市場調查報告書
商品編碼
1466450
資料收益市場:按組成部分、資料類型、業務功能、部署類型、組織規模、產業 - 2024-2030 年全球預測Data Monetization Market by Component (Services, Tools), Data Type (Customer Data, Financial Data, Product Data), Business Function, Deployment Type, Organization Size, Vertical - Global Forecast 2024-2030 |
※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。
預計2023年資料收益市場規模為38.3億美元,預計2024年將達45.8億美元,2030年將達到135.5億美元,複合年成長率為19.75%。
資料收益市場由個人、公司或實體組成的互連網路組成,營業單位創建、收集、共用、交易和利用資料作為有價值的資源或商品。資料量的增加和資料儲存成本的降低正在促進市場的成長。對資料主導決策的日益關注以及高級分析和視覺化的快速成長也推動了資料收益市場的採用。然而,資料結構日益複雜可能限制資料收益解決方案的採用。此外,與資料收益解決方案相關的安全和隱私問題也是市場成長的一個令人擔憂的因素。此外,資料收益解決方案的進步和新興國家數位化的提高預計將為市場帶來巨大的成長潛力。
主要市場統計 | |
---|---|
基準年[2023] | 38.3億美元 |
預測年份 [2024] | 45.8億美元 |
預測年份 [2030] | 135.5億美元 |
複合年成長率(%) | 19.75% |
更多使用資料收益諮詢服務來發展組件業務
在資料收益市場中,諮詢服務主要提供專家指導、見解和解決方案,幫助企業最佳化資料產生、收集和使用。部署和整合服務將資料分析解決方案無縫整合到您現有的基礎架構中,最終促進向資料主導的決策和業務的平穩過渡。支援和維護服務維護資料商業化戰略的整體功能,確保不間斷地存取正確的資料,並實現資料主導流程的最佳運行,從而提高業務效率和盈利。資料收益工具可以成為寶貴的資產,可以從原始資料中提取有形價值,並揭示影響商務策略和盈利的隱藏趨勢。
資料類型利用產品資料的激增實現更好的資料收益
客戶資料主要提供對現有和潛在客戶的行為、偏好和屬性的洞察。基於客戶資料的詳細分析可以推動個人化行銷策略、改善客戶體驗並提高客戶忠誠度和銷售。財務資料代表公司進行的財務交易,由損益表、資產負債表、現金流量表、報稅表等組成,用於評估經濟趨勢、檢查過去的業績並預測未來的結果。產品資料包括有關公司庫存的資訊,例如產品規格、價格、可用性和銷售統計數據。供應商資料包括有關公司供應商及其績效指標的資訊。對供應商資料進行有效分析和收益有助於建立更好的談判地位,提高供應鏈效率並降低潛在風險。
業務職能:透過加強資料收益解決方案來改善銷售和行銷業務
財務部門透過分析歷史財務資料並有效預測收益趨勢、潛在風險和成長機會,使用資料收益進行預測預算和預測。在營運中,資料收益支援資料驅動驅動的決策和策略,以實現更好的資源分配、人才管理和成本效率。銷售和行銷團隊正在使用資料收益來更好地定位廣告、了解消費行為、預測購買模式、個人化宣傳活動等。公司將供應鏈資料收益,以最佳化存量基準、資產利用率、提高路線效率、對庫存不足和庫存過剩情況進行預測分析,並減少不必要的支出。
部署類型:增強型雲端部署模型
雲端部署模型中的資料收益利用了雲端資源的可擴展性、彈性和可負擔性。組織可以實施計量收費模式,使他們能夠根據資料收益工作來擴展儲存需求。雲端的採用還支援即時分析,這對於資料商業化戰略非常重要。本地資料收益利用組織現有的基礎架構進行資料收集、儲存和分析,使您能夠更好地控制資料環境。本地可讓您密切管理和監控資料環境,降低資料外洩和未授權存取的風險。
組織規模:中小型企業大量採用資料收益解決方案
大型企業擴大轉向資料收益,以擴大收益來源並釋放新的商機。大型企業正在利用其資料資產為客戶開發新服務或將資料出售給第三方以直接收益來創造業務成長潛力。小型企業在實施資料商業化戰略方面具有更大的靈活性,因為它們的資料生態系統不那麼複雜,監管障礙也比大型企業低。中小型企業通常專注於內部資料收益,以從資料中獲取可操作的見解,以最佳化業務流程並提高效率。
按行業分類:各行業擴大引入資料收益解決方案
透過資料收益解決方案,金融機構正在利用客戶資料來預測客戶行為、改善風險管理、創造個人化銀行體驗並推動核保決策。零售商可以利用資料收益工具來了解消費者的行為、偏好和購買模式。能源公司可以更有效地部署資料商業化戰略來管理能源生產、消耗和分配。醫療保健提供者通常使用患者資料在健康問題變得嚴重之前預測健康問題,並制定必要的治療方案以改善患者的治療結果。 IT 公司正在透過資料貨幣化來提供新產品、增強現有服務、個人化軟體解決方案並改善客戶體驗。資料收益解決方案幫助媒體和娛樂公司了解受眾偏好、消費模式和參與習慣。運輸和物流公司可以利用資料商業化戰略來改善路線規劃、車輛維護、車隊管理並最佳化物流業務。
區域洞察
在美洲地區,技術創新和主要參與者的強大影響力,特別是在美國和加拿大,已經在資料收益市場上留下了顯著的足跡。強大的技術基礎設施、物聯網設備的普及以及巨量資料分析的不斷成長趨勢為美洲地區的市場成長做出了重大貢獻。在歐洲地區,向工業 4.0 的轉變和嚴格的監管環境正在對資料收益市場產生積極影響。德國、義大利和法國等國家對人工智慧和預測分析的採用率很高,增加了資料收益的商機。公共部門數位轉型舉措,尤其是海灣合作理事會國家的公共部門數位轉型舉措,已成為中東和北非地區資料收益的關鍵成長催化劑。由於印度和中國等新興國家的快速數位轉型,亞太地區成為資料收益成長最快的市場之一。除了雄心勃勃的經濟成長議程外,亞太地區國家越來越關注工業4.0,高科技監管政策正在推動該地區的資料收益市場。
FPNV定位矩陣
FPNV定位矩陣對於評估資料收益市場至關重要。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種綜合工具,可以對資料收益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。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.競爭評估與資訊: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、製造能力等進行全面評估。
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.資料收益市場的市場規模與預測是多少?
2.在資料收益市場的預測期內,有哪些產品、細分市場、應用程式和領域需要考慮投資?
3.資料收益市場的技術趨勢和法規結構是什麼?
4.資料收益市場主要廠商的市場佔有率是多少?
5. 進入資料收益市場的合適型態和策略手段是什麼?
[183 Pages Report] The Data Monetization Market size was estimated at USD 3.83 billion in 2023 and expected to reach USD 4.58 billion in 2024, at a CAGR 19.75% to reach USD 13.55 billion by 2030.
Data monetization market comprises the interconnected network of individuals, companies, or entities that create, collect, share, trade, and utilize data as a valuable resource or commodity. The increase in data volume and lower cost of data storage are contributing to market growth. Increasing focus on data-driven decision-making and surging growth in advanced analytics & visualization are also enhancing the adoption of the data monetization market. However, increasing data structure complexity may limit the adoption of data monetization solutions. Security and privacy concerns related to data monetization solutions are also factors of concern for market growth. Moreover, the advancements in data monetization solutions and rising digitalization in emerging economies are expected to generate significant growth potential in the market.
KEY MARKET STATISTICS | |
---|---|
Base Year [2023] | USD 3.83 billion |
Estimated Year [2024] | USD 4.58 billion |
Forecast Year [2030] | USD 13.55 billion |
CAGR (%) | 19.75% |
Component: Increasing utilization of data monetization consulting services for business growth
In the data monetization market, consulting services primarily offer expert guidance, insights, and solutions that equip businesses to optimize their data generation, collection, and usage. The implementation and integration services ensure seamless assimilation of data analytics solutions into your existing infrastructure, ultimately facilitating a smooth transition to data-driven decision-making and operations. Support and maintenance services upkeep the holistic functioning of data monetization strategies, ensuring uninterrupted access to pertinent data and enabling optimized functioning of data-driven processes, thereby maximizing business efficiency and profitability. Data monetization tools serve as invaluable assets in extracting tangible value from raw, unprocessed data to unveil hidden trends that can influence business strategy and profitability.
Data Type: Surging utilization of product data for better data monetization
Customer data primarily provides insights into the behavior, preferences, and demographics of existing and potential customers. Detailed analytics based on customer data can catalyze personalized marketing strategies, enhance customer experience, and drive customer loyalty and sales. Financial data represents the monetary transactions conducted by a business, comprising income statements, balance sheets, cash flow statements, and tax returns, for evaluating economic trends, studying historical performances, and making future predictions. Product data encompasses information about a company's inventory, including product specifications, pricing, availability, and sales statistics. Supplier data incorporates information about a business's suppliers and their performance metrics. Effective analysis & monetization of supplier data help to establish better negotiating positions, improve supply chain efficiencies, and reduce potential risks.
Business Function: Enhancements in data monetization solutions for improvements sales and marketing operations
In the finance sector, data monetization is utilized towards predictive budgeting and forecasting by analyzing past financial data to predict revenue trends, potential risks, and growth opportunities effectively. Data monetization in operations helps organizations make data-driven decisions and strategies for better resource allocation, management of human resources, and cost-effectiveness. Sales and marketing teams leverage data monetization by targeting ads more effectively, understanding consumer behavior, predicting buying patterns, and personalizing campaigns. Organizations monetize supply chain data to optimize inventory levels, asset usage and enhance route efficiency to perform predictive analytics for inventory shortages and overstock scenarios, thereby reducing unnecessary expenditure.
Deployment Type: Enhancements in cloud deployment models
Data monetization in cloud deployment models capitalizes on the scalability, flexibility, and affordability of cloud resources. Organizations can institute a pay-as-you-grow model, enabling them to scale their storage requirements according to their data monetization efforts. Cloud deployment also supports real-time analytics, which is crucial in data monetization strategies. On-premises data monetization involves leveraging an organization's existing infrastructure for data collection, storage, and analysis, offering greater control over the data environment. The on-premises deployment has the ability to manage and monitor the data landscape closely, reducing the risk of data leakage and unauthorized access.
Organization Size: Significant adoption of data monetization solutions by small and medium-sized enterprises
Large enterprises are increasingly turning to data monetization to amplify their revenue streams and unlock new business opportunities. Large enterprises harness their data assets to develop new offerings for their customers and monetize their data directly by selling them to third-party entities to generate business growth potential. Small and medium-sized enterprises (SMEs) have less complex data ecosystems and fewer regulatory hurdles than large enterprises, which lends them greater agility in implementing data monetization strategies. SMEs typically focus their efforts on internal data monetization, uncovering actionable insights from their data to optimize business processes and drive efficiency.
Industry Vertical: Increasing adoption of data monetization solutions across industry verticals
Through data monetization solutions, financial institutions leverage client data to predict client behavior, improve risk management, create personalized banking experiences, and facilitate decision-making in insurance underwriting. Retail businesses can utilize data monetization tools to understand consumer behavior, preferences, and purchasing patterns. Energy companies can deploy data monetization strategies better to manage energy production, consumption, and distribution. Healthcare providers generally use patient data to anticipate health issues before they become critical and tailor indispensable treatments that result in better patient outcomes. IT companies monetize data to create new product offerings, enhance existing services, personalize software solutions, and deliver improved client experiences. Data monetization solutions help media and entertainment businesses understand audience preferences, consumption patterns, and engagement habits. Transportation and logistics companies can leverage data monetization strategies to improve route planning, vehicle maintenance, fleet management, and optimize logistics operations.
Regional Insights
In the Americas region, technological innovations and strong presence of key players particularly in the United States and Canada, has established a remarkable footprint in the data monetization market. Robust technological infrastructure, the prevalence of IoT devices, and a growing trend towards big data analytics significantly contribute to the market's growth in the Americas region. In the European region, the shift towards Industry 4.0 and the presence of a stringent regulatory landscape positively influence the data monetization market. Countries such as Germany, Italy, and France have higher adoption rates of AI and predictive analytics, augmenting the data monetization opportunities. The public sector's digital transformation initiatives, especially in the GCC countries, are serving as a significant growth catalyst for data monetization in the Middle-East and Africa region. Asia-Pacific stands as one of the fastest-growing markets for data monetization due to rapid digital transformation in emerging economies including India and China. Ambitious economic growth agendas, coupled with an increased focus on Industry 4.0 and pro-tech regulatory policies, in APAC countries are driving the region's data monetization market.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Data Monetization 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 Data Monetization 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 Data Monetization Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Adstra, LLC, Cisco Systems, Inc., Dawex Systems, Domo, Inc., Emu Analytics Ltd., Infosys Limited, International Business Machines Corporation, Microsoft Corporation, Narrative I/O, Inc., NetScout Systems, Inc., Optiva, Inc., Oracle Corporation, QlikTech International AB, Reltio, Inc., Revelate Data Monetization Corp., Salesforce, Inc., SAP SE, SAS Institute Inc., Sisense Inc., Tech Mahindra, ThoughtSpot, Inc., TIBCO Software Inc., and Virtusa Corporation.
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 Data Monetization Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Data Monetization Market?
3. What are the technology trends and regulatory frameworks in the Data Monetization Market?
4. What is the market share of the leading vendors in the Data Monetization Market?
5. Which modes and strategic moves are suitable for entering the Data Monetization Market?