Macon Company (CEO Lee Hwa-jin), a digital comprehensive advertising agency, has launched a solution called “MARS 2.0,” a influencer matching system based on AI and big data.

Macon Company’s “MARS 2.0” is an upgraded version of the influencer Matching System (MARS), which was patented in 2019, and is a solution that enables more precise influencer matching by adding YouTube video analysis results applying AI technology and big data.

Currently, domestic and foreign influencer marketing markets are rapidly growing every year. In fact, according to the release of the Global Market Research Company Market Insight Report, it is estimated that it will grow 33.4% annually from 2022 to 2028, and the market size will reach $143.1 billion.

Naver, Korea’s leading portal site, also announced that it will establish a new influencer search function from 2020 and expand to larger advertising areas than brand DA advertisements in the future.

In line with this global trend, MARS 2.0 upgrades existing systems and analyzes YouTube videos individually to provide numerical data values that are suitable for the brand’s marketing activities. Most of the common solutions currently used are analyzing the basic values provided by the platform, such as the title of the video, tags, and comments.

Macon’s MARS 2.0 uses AI and big data to convert voice data in video content into text, classify it into related words, and provide numerical results, so it can establish a marketing strategy more precisely. Through this, indiscriminate influencer marketing costs can be reduced and more accurate advertisements can be measured efficiently.

Macon Company plans to expand the scope of analysis of influencer matching systems using AI. Following the “context analysis and digitization algorithm using AI,” which has already obtained the first patent, a second related patent is also being applied. In the future, it plans to develop a solution that analyzes not only voice and conversation but also all major components of images such as people, music, and color, and use it for data-based video communication as well as influencer matching optimized for consumer characteristics.

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