The document discusses how machine learning is changing the modern advertising industry. It provides 5 examples of how ML is impacting advertising: 1) generating valuable insights from data, 2) improving ad creatives, 3) increasing contextual relevance, 4) better targeting customer segments, and 5) boosting conversions. ML allows analysis of large datasets to personalize ads and optimize campaigns in a way not previously possible.

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 Machine Learning (https://www.usmsystems.com/category/machine-learning/)
5 Examples That Show How Machine
Learning is Changing Modern Advertising
Industry
(https://www.usmsystems.com/ ve-examples-that-show-how-machine-learning-is-
changing-modern-advertising-industry/)
 November 6, 2019  usmsys (https://www.usmsystems.com/author/usmsys/)
The current advertising industry continues to adopt advanced technologies. Moreover, a signi cant part
of Arti cial Intelligence (AI) called Machine Learning (ML) is on-demand in this modern advertising
industry.

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ML is transforming the way industries collect, process, and analyze the data. It is o ering multiple
bene ts to digital marketing channels. In this article, we try to capture how ML will change digital
marketing.
What is Machine Learning?
ML is a major part of Arti cial Intelligence. ML techniques allow systems to learn from the given data
and improve from the previous experience without programming explicitly.
How ML Is Used In Advertising?
ML in digital advertising is a hot topic in the marketing industry. It is changing the way how an ad
technology collects more data and processes it for improving tasks.
ML technology can easily learn from given data and analyze related patterns to hit the targeted
audience. Using ML algorithms, the users can analyze customer behavior patterns and segment the
targeted audience, etc. Same like a human, the advanced ML technology handles more data, processes
securely, and gives accurate insights and predictions.
The Difference Between ML and AI
Many of us have a small doubt that is AI and ML are the same in features and capabilities?
No. ML use data and learn from it to improve assigned tasks. AI is a broader eld. It uses multiple
advanced technologies that can perform tasks with human intelligence. Thus, ML is an application of AI,
but not the same as AI.
Why Machine Learning?
Nowadays, every business is modernizing with AI and ML. However, if data is more, the complexity to
manage it securely will also be increased. For instance, a vast amount of data stored on the cloud may
open up new opportunities. But, on the other side, it may pose a few severe complexities to manage
such vast data. Due to not much aware of AI and ML, unfortunately, most of the companies are wasting
their time and money on traditional methods.

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According to the international market reports, the data which is being stored on the cloud is almost
unused. The below gure depicts the primary reasons behind this scenario:
In the above picture, we can understand that a lack of intelligent tools to collect and process data is a
major reason for data goes unused. This case is not only for the advertising industry, but it is also for all
industries who are dependent on data.
Well, now we’ll look the ve bene ts of machine learning in advertising, if the data is properly used:
1. Capitalize On Valuable Insights
If you’re an expert in advertising, so you’ll run ads using the targeted data. But the problem is the way of
nding the data is not right!
You may want to use and evaluate the data linked with your o er. Thus, to meet this, you might require
the most prioritized data to run a successful ad campaign. But, your budget means a lot to adopt
advanced advertising tools.
Due to less advertising, you may lose a few targeted audiences. For instance, if you’re promoting a video
game, then probably you target young and middle-aged people. And, you’ll not consider grandparents.
These types of assumptions may a ect your revenue.

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Here, ML plays a vital role. Machine learning models (/application-development/machine-learning-
solutions-services/) nd new revenue opportunities. It limits the budget and workforce costs. Due to this
reason, ML algorithms can easily process data sets at low costs and time. Machine learning technologies
best useful for generating more revenue opportunities through digital ads. ML solutions provide various
insights into the collected data. These insights might include audience analysis, their search patterns,
and also help to frame business strategies.
2. Improve Ad Creative
Do you agree that creative ads attract more audiences?
I hope, over half of the crowd agreed on the above sentence!
Well, the target audience will respond to creative ads. And, remember that the audience will not spend
much time on your ads and switch to di erent media’s. Call-to-action, internal links might attract your
audience and grab more attention to your services.
Many people think that ML algorithms can only process quantitative data, but this is not true.
Advancements in this AI application are still growing. According to the researchers, using ML can greatly
impact the overall performance of the marketing campaign. Predictive analytics techniques help to
make your campaign more creative.
USM meets your marketing needs. We develop AI & ML-powered mobile applications (/marketing-
sales/). These machine learning models analyze visual media and nd creative techniques to improve
sales.
Are you in plans of investing in AI & ML? Contact USM Now! (/contact-us/)
3. Augment Contextual Relevance
It’s a fact that innovative ad is always the best way to generate an immense response from the targeted
audience. Before this, the marketing teams have to nd the right platform and the right audience at the
right time. Here, ML comes into the picture.
Rather than depending only on the target audience data, ML models are used to process on-page data.
They can do any task like a human.

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With developments in ML, the machines are now capable enough to identify and understand the user
requirements. For instance, they can categorize the user opinions/queries expressed in a text form. In
addition, ML-based machines can also respond to emotions. This will be done using deep learning
techniques.
Similarly, deep learning advancements allow systems to process images and videos. A combination of
AI, ML, and deep learning helps advertisers bring innovations into their approaches and to do a few
amazing things.
4. Target More Defined Segments
The goal of every advertiser is to segment the audience based on their search. The deep analysis of their
search allows an advertiser to provide increased personalization and satisfaction.
But, if you want to provide personalized services, you require a large amount of data to start with. Then,
the implementation of ML algorithms helps to transform raw data into something useful.
ML techniques help to narrow your target customers and achieve fruitful results through digital
advertising.
5. Boost conversions
Advertisers always want better applications for trending technologies. So, ML-powered chatbots, image
processing, and voice recognition are the best t for improving sales. Machine learning will have a great
impact on an ad campaign in the future. ML models improve ad creativity, bidding strategies, and
personalization. Thus, invest in ML and remain competitive in this digital world.
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