Consumers are bombarded with thousands of advertising messages every day, both online and offline. With more and more people using adblocking, it is clear that we are looking for ways to shield us from advertising. This is primarily about the fact that the advertising we encounter is of no relevance. Here’s how marketers can increase the efficiency of their ads by using Deep Learning.
In this article you will learn:
- What is Deep Learning technology
- Why and how is Deep Learning being used in the marketing world
- How can the usage of Deep Learning algorithms boost your marketing strategy
- What are other Deep Learning benefits
Table of Contents:
- What is Deep Learning?
- Why should Deep Learning algorithms be used in digital marketing?
- Advantages of Deep Learning technology in marketing
- What can you expect in the future?
What is Deep Learning?
Deep Learning is a subcategory of a much broader concept – machine learning. It involves the construction and use of neural networks in such a way that they mimic the human brain – i.e. that they learn with each repetition of a specific task and as a result generate even more satisfactory results.
The advantage of computers over the human mind is undoubtedly the speed and precision of operation. Deep Learning allows for huge volumes of data to be processed in a very short time and proper decisions to be made on their basis. This opens up extremely wide possibilities in many business areas, including marketing. Already today, artificial intelligence in various forms supports decision-making engines of many programs and applications, thanks to which the implementation of the marketing strategy is largely automated, and its results are usually much more satisfying.
How does Deep Learning use modern tools and programs that support marketing activities? Artificial intelligence is used today, for example, in:
- automatic creation of a wide variety of content;
- bidding for favorable advertising rates;
- personalizing marketing activities;
- accurately analyzing user behavior online;
- create advanced recommendation systems
- designing chatbots;
- speech recognition and natural language processing (NLP).
The cited examples of using Deep Learning in the world of marketing clearly prove that with the help of technology it is possible today to take marketing activities and the manner of marketing strategy implementation to a whole new level. Artificial intelligence makes it possible to control data collected by an organization, process it in an extremely short period of time and draw the right conclusions on its basis.
This is an effective opportunity not only to achieve better results, but also to significantly reduce costs. Today, technology is able to replace marketers in many of their daily duties and perform their previous work much faster and more precisely. Freed from repetitive tasks, professionals can thus focus on more creative and demanding aspects of their work to make the most of the opportunities that modern technology brings.
Good to know: The Evolution of AI Applications
Why should Deep Learning algorithms be used in digital marketing?
Digital marketing has reached a point where the purpose of advertising often has the opposite effect on the recipient. A clear example of this is that the use of adblocking has increased in recent years, mainly on mobile devices. At the same time, individualization has become a growing trend. Consumers want customized offers that fit their preferences. It is all about getting the right message to the right person at the right time. With the help of Deep Learning, your marketing strategy can improve the efficiency with which you generate customer interest and establish contact with your potential customers.
Advantages of Deep Learning technology in marketing
Harnessing modern technology and its use in the area of marketing brings a number of significant benefits, which translate directly into the effectiveness of the marketing strategy and, consequently, into financial results.
What is the reason for the high effectiveness of Deep Learning in marketing?
There are two problems with retargeting today: what to offer and how to display it. Advertisers, in various ways, try to adapt the advertising message so that it feels personal and attractive to the customer. Unlike machine learning, which aims to develop a machine’s ability to understand and handle large amounts of data, Deep Learning is an artificial network where the algorithms work in the same way as when the human brain’s neurons communicate with each other. When you use Deep Learning in e-commerce, it learns from experience, resulting in a faster and more accurate identification of potential purchases. The effectiveness of recommendations increases by up to 41 percent compared to campaigns that do not use Deep Learning.
Exposing the hidden
Deep Learning in retargeting has not only made it possible to analyze basic user behaviors, such as which products or product categories are visited but also other hidden data. With Deep Learning, it is possible to analyze the visit time on products and the sequence of visited subpages in a store. Using data, machines interpret exactly what users did at the store and thereby predict their actual purchase intentions. It is possible to determine which products users are most interested in, and thus, send them customized offers.
With all this data, the next step is deciding how to present an offer in an ad, and in what order. Deep Learning algorithms analyze offers and how attractive they are from a user’s perspective. Deep Learning technology is much more sophisticated than classic retargeting, as the products displayed on a banner are more personalized. This approach makes it possible to implement a rule where there is otherwise no clear pattern for a particular group of users. The algorithms understand each user on a deeper level; they look for the best deals, and the order in which the offers should appear on the ads for the users.
Our behavior profiles are constantly changing. Deep Learning can build a real-time behavioral profile and adjust what is presented on a banner every time an ad is displayed. Algorithms determine what should be shown on each banner, adjusting the contents based on a customer’s responses to previous offers. Thanks to powerful algorithms and constant analysis, Deep Learning can rebuild user behavior profiles in real time.
What can you expect in the future?
The dynamic development of technology, as well as great interest in the subject of artificial intelligence among the world’s largest corporations, allow us to assume that the possibilities of using Deep Learning in everyday marketing activities will grow from year to year.
This works perfectly well wherever decisions are made on the basis of data, therefore it is expected that the algorithms will help marketers plan and deliver their campaigns even more. This is important especially in the context of the decision to retire third-party cookies by major browsers, which in result makes delivering personalized advertising more challenging than ever before. With that being said, It is necessary to choose a partner who understands cookieless well and has a technology that is designed with user privacy in mind.
If you have any questions, comments or issues, or you’re interested in meeting with us, please get in touch.