市場調查報告書
商品編碼
1466390
客服中心人工智慧市場:按元件、應用程式、部署、組織、產業分類 - 2024-2030 年全球預測Call Center AI Market by Component (Services, Software), Application (Agent Performance Management, Appointment Scheduling, Journey Orchestration), Deployment, Organization, Vertical - Global Forecast 2024-2030 |
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預計2023年客服中心人工智慧市場規模為24億美元,2024年預估達29億美元,2030年將達98.5億美元,複合年成長率為22.34%。
客服中心人工智慧,也稱為客服中心人工智慧,充當自動化系統,旨在簡化客戶交互,同時提高效率和生產力。這項先進的技術使用機器學習演算法和自然語言處理來理解、解釋和回應客戶的詢問,提供 24/7 虛擬援助。客服中心人工智慧軟體可自動執行呼叫路由、資料收集和日常客戶查詢等任務,減少人工參與,使員工能夠專注於更複雜和定性的任務。人工智慧和機器學習技術的進步、數位化的提高以及客戶服務業務對成本效益的需求正在加速對客服中心人工智慧的需求。然而,資料隱私問題、技術故障和故障的風險以及實施和維護人工智慧解決方案的成本正在阻礙其普及。開拓公司透過先進的預測分析來解決隱私問題,以實現更準確的資料預測,支援人工智慧的培訓模組可提高代理績效,類人對話人工智慧可提高客戶參與。方案。隨著該領域的積極研發,客服中心AI市場可望成為未來利潤豐厚的投資領域。
主要市場統計 | |
---|---|
基準年[2023] | 24億美元 |
預測年份 [2024] | 29億美元 |
預測年份 [2030] | 98.5億美元 |
複合年成長率(%) | 22.34% |
組件 開發高效能客服中心人工智慧軟體以改善客戶體驗
服務包括客服中心人工智慧實施和營運的專業服務和支援服務。專業服務包括諮詢、系統整合、客製化和培訓,幫助企業有效實施人工智慧解決方案。支援服務包括維護技術支援和持續協助,以確保客服中心AI的順利運作。客服中心人工智慧領域的第二個組成部分是軟體,包括自動回應、簡化呼叫流程和提供客戶分析的解決方案。許多公司更喜歡提供豐富的人工智慧實施並確保根據其要求輕鬆整合和客製化的軟體解決方案。客服中心人工智慧軟體解決方案可實現自動化、銷售服務、即時資料分析、客戶關係管理以及與客服中心應用程式的整合。呼叫路由和互動語音回覆系統(IVR) 系統、預測分析軟體和情緒分析工具是客服中心人工智慧的一些關鍵工具。
部署:雲端客服中心人工智慧提供擴充性、成本效益和易於更新
客服中心人工智慧的雲端部署是許多公司選擇的可存取、可擴展且經濟高效的解決方案。雲端部署通常最適合工作負載波動的企業或需要自動線上更新人工智慧軟體的企業。它也適合希望降低硬體、軟體和內部 IT 人員成本的企業。重視對其解決方案和資料進行細粒度控制的公司更喜歡本地部署客服中心人工智慧。這些解決方案特別適合擁有大量 IT 資源和監管要求的大型企業,以將資料保存在自己的基礎架構內。
快速普及人工智慧來最佳化應用客服中心的座席效能
人工智慧可以透過提供即時回饋和績效指標來幫助監控和提高座席績效。人工智慧用於衡量代理的有效性和效率,以確保無縫的客戶服務。人工智慧透過最佳化客服人員時間和提高客戶滿意度來幫助有效安排預約。借助人工智慧系統,繪製和簡化客戶旅程變得更加順暢,確保與客戶的個人化聯繫。預測呼叫路由採用人工智慧根據資料分析有目的地路由客戶呼叫。市場相關人員正在將客戶情緒和偏好納入其路由演算法中,以提供更好的服務。客服中心的人工智慧使用情緒分析來確定客戶對產品和服務的態度。領先的供應商正在使用人工智慧來分析詞彙、音調和語氣,以更好地了解客戶的氣質。借助工作流程自動化和智慧調度,人工智慧技術將機器學習整合到平台中,最佳化勞動力管理並釋放勞動力的全部潛力。
分區:客服中心AI在銀行、金融、保險等領域廣泛應用
BFSI 領域繼續需要增強人工智慧,以改善客戶交互,例如帳戶查詢和提供有關金融產品的資訊。醫療保健領域的人工智慧支援臨床決策和患者檢查,並為預約安排和圖表管理提供協助。在媒體和娛樂領域,人工智慧有助於個人化和推薦內容。演算法分析用戶偏好和觀看習慣並提供個人化內容,從而提高用戶參與度。從庫存管理到個人化購物體驗,人工智慧正在為零售和電子商務提供幫助。人工智慧演算法還根據需求、競爭等因素調整產品價格,以擴大盈利。在通訊業,人工智慧可以幫助通訊業者維護網路健康並改善客戶服務。人工智慧監控網路效能,識別問題並預測不間斷服務的維護,這些品質可以有利於客服中心代理提供更好的服務。旅遊和酒店業中的人工智慧可改善客戶預訂體驗並最佳化業務效率。人工智慧將追蹤您的旅行行程,發送更新並提供有關當地景點的資訊。
區域洞察
在美洲,客服中心人工智慧被廣泛採用,主要是在美國和加拿大,這是為最終用戶提供多樣化解決方案的主要技術提供者的所在地。隨著這些技術提高生產力,電子商務平台、電信業者和金融服務正在實現積極成長。在日本、韓國和新加坡等技術先進國家,人工智慧正在整合到客服中心中,以提供多語言支援和即時客戶協助。在印度和菲律賓等新興經濟體,人工智慧新興企業在客服中心人工智慧市場不斷湧現。亞洲也是客服中心的重要外包地點,擴大採用人工智慧解決方案來處理日益增加的客戶互動。歐洲注重資料保護和客戶隱私,精心實施了客服中心人工智慧,以確保 GDPR 合規性。在德國、法國和英國等國家,人工智慧聊天機器人和語音助理越來越受歡迎,並保證 24/7 客戶支援。在東歐,醫療保健和通訊業的採用正在取得進展,重點是對現有員工進行人工智慧技術培訓,以確保無縫過渡。
FPNV定位矩陣
FPNV定位矩陣對於評估客服中心 AI市場至關重要。我們檢視與業務策略和產品滿意度相關的關鍵指標,以對供應商進行全面評估。這種深入的分析使用戶能夠根據自己的要求做出明智的決策。根據評估,供應商被分為四個成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市場佔有率分析
市場佔有率分析是一個綜合工具,可以對客服中心人工智慧市場中供應商的現狀進行深入而深入的研究。全面比較和分析供應商在整體收益、基本客群和其他關鍵指標方面的貢獻,以便更好地了解公司的績效及其在爭奪市場佔有率時面臨的挑戰。此外,該分析還提供了對該行業競爭特徵的寶貴見解,包括在研究基準年觀察到的累積、分散主導地位和合併特徵等因素。這種詳細程度的提高使供應商能夠做出更明智的決策並制定有效的策略,從而在市場上獲得競爭優勢。
1. 市場滲透率:提供有關主要企業所服務的市場的全面資訊。
2. 市場開拓:我們深入研究利潤豐厚的新興市場,並分析其在成熟細分市場的滲透率。
3. 市場多元化:提供有關新產品發布、開拓地區、最新發展和投資的詳細資訊。
4. 競爭評估和情報:對主要企業的市場佔有率、策略、產品、認證、監管狀況、專利狀況和製造能力進行全面評估。
5. 產品開發與創新:提供對未來技術、研發活動和突破性產品開發的見解。
1.客服中心AI市場的市場規模與預測為何?
2.客服中心人工智慧市場預測期間需要考慮投資的產品、細分市場、應用程式和領域有哪些?
3.客服中心AI市場的技術趨勢和法規結構是什麼?
4.客服中心AI市場主要廠商的市場佔有率如何?
5.進入客服中心AI市場合適的型態和策略手段是什麼?
[184 Pages Report] The Call Center AI Market size was estimated at USD 2.40 billion in 2023 and expected to reach USD 2.90 billion in 2024, at a CAGR 22.34% to reach USD 9.85 billion by 2030.
Call center AI, also known as artificial intelligence in call centers, functions as an automated system designed to streamline customer interactions while enhancing efficiency and productivity. This sophisticated technology utilizes machine learning algorithms and natural language processing to understand, interpret, and respond to customer inquiries, providing 24/7 virtual assistance. Automating tasks such as call routing, data collection, and routine customer queries with call center AI software reduces human involvement, allowing staff to focus on more complex and qualitative tasks. Advancements in AI and machine learning technologies, the push towards digitization, and the need for cost-effectiveness in customer service operations have accelerated the demand for call center AI. However, data privacy issues, the risk of technology failure or glitches, and the cost of implementing and maintaining AI solutions have impeded their widespread adoption. Market players are developing advanced predictive analytics for more accurate demand forecasting, AI-enabled training modules for enhancing agent performance, human-like conversational AI for better customer engagement, and secure data handling solutions that address privacy concerns. Rigorous research and development in these areas is expected to make the call center AI market a lucrative area for investment in the future.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 2.40 billion |
Estimated Year [2024] | USD 2.90 billion |
Forecast Year [2030] | USD 9.85 billion |
CAGR (%) | 22.34% |
Component: Development of high-performing call center AI software to provide enhanced customer experience
Services include professional and support services related to call center AI implementation and operation. Professional services cover consulting, system integration, customization, and training to help businesses implement AI solutions effectively. Support services encompass maintenance technical support and ongoing assistance to ensure the smooth operation of call center AI. Software, the second component of the Call Center AI field, entails solutions that automate responses, streamline call flows, and offer customer analytics. Many businesses prefer software solutions that provide high-functioning AI implementations, ensuring ease of integration and customization according to their requirements. Call center AI software solutions enable automation, sell service, real-time data analysis, and integration with customer relationship management and contact center applications. Call routing and interactive voice response (IVR) systems, predictive analytics software, and sentiment analysis tools are some of the major call center AI tools utilized.
Deployment: Increased scalability, cost-effectiveness, and ease of updates offered by on-cloud call center AI
On-cloud deployment of call center AI has emerged as a preferred choice for many businesses as this model facilitates accessible, scalable, and cost-effective solutions. On-cloud deployment is generally ideal for businesses with fluctuating workloads and those that need online and automated updates to their AI software. It is also suitable for organizations seeking to cut down on hardware, software, and in-house IT staffing costs. On-premises deployment of call center AI is preferred by businesses emphasizing granular control over their solution and data. These solutions are particularly suitable for larger organizations with significant IT resources and regulatory requirements to keep data within their own infrastructure.
Application: Exponential adoption of AI for optimizing agent performance in call centers
AI can assist in monitoring and improving agent performance by providing real-time feedback and performance metrics. AI is used to measure the effectiveness and efficiency of agents to ensure seamless customer service. AI aids in scheduling appointments effectively by optimizing agents' time and improving customer satisfaction. Mapping and streamlining customer journeys are made smoother by AI systems, ensuring personalized connections with customers. Predictive call routing employs AI to route customer calls purposefully based on data analysis. Market players are incorporating customer emotions and preferences into routing algorithms to offer improved services. AI in call centers uses sentiment analysis to determine customers' attitudes toward products or services. Major providers use AI to analyze words, pitch, and tone to understand customer temperament better. Through workflow automation and intelligent scheduling, AI technologies optimize workforce management by integrating machine learning into its platform to maximize workforce potential.
Vertical: Extensive usability of call center AI in banking, finance, and insurance sectors
The BFSI sector continually requires AI enhancements to improve customer interactions by offering assistance with account inquiries and information on financial products. AI in healthcare aids in clinical decision-making and patient consultations while offering help with appointment scheduling and medical records management. In media and entertainment, AI assists with content personalization and recommendation as the algorithms analyze user preferences and viewing habits to offer personalized content, improving user engagement. From inventory management to personalized shopping experiences, AI proves instrumental in the retail & eCommerce sector. AI algorithms also adjust product pricing based on demand, competition, and other factors to expand profitability. AI assists telecom operators in maintaining the network's health and improving customer service in the telecommunications industry. AI monitors network performance, identifies issues, and predicts maintenance for uninterrupted service, and these qualities can benefit the call center agent to provide better services. AI in travel and hospitality enhances customer booking experiences and optimizes operational efficiency. AI complies with travel itineraries, sends updates, and provides information on local attractions.
Regional Insights
In the Americas, call center AI has been widely adopted, mainly in the U.S. and Canada, being home to major technology providers offering diverse solutions for end-users. E-commerce platforms, telecommunication companies, and financial services have shown positive growth and productivity enhancements due to these technologies. Predominantly in technologically advanced countries like Japan, South Korea, and Singapore, AI has been integrated into call centers, providing multilingual support and real-time customer assistance. In developing economies of India, the Philippines, and others, AI startups are emerging in the call center AI market. Asia is also a significant outsourcing hub for call centers, and the adoption of AI solutions is on the rise to handle the increasing volume of customer interactions. Europe's emphasis on data protection and customer privacy has cautiously implemented call center AI, ensuring GDPR compliance. AI-powered chatbots and voice assistants have gained popularity in nations such as Germany, France, and the UK, guaranteeing 24/7 customer support. In Eastern Europe, markets are catching up with the adoption across healthcare and telecom industries, focusing on training the existing workforce about AI technologies to ensure a seamless transition.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Call Center AI Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Call Center AI Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Call Center AI Market, highlighting leading vendors and their innovative profiles. These include Artificial Solutions, Avaya Holdings Corp., Cognigy GmbH, Conversica, Inc., Cresta Intelligence, Inc., Dialpad, Inc., Five9, Inc. by Zoom Video Communications, Inc., Gemshelf Inc., Google, LLC by Alphabet, Inc., Inbenta Technologies Inc., Infinitus Systems, Inc., International Business Machines Corporation, Jio Haptik Technologies Limited, Kore.ai, Inc., Level AI, LivePerson, Inc., Microsoft Corporation, Nextiva, Inc., Oracle Corporation, Parloa GmbH, PolyAI Limited, Pypestream Inc., Replicant Solutions, Inc., RingCentral, Inc., Rulai, Inc., SAP SE, Skit USA, Inc., Talkdesk, Uniphore Technologies Inc., and Zendesk, Inc..
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Call Center AI Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Call Center AI Market?
3. What are the technology trends and regulatory frameworks in the Call Center AI Market?
4. What is the market share of the leading vendors in the Call Center AI Market?
5. Which modes and strategic moves are suitable for entering the Call Center AI Market?