode, 2022 to 2032 11. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Organization Size 11.1. Introduction / Key Findings 11.2. Historical Market Size Value (US$ Million) Analysis By Organization Size, 2017 to 2021 11.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Organization Size, 2022 to 2032 11.3.1. Large Enterprises 11.3.2. SMEs 11.4. Y-o-Y Growth Trend Analysis By Organization Size, 2017 to 2021 11.5. Absolute $ Opportunity Analysis By Organization Size, 2022 to 2032 12. Global Analysis 2017 to 2021 and Forecast 2022 to 2032, By Region 12.1. Introduction 12.2. Historical Market Size Value (US$ Million) Analysis By Region, 2017 to 2021 12.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2022 to 2032 12.3.1. North America 12.3.2. Latin America 12.3.3. Europe 12.3.4. Asia Pacific 12.3.5. Middle East and Africa (MEA) 12.4. Market Attractiveness Analysis By Region 13. North America Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2017 to 2021 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2022 to 2032 13.2.1. By Country 13.2.1.1. United States of America 13.2.1.2. Canada 13.2.2. By Service Type 13.2.3. By Mode of Channel 13.2.4. By Verticals 13.2.5. By Business Function 13.2.6. By Application 13.2.7. By Deployment Mode 13.2.8. By Organization Size 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Service Type 13.3.3. By Mode of Channel 13.3.4. By Verticals 13.3.5. By Business Function 13.3.6. By Application 13.3.7. By Deployment Mode 13.3.8. By Organization Size 13.4. Key Takeaways 14. Latin America Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2017 to 2021 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2022 to 2032 14.2.1. By Country 14.2.1.1. Brazil 14.2.1.2. Mexico 14.2.1.3. Rest of Latin America 14.2.2. By Service Type 14.2.3. By Mode of Channel 14.2.4. By Verticals 14.2.5. By Business Function 14.2.6. By Application 14.2.7. By Deployment Mode 14.2.8. By Organization Size 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Service Type 14.3.3. By Mode of Channel 14.3.4. By Verticals 14.3.5. By Business Function 14.3.6. By Application 14.3.7. By Deployment Mode 14.3.8. By Organization Size 14.4. Key Takeaways 15. Europe Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2017 to 2021 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2022 to 2032 15.2.1. By Country 15.2.1.1. Germany 15.2.1.2. United Kingdom 15.2.1.3. France 15.2.1.4. Spain 15.2.1.5. Italy 15.2.1.6. Rest of Europe 15.2.2. By Service Type 15.2.3. By Mode of Channel 15.2.4. By Verticals 15.2.5. By Business Function 15.2.6. By Application 15.2.7. By Deployment Mode 15.2.8. By Organization Size 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Service Type 15.3.3. By Mode of Channel 15.3.4. By Verticals 15.3.5. By Business Function 15.3.6. By Application 15.3.7. By Deployment Mode 15.3.8. By Organization Size 15.4. Key Takeaways 16. Asia Pacific Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country 16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2017 to 2021 16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2022 to 2032 16.2.1. By Country 16.2.1.1. China 16.2.1.2. Japan 16.2.1.3. South Korea 16.2.1.4. India 16.2.1.5. Malaysia 16.2.1.6. Singapore 16.2.1.7. Australia 16.2.1.8. New Zealand 16.2.1.9. Rest of APAC 16.2.2. By Service Type 16.2.3. By Mode of Channel 16.2.4. By Verticals 16.2.5. By Business Function 16.2.6. By Application 16.2.7. By Deployment Mode 16.2.8. By Organization Size 16.3. Market Attractiveness Analysis 16.3.1. By Country 16.3.2. By Service Type 16.3.3. By Mode of Channel 16.3.4. By Verticals 16.3.5. By Business Function 16.3.6. By Application 16.3.7. By Deployment Mode 16.3.8. By Organization Size 16.4. Key Takeaways 17. MEA Analysis 2017 to 2021 and Forecast 2022 to 2032, By Country 17.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2017 to 2021 17.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2022 to 2032 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 Service Type 17.2.3. By Mode of Channel 17.2.4. By Verticals 17.2.5. By Business Function 17.2.6. By Application 17.2.7. By Deployment Mode 17.2.8. By Organization Size 17.3. Market Attractiveness Analysis 17.3.1. By Country 17.3.2. By Service Type 17.3.3. By Mode of Channel 17.3.4. By Verticals 17.3.5. By Business Function 17.3.6. By Application 17.3.7. By Deployment Mode 17.3.8. By Organization Size 17.4. Key Takeaways 18. Key Countries Analysis 18.1. United States of America 18.1.1. Pricing Analysis 18.1.2. Market Share Analysis, 2021 18.1.2.1. By Service Type 18.1.2.2. By Mode of Channel 18.1.2.3. By Verticals 18.1.2.4. By Business Function 18.1.2.5. By Application 18.1.2.6. By Deployment Mode 18.1.2.7. By Organization Size 18.2. Canada 18.2.1. Pricing Analysis 18.2.2. Market Share Analysis, 2021 18.2.2.1. By Service Type 18.2.2.2. By Mode of Channel 18.2.2.3. By Verticals 18.2.2.4. By Business Function 18.2.2.5. By Application 18.2.2.6. By Deployment Mode 18.2.2.7. By Organization Size 18.3. Brazil 18.3.1. Pricing Analysis 18.3.2. Market Share Analysis, 2021 18.3.2.1. By Service Type 18.3.2.2. By Mode of Channel 18.3.2.3. By Verticals 18.3.2.4. By Business Function 18.3.2.5. By Application 18.3.2.6. By Deployment Mode 18.3.2.7. By Organization Size 18.4. Mexico 18.4.1. Pricing Analysis 18.4.2. Market Share Analysis, 2021 18.4.2.1. By Service Type 18.4.2.2. By Mode of Channel 18.4.2.3. By Verticals 18.4.2.4. By Business Function 18.4.2.5. By Application 18.4.2.6. By Deployment Mode 18.4.2.7. By Organization Size 18.5. Germany 18.5.1. Pricing Analysis 18.5.2. Market Share Analysis, 2021 18.5.2.1. By Service Type 18.5.2.2. By Mode of Channel 18.5.2.3. By Verticals 18.5.2.4. By Business Function 18.5.2.5. By Application 18.5.2.6. By Deployment Mode 18.5.2.7. By Organization Size 18.6. United Kingdom 18.6.1. Pricing Analysis 18.6.2. Market Share Analysis, 2021 18.6.2.1. By Service Type 18.6.2.2. By Mode of Channel 18.6.2.3. By Verticals 18.6.2.4. By Business Function 18.6.2.5. By Application 18.6.2.6. By Deployment Mode 18.6.2.7. By Organization Size 18.7. France 18.7.1. Pricing Analysis 18.7.2. Market Share Analysis, 2021 18.7.2.1. By Service Type 18.7.2.2. By Mode of Channel 18.7.2.3. By Verticals 18.7.2.4. By Business Function 18.7.2.5. By Application 18.7.2.6. By Deployment Mode 18.7.2.7. By Organization Size 18.8. Spain 18.8.1. Pricing Analysis 18.8.2. Market Share Analysis, 2021 18.8.2.1. By Service Type 18.8.2.2. By Mode of Channel 18.8.2.3. By Verticals 18.8.2.4. By Business Function 18.8.2.5. By Application 18.8.2.6. By Deployment Mode 18.8.2.7. By Organization Size 18.9. Italy 18.9.1. Pricing Analysis 18.9.2. Market Share Analysis, 2021 18.9.2.1. By Service Type 18.9.2.2. By Mode of Channel 18.9.2.3. By Verticals 18.9.2.4. By Business Function 18.9.2.5. By Application 18.9.2.6. By Deployment Mode 18.9.2.7. By Organization Size 18.10. China 18.10.1. Pricing Analysis 18.10.2. Market Share Analysis, 2021 18.10.2.1. By Service Type 18.10.2.2. By Mode of Channel 18.10.2.3. By Verticals 18.10.2.4. By Business Function 18.10.2.5. By Application 18.10.2.6. By Deployment Mode 18.10.2.7. By Organization Size 18.11. Japan 18.11.1. Pricing Analysis 18.11.2. Market Share Analysis, 2021 18.11.2.1. By Service Type 18.11.2.2. By Mode of Channel 18.11.2.3. By Verticals 18.11.2.4. By Business Function 18.11.2.5. By Application 18.11.2.6. By Deployment Mode 18.11.2.7. By Organization Size 18.12. South Korea 18.12.1. Pricing Analysis 18.12.2. Market Share Analysis, 2021 18.12.2.1. By Service Type 18.12.2.2. By Mode of Channel 18.12.2.3. By Verticals 18.12.2.4. By Business Function 18.12.2.5. By Application 18.12.2.6. By Deployment Mode 18.12.2.7. By Organization Size 18.13. Malaysia 18.13.1. Pricing Analysis 18.13.2. Market Share Analysis, 2021 18.13.2.1. By Service Type 18.13.2.2. By Mode of Channel 18.13.2.3. By Verticals 18.13.2.4. By Business Function 18.13.2.5. By Application 18.13.2.6. By Deployment Mode 18.13.2.7. By Organization Size 18.14. Singapore 18.14.1. Pricing Analysis 18.14.2. Market Share Analysis, 2021 18.14.2.1. By Service Type 18.14.2.2. By Mode of Channel 18.14.2.3. By Verticals 18.14.2.4. By Business Function 18.14.2.5. By Application 18.14.2.6. By Deployment Mode 18.14.2.7. By Organization Size 18.15. Australia 18.15.1. Pricing Analysis 18.15.2. Market Share Analysis, 2021 18.15.2.1. By Service Type 18.15.2.2. By Mode of Channel 18.15.2.3. By Verticals 18.15.2.4. By Business Function 18.15.2.5. By Application 18.15.2.6. By Deployment Mode 18.15.2.7. By Organization Size 18.16. New Zealand 18.16.1. Pricing Analysis 18.16.2. Market Share Analysis, 2021 18.16.2.1. By Service Type 18.16.2.2. By Mode of Channel 18.16.2.3. By Verticals 18.16.2.4. By Business Function 18.16.2.5. By Application 18.16.2.6. By Deployment Mode 18.16.2.7. By Organization Size 18.17. GCC Countries 18.17.1. Pricing Analysis 18.17.2. Market Share Analysis, 2021 18.17.2.1. By Service Type 18.17.2.2. By Mode of Channel 18.17.2.3. By Verticals 18.17.2.4. By Business Function 18.17.2.5. By Application 18.17.2.6. By Deployment Mode 18.17.2.7. By Organization Size 18.18. South Africa 18.18.1. Pricing Analysis 18.18.2. Market Share Analysis, 2021 18.18.2.1. By Service Type 18.18.2.2. By Mode of Channel 18.18.2.3. By Verticals 18.18.2.4. By Business Function 18.18.2.5. By Application 18.18.2.6. By Deployment Mode 18.18.2.7. By Organization Size 18.19. Israel 18.19.1. Pricing Analysis 18.19.2. Market Share Analysis, 2021 18.19.2.1. By Service Type 18.19.2.2. By Mode of Channel 18.19.2.3. By Verticals 18.19.2.4. By Business Function 18.19.2.5. By Application 18.19.2.6. By Deployment Mode 18.19.2.7. By Organization Size 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 Service Type 19.3.3. By Mode of Channel 19.3.4. By Verticals 19.3.5. By Business Function 19.3.6. By Application 19.3.7. By Deployment Mode 19.3.8. By Organization Size 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. Google 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. Oracle 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. Artificial Solutions 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. Meta 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. Enterprise Bot 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. Baidu 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. Haptik 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. Webio 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 20.1.11. AWS 20.1.11.1. Overview 20.1.11.2. Product Portfolio 20.1.11.3. Profitability by Market Segments 20.1.11.4. Sales Footprint 20.1.11.5. Strategy Overview 20.1.11.5.1. Marketing Strategy 21. Assumptions & Acronyms Used 22. Research Methodology
Explore Technology Insights
View Reports
Bot Services Market
