Machine Learning in Programmatic Marketing and Advertising

Machine learning is a buzzword you have probably heard a lot lately, especially when it comes to programmatic advertising. But what exactly is machine learning and how can it help your business? This blog post discusses the basics of machine learning and programmatic advertisers use it to improve their campaigns.

What is Machine Learning?

Machine learning is a subset of artificial intelligence. It enables computers to learn from data without being explicitly programmed. In other words, machine learning allows computers to “learn” on their own by using algorithms. This analyzes data and identifies patterns. The process of “learning” can help businesses improve their marketing campaigns. Ultimately, it allows them to better understand customer behavior and target ads more effectively.

Defining Machine Learning in Programmatic Advertising

One way programmatic advertisers utilize machine learning is through the use of predictive analytics. Predictive analytics is a type of machine learning using historical data to predict future outcomes. For example, predictive analytics determines which customers are most likely to purchase a product or service. This information can help develop targeted ads that are more effective at reaching those customers.

Additionally, programmatic advertisers use machine learning by using algorithms to analyze a customer’s behavior on social media platforms, such as Facebook and Twitter. The data collected from these sites is then used for market research purposes or even personalized marketing materials. So, they match each user’s interests (and thus increase conversions).

Search engine optimization (SEO) also applies machine learning. It allows websites to better understand what people are searching for when they enter queries into Google or other search engines. For example, if someone searches “weather forecast,” ads related to weather forecasts will likely be on display on the side of the page. Why? Because machine learning algorithms have determined these types of products are likely what they’re looking for.

Most importantly, programmatic advertisers use machine learning to expand their ideal customers to a full national scale. First-party data as always been better than third-party data. Cookie deprecation gave advertisers the push they needed to see it. Take your seed data (aka a CSV file of your best customers) upload it into Omni IQ. It will find people like your best customers and expand those profiles with machine learning.

How Machine Learning Applies to Programmatic Advertising

We’ve defined and established the various uses for machine learning. Here’s how it specifically relates to programmatic advertising. Machine learning is used in programmatic advertising by analyzing customer data from different sources and identifying patterns among them (e.g., purchase history). This allows businesses to better understand their customers so that they can improve their campaigns based on insights gleaned from this type of analysis. For example, a clothing retailer might analyze its customer database to see which items were purchased together or at similar times during previous years. Then, those insights become useful when creating promotions next year around holidays like Christmas or Thanksgiving Day sales events.

Furthermore, here’s another example of programmatic advertising uses machine learning. A business wants to improve its campaign performance by targeting ads to potential customers who are likely to purchase its products. To do this, the business uses machine learning algorithms to analyze data from different sources (e.g., past customer purchases, website traffic, social media posts) and identify patterns among them. This analysis allows the business to better understand which customers are most likely to buy its products. Then, they can target those individuals with targeted ads. As a result, the business’s campaign performance improves as it reaches more of the right people with its advertising messages.

How Machine Learning Increases Efficiency for Marketers

Machine learning allows computers to “learn” how people behave on their own without any human input necessary. It’s a powerful tool for marketers to increase efficiency and save time and resources. Marketers no longer need teams of analysts working around-the-clock just so they can analyze customer data from different sources and identify patterns among them. Machine learning algorithms do all this work automatically.

In other words, machine learning allows computers to learn on their own by using algorithms to analyze data and identify patterns. This process of learning helps businesses understand customer behavior better, so they can target ads more effectively.

Many businesses are now using machine learning to improve their marketing campaigns. In fact, some companies have even created entire departments dedicated solely to the process of analyzing customer data for insights. This helps them better understand consumer behavior (and thus increase conversions) – all thanks in part due to advances in technology like artificial intelligence (AI).

Another way programmatic advertising leverages machine learning is via social media listening. By analyzing data from social media posts, companies can understand the conversations people are having about their brand and products. This information generates targeted ads that speak to what customers are interested in.

In conclusion, machine learning is a powerful tool that programmatic advertisers use to improve campaign performance. By using machine learning algorithms to analyze data from different sources, businesses obtain valuable insights to help improve their marketing campaigns.