Company envisions and integrates machine learning into back-end processes and marketing functions basic. When enough data is available, the solution automatically chooses an attribution based on many signals. Machine learning: less drudgery, more strategy Asked about the role of machine learning and the inherent tension between automation and control, Dischler said, "Generally, we want to use machine learning to make advertisers' jobs easier." Advertisers can spend less time in the drudgery of manually setting bids and thinking strategically: what is the most effective message? What are the most interesting customer segments? How do we
support new product lines and initiatives? How to improve the website? From an employment perspective, search marketers will be able to move from transactional jewelry retouching service value to customer lifetime value more quickly. "Many companies couldn't get there because they're still so caught up in the mechanics of large-scale online advertising." The industry has been discussing and experimenting with the impact of automation for several years now, but the rate of
ubiquity of machine learning in search advertising has accelerated rapidly over the past year. For marketers who used to have a lot of manual controls and were the guinea pigs of machine learning, trusting the system and the algorithms can be difficult. Don't expect to see how the sausage is made "We try to have controls where possible and transparency in reporting," Dischler explained, "but not everything can be reported. With deep neural networks, you can't explain everything that happens.