How Deep Learning Can Help You Work Smarter, Not Harder

Marketers can free themselves of tedious manual work and scale investment dollars even further

These days, marketers and agencies using self-serve tools to buy and trade media are under a lot of pressure to deliver incredible results on smaller and smaller budgets. Manual optimization only compounds those difficulties—it takes forever, it is inconsistent and it is not scalable.

However, with deep learning, marketers can free themselves from most of the tedium of manual optimization and instead be able to handle more campaigns or focus their limited resources on higher-level strategic initiatives—in other words, work smarter, not harder.

Deep learning is less well-known than its compatriot terms “machine learning” and “artificial intelligence,” yet it is the most powerful tool in the AI arsenal and has made by far the largest difference in how we interact with computers since their inception.

The fact is, most of us already use deep learning on a daily basis without even knowing it. Every time you unlock your phone using facial recognition or ask Alexa to tell you the day’s weather, you rely on deep learning. Your car is likely equipped with features that use deep learning, such as automatic braking, self-parking or self-driving capabilities. The point is, deep learning has been proven to make our lives easier—so why not apply it to marketing?

It’s worth (and maximizes) every penny

We’re not talking about using deep learning to eliminate the need for human marketers, or replacing existing workers with machines. Rather, by relying on deep learning, marketers can augment their teams and use deep learning to offload work that is tedious, mind-numbing and time-consuming and instead focus their attention on more creative or strategic matters.

Case in point: Manually optimizing media buying strategy takes ages, requires constant retooling and produces inconsistent results. Marketers have neither the energy nor the computational ability to produce a perfectly optimized media buying plan—but deep learning does. A deep learning algorithm doesn’t need to eat, sleep or take showers; instead, it can keep humming along, 24-7, working to make sure that each dollar is being spent precisely as it should.

One of the reasons manual optimization is so difficult for people to do effectively is because it requires a lot of data analysis, which, without a background in data science, is difficult to do. The purpose of this analysis is to determine which audiences to target and the best ways of reaching them.

But without sophisticated tools, marketers are stuck with only a basic understanding of their customers and none of the advanced insights required to drive conversions at scale. Some manual tactics will always be easy and provide results, but they always max out before scaling to the entire market.

And it only gets better with time

Deep learning is able to scale and provide insights that can help inform other manual tactics in and out of the digital realm. By combing through customer data, deep learning algorithms can identify not only the types of consumers marketers should be targeting but also how best to convert those users in the most efficient way.

From there, they can make predictions about which individuals to pursue and which to leave alone and buy impressions based on which is most likely to produce a positive outcome (i.e., purchase). Best of all, because deep learning algorithms are self-learning and self-driving, they are able to automatically improve over time as they learn more about what causes people to convert, thus enabling both scale and improved efficiency.

Implementing deep learning within your organization might sound like a daunting task, but it doesn’t have to be. It might seem that companies with a data science team at their disposal are at an advantage, but deep learning has never been more accessible. Plug-and-play deep learning solutions are available from a number of marketing partners now, including custom algorithms built just for your specific marketing challenge and KPIs.

At a time when marketing budgets are under increased strain and organizations are still recovering from the effects of the pandemic, marketers and their agencies are feeling more pressure than ever to deliver. Instead of spending long days at the (virtual) office, it’s time for marketers to invest in the tools that will enable them to spend less time on grunt work (that does not even deliver consistent results) and more time on moving their brands forward.

With deep learning in hand, marketers are finally able to achieve true marketing optimization with a fraction of the effort.