The Impact of AI and Machine Learning in Marketing

In the new world of artificial intelligence and machine learning, predictive content is digital content that automatically assembles itself in real-time for each impression with deep and precise predictive intelligence. In marketing and consumer engagement, this is as close to personalization at scale that we, as marketers, have to date.

Up until now, many have used the word predictive when in fact it has been truly an adaptive capability. Adaptive platforms are those that use static rules written by the marketer in advance. Adaptive can make in-the-moment content decisions, but it is not continuous machine learning.

Predictive intelligence, on the other hand, is automatically rendered by technology machine learning in real-time. It does this by observing subtle trends in engagement, removing the need for A/B testing, and re-learning each time the consumer engages to deliver precise and personal communication.

Predictive AI Machine Learning Highlights:

Real-time prediction: Makes in-the-moment content decisions.

Real-time data ingestion: Incorporates performance data as it streams in.

Real-time model training: Incorporates performance data.

Continuous algorithm evaluation and selection: Automatically adapts to your data point, brand, content, and the unique patterns that exist among them.

Test vs. control framework: Eliminates the need for any A/B testing and enables “continuous listening” over time.

The results and lift of campaigns done using predictive AI machine learning is significant, up to 40% on average. And the insight in the data helps to craft content strategy and creative development as well as provide hyper target audience segmentation for the brands.

This predictive AI impression-based learning can happen on any device and in any channel including email, web, mobile, or video. Using AI predictive intelligence in video is a breakthrough. There has been very little marketers can do with video to help personalize it, but that has now changed.

Four ways you can alter or create video to render in real time and personalize it include:

1. Personalized Video

  • Unique for each individual viewer
  • Built with pre-existing data points

2. Real-Time Video

  • Built and rendered at the instant the video is viewed
  • Real-time information

3. Contextual Video

  • Built and rendered at the instant the video is viewed
  • Adapt to the real-time context of the viewer

4. Interactive Video

  • Interactive elements overlaid on the video as it is being viewed

The personalization in video is a very exciting development and consumers are engaging and re-watching at astonishing rates that we have not seen before in video. Personalization at scale is here, and learning and piloting AI machine learning in all channels is essential.

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