Madison Avenue Meets Wall Street: How Marketing is Imitating Finance
The financial industry has found great success using algorithms to manage the bulk of its everyday trading operations. The marketing industry is quickly learning to do the same.
The floor of the New York Stock Exchange is still an important hub of global commerce, but in recent decades, the importance of the floor itself has become more symbolic than anything else. Many of the world’s most important transactions happen at stock exchanges like the NYSE, but the volume of them that actually take place on their floors has sharply declined. Instead, the great majority of trading these days is done at a rapid pace by a series of advanced algorithms.
The New Finance
Like healthcare, education, and software development, finance has been fundamentally redefined by the steady maturation of computer algorithms, especially those falling under the “artificial intelligence” (AI) umbrella.
Finance relies so heavily on such a wide variety of variables that the introduction of algorithmic trading was all but inevitable. Not only can a computer pick up on valuable micro-trends and base trading decisions on them in a fraction of a second, but it can also execute a predefined trading strategy with a kind of cold, objective calculus that human traders simply can’t match.
Valerie Bogard, an equity analyst at research and consulting firm Tabb Group, estimates that “[modern trading] is 90% algorithmic, but there is not a great way to quantify that.” Other insiders grant humans a slightly more generous role — QuantConnect claims that humans execute around 25% of all trades — but the general consensus is clear: the financial markets now depend on these algorithms to function.
Aside from their ability to conduct trades at superhuman speeds, a large part of the reason why algorithms have managed to become so prevalent so quickly is their flexibility. As QuantConnect summarizes, “Investment managers may use algorithms to analyze trades and buy or sell manually based on the algorithm’s suggestions, or may allow the algorithm to trade automatically, intervening on occasion.” In other words, instead of threatening to replace finance professionals, algorithms have proven to be a remarkably powerful tool with which such professionals can perfect — and expand — their operations.
How the Marketing Sector Can Capitalize
Given its current situation, the modern marketing industry is primed for an algorithmic revolution mirroring the one finance has already undergone.
Marketers took a tentative step toward automated operations when it embraced programmatic media buying. The prospect of automating the purchase of digital ad space was so enticing that programmatic ad spending in the United States exceeded $10 billion in 2014, accounting for roughly 63% of all digital display advertising. But as marketers began to develop expertise in this new approach, it became clear that the increased efficiency delivered by automated buying platforms didn’t come without its drawbacks.
From their susceptibility to bot fraud to their tendency to make it difficult for marketers to intervene in their processes once deployed, programmatic platforms have often proven to be more trouble than they’re worth. That’s especially true for smaller companies that might not have the expansive marketing departments needed to manage programmatic buying effectively.
Luckily, artificial intelligence tools like Albert™, the world’s first fully-autonomous marketing platform, offer an alternative to programmatic media buying, one that’s more in-line with the AI-driven algorithms that have served finance institutions so well.
Like many trading algorithms, Albert uses deep learning and predictive analytics to find “hidden” patterns within a company’s data that empower the company to more accurately target the right audiences. What’s more, Albert not only uncovers new and more nuanced marketing insights, he acts upon them as well, conducting thousands of micro-campaigns in order to determine the ideal combination of channel, messaging, and timing.
In an ideal situation, a marketing team will direct its energies toward uniquely human tasks like the crafting of creative materials and the outlining of overall company strategy and let the AI system handle the granular details of everyday marketing operations. Once marketers manage to strike the proper collaborative balance with their AI platforms, they’ll be well-positioned to enjoy the kind of efficiency that characterizes finance today.