LONDON--(BUSINESS WIRE)--SpendEdge has been monitoring the global automatic content recognition market and the market is poised to experience spend growth of more than USD 3 billion between 2019-2024 at a CAGR of nearly 24% during the forecast period. Request Free Sample Pages.
Read the 130-page research report with TOC and LOE on "The Global Automatic Content Recognition Market – Procurement Intelligence Report, Pricing Outlook in Geographies that include APAC, North America, South America, and MEA, top service providers, supplier selection and negotiation strategies, and insights into best practices to optimize procurement spend.”
Buyers are capitalizing on the popularity of the e-commerce industry to orchestrate their brands and to earn better customer engagement. To achieve these objectives, they are collaborating with online marketing service providers who have integrated automatic content recognition techniques to improve the response rate of their online advertising campaigns and to improve buyers’ ROI. This is propelling spend momentum in the automatic content recognition market. Most of the organizations are designing application portfolios integrated with automatic content recognition in a bid to improve their business process efficiency and strengthen relationships with customers.
Healthcare companies in North America are among the largest end-users as they are facing a pressing requirement to handle large amounts of real-time data. This is primarily driving spend growth in the automatic content recognition market in this region. APAC is home to the world's largest gaming market. The presence of a large number of media companies, advertisers, and gaming companies are creating an exponential demand for automatic recognition content in this region.
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The Top Automatic Content Recognition Service Providers Enlisted in this Report:
Substantial increase in technology expenses will propel service providers OPEX in this market. To compensate for this, they will increase their service charge which will have an inflationary impact on the overall price structure in the global automatic content recognition market. However, strategic cost-control initiatives, price forecasting techniques, and adequate technology adoption will aid automatic content recognition service providers to sustain their profit margins. Such service providers will have the liberty to offer service to buyers at competitive rates without hurting their profit margins. On this note, this report has listed the top automatic content recognition service providers, SLA agreement insights, and the selection and negotiation strategies that buyers must undertake to achieve optimal procurement in this market. Insights into some of the suppliers’ portfolio are given below:
Apple- It is known to engage in horizontal integration strategies by acquiring and collaborating with other specialized or full-service agencies to get access to the latest technologies, improve operations, enhance capabilities, and expand its automatic content recognition portfolio in various regions. In 2018, Apple acquired Shazam, one of the leading song identification apps. This acquisition has enabled Apple to enhance its services by developing products such as SIRI.
Kantar- The supply market is highly fragmented owing to the presence of a large number of tier-2 and tier-3 service providers. Among them, Kantar will gain prominence. Buyers are expected to exercise moderate bargaining power owing to the standardization of automatic content recognition services.
Nielsen Holdings Plc- Buyers, especially the media and marketing firms, must collaborate to include broadband-enabled features such as content personalization, dynamic advertising, and viewership measurement with the broadcast content.
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Some of the key topics covered in this report are:
- Automatic content recognition market spend segmentation by region
- Automatic content recognition supply market analysis
- Regional spend opportunity for automatic content recognition service providers
- Automatic content recognition service providers cost structure
- Total cost of ownership analysis in the automatic content recognition market
- Automatic content recognition pricing models analysis
- Category management objectives
- Cost saving opportunities in the automatic content recognition market
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