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Leveraging Machine Learning to Drive Marketing
Today’s most trending phenomena amongst the marketers and the consumers of a brand are personalization. The demand for personalization has already reached its peak and isn’t likely to go away anytime soon. Moreover, the growing complexities of the use of internet on consumer behavior, fast fashion, and overconsumption of goods often times is making the end-point customers wary. With this in mind, Google has unveiled a set of machine learning tools that would enable marketers to provide targeted advertisements to prospective end-consumers and eliminate the problem of excessive options from consumer feed. This will eventually help consumers curtail time spend on researching and increase investment in the different industry.
Google will enable marketers to leverage machine learning tools to create ad formats that use and match creative assets in real-time to provide consumers with the best ad experience for each search query. The tool also enables marketers to optimize ad performance in YouTube by automatically adjusting the bids at auction times. Machine learning can also be implemented to improve visits to physical stores by producing and showcasing area specific ads across the Google platform. Marketers can also use these machine learning tools to promote their criteria and goals through smart advertisement campaigns of a particular brand.
Research conducted by Google has found that marketers using machine learning tools has witnessed a 15 percent increase in customer views. Machine learning can be used to drive personalization strategy, create creative contents on brand features to appeal to the consumers, and promote new trends across the global platform. In fact, data from Google’s silos can also be analyzed and leveraged to create contents that are in line with a group or community.
Perhaps it’s the dawn of new age marketing, businesses and brands no longer have to mass advertise and waste billions of dollars each year on radio, television, or newspaper hoping that at least someone’s attention would be attracted by it. Now, marketers can target a specific audience, analyze which type of content is attracting more consumer attention and hence optimizing such factors for the best results. The bleeding-age technologies such as AI, machine learning, and data analysis are creating an unprecedented impact on the ad industry.