Post by wekeve7933 on Dec 5, 2023 4:04:07 GMT -5
In an era of real-time advertising and content personalization, an IDC / Criteo study reveals to what extent the process, still largely manual, of advertising creation and design is called upon to integrate an increasing share of machine learning via AI… The online advertising sector is still a young industry, having only been ten years old.
During this period, it has undergone so many Phone Number changes that it is now unrecognizable. Real-time (RTB) selling and buying of advertising space has transformed the industry, and indeed the entire advertising supply chain. AI-based creations? Nearly 60% of marketers plan to use “significantly more” or “more” online advertising by 2020, which is a rapidly growing investment area for businesses. Advertising personalization is a complex operation whose effectiveness relies on real-time responsiveness to customer purchasing behavior, “in the moment” of the act of reflection and purchase.
In reality, the speed and dexterity required to implement this type of real-time personalization remains the preserve of machines. As a result, marketers are increasingly moving away from creative content produced by humans in favor of content produced by machines. They plan to entrust machines with automating the production of creative content, through online advertising aimed at consumers. 64% of marketers believe that optimizing message targeting and real-time personalization of advertising inserts represent key tasks for which machines will offer operational advantages by 2020. In this context, creative staff will continue to design the source content, while machine learning technologies will combine the variables to deliver the right content at the right time for each potential customer.
More and more AI despite some fears This interest in automation is reflected in the market trends identified by IDC. It forecasts that spending on AI software for marketing and related activities will grow at an average annual growth rate (CAGR) of 54% worldwide, from nearly $360 million in 2016 to more two billion dollars in 2020 . Although marketers recognize the value and benefits of machine learning for personalization, few are currently using it. This is due to a lack of internal machine learning skills, as well as a lack of confidence in the technology's ability to provide an adequate level of customer data privacy and brand control. Not respecting brand identity is one of the risks of machine learning identified by some interviewees. They admit to “ doubting their ability to manage and control their brand and their creation ”, which constitutes one of the main obstacles limiting the adoption of machine learning. IDC believes, however, that brand concerns will gradually disappear as machine learning is adopted by online advertising companies. The research firm predicts that machine learning will be democratized at all levels of the ad technology chain by 2022.
During this period, it has undergone so many Phone Number changes that it is now unrecognizable. Real-time (RTB) selling and buying of advertising space has transformed the industry, and indeed the entire advertising supply chain. AI-based creations? Nearly 60% of marketers plan to use “significantly more” or “more” online advertising by 2020, which is a rapidly growing investment area for businesses. Advertising personalization is a complex operation whose effectiveness relies on real-time responsiveness to customer purchasing behavior, “in the moment” of the act of reflection and purchase.
In reality, the speed and dexterity required to implement this type of real-time personalization remains the preserve of machines. As a result, marketers are increasingly moving away from creative content produced by humans in favor of content produced by machines. They plan to entrust machines with automating the production of creative content, through online advertising aimed at consumers. 64% of marketers believe that optimizing message targeting and real-time personalization of advertising inserts represent key tasks for which machines will offer operational advantages by 2020. In this context, creative staff will continue to design the source content, while machine learning technologies will combine the variables to deliver the right content at the right time for each potential customer.
More and more AI despite some fears This interest in automation is reflected in the market trends identified by IDC. It forecasts that spending on AI software for marketing and related activities will grow at an average annual growth rate (CAGR) of 54% worldwide, from nearly $360 million in 2016 to more two billion dollars in 2020 . Although marketers recognize the value and benefits of machine learning for personalization, few are currently using it. This is due to a lack of internal machine learning skills, as well as a lack of confidence in the technology's ability to provide an adequate level of customer data privacy and brand control. Not respecting brand identity is one of the risks of machine learning identified by some interviewees. They admit to “ doubting their ability to manage and control their brand and their creation ”, which constitutes one of the main obstacles limiting the adoption of machine learning. IDC believes, however, that brand concerns will gradually disappear as machine learning is adopted by online advertising companies. The research firm predicts that machine learning will be democratized at all levels of the ad technology chain by 2022.