How can advertisers leverage machine learning for personalized advertising?

by David Hunt Data Geek and Analytics Fanatic

The hype around machine learning in business and marketing is enormous right now. Machine Learning refers to a technology that enables computers to make real-time decisions based on previously stored knowledge or information. The advertising industry in particular has been very ready in adopting machine learning technologies.

With advancements in machine learning, it is now possible to offer much targeted personalization of advertisements and automate activities with the help of AI-driven solutions, which in turn can improve the ROI of marketing. Machine learning also provides a great facility for advertisers to make data-driven decisions.

Some of the most popular utilities of machine learning in digital advertising are -

1.       Boost performance of digital advertising

2.       Automate manual efforts thereby reducing costs.

3.       Get better insights by finding hidden trends and correlations in datasets of previously unmanageable sizes

4.       Uncover new customer insights by previously stored information

5.       Predictive advertising and personalized communication thereby increasing conversion rates


Machine learning can boost ad performance

Managing and tracking campaigns and digital advertising analytics is a very manual and tiresome process. Machine learning can improve this by automating a lot of these processes thus reducing human intervention and reducing the chances of errors.  A campaign’s performance can be attributed to a lot of different factors. The machine learning algorithm can give you insights into these factors are and how to manage them to deliver a profitable campaign and what more precisely what exact parameters to set or optimize. As more and more data is injected into this machine learning model, the accuracy in output improves thereby boosting the campaign’s performance.

Machine learning helps to improve ad creatives

A lot of a campaign’s performance depends on the advertising copies and creatives used. Fonts, colors, sizes etc. all contribute to creating a great creative and can positively impact the output. Machine learning algorithms can study previously used creatives in order to predict what will work best for the future campaigns. With machine learning, we can now analyse user habits, preferences, personality traits etc. to craft a campaign using the best possible creatives that will be impactful.

Segmenting customer groups more effectively

Customer segmentation in marketing is often an underutilized subject. All customers respond differently to any set of online ads. Targeting has far greater an effect on the ROI than the ad copies themselves. Marketers find it challenging to fine-tune their targeting. Complications arise because customer behaviour is not exactly predictable and often varies from what was planned earlier.

Machine learning algorithms can identify the customer groups that convert the best. This data can be used to identify the target criteria for a digital campaign, as well as the customer demographics that correlate with the highest conversion rate. Machine learning technology can look at various customer segments to see how they respond to different content. They can create custom content for users depending on their location, age, and income thresholds.

Machine learning in personalized ads

Many companies find it difficult to effectively manage the enormous volumes of user data they gather. Data scientists are hired to draw correlations and organize all these data sets. The efforts are still manual and take up lot of time and effort. Machine learning empowers advertisers to automatically build campaigns where creatives and targeting are precisely designed for personalized experience. In contextual advertising, a web-page's content is analysed so that one could run ads that match with the context and the user’s interest. Machine learning can be used in such a situation to create user personas based on the emotional intent of the web content and thus ensuring the right audience is matched to these pages.

Machine learning algorithms can curate real-time content to help recover from negative brand value and sentiments. They can also use more aggressive marketing copy for customers that have highly favorable brand perspectives. Personalization is the key to deriving value out of digital marketing. Machine learning is the foundation of it.

It is however to be noted that machine learning is not a replacement for creative thinking that only humans can achieve. Machine learning can assist in automating most the complex procedures and give them the leverage to conduct creatively. AI is also useful to automate more mundane tasks, which helps marketers conserve their cognitive resources to focus on more important challenges.

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About David Hunt Innovator   Data Geek and Analytics Fanatic

10 connections, 0 recommendations, 53 honor points.
Joined APSense since, March 14th, 2020, From New York City, United States.

Created on Apr 11th 2020 06:08. Viewed 360 times.


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