Artificial Intelligence: Use Cases for Content Personalization

Jul 10, 2018

Artificial Intelligence: Use Cases for Content Personalization

Artificial intelligence (AI) and machine learning are giving marketers the ability to scale their content marketing strategies. For example, programs that typically require many hours on manual operational tasks can now be optimized via machine learning to increase frequency, effectiveness and targeting.

Research finds that more and more marketers are confident that machine learning can personalize content to individual interests and improve the customer experience. For this reason, it’s clear this technology will become the standard best practice for organizations trying to scale and evolve their personalization programs to meet the demands of the modern consumer.

Here are a few ways that machine learning AI technologies can enhance the customer experience to enable content personalization at scale.

1. Optimize Content Delivery

One misconception many have about marketing and AI is that AI is responsible for content creation. For some organizations, this may be true. But where AI really shines is in content delivery. In order to stand out in a noisy digital marketplace, brands have to focus on reaching the right consumers at the right time through the right channel and with the right content. Sound like a tall order? Not when AI and machine learning are part of the equation. Today’s AI-based content marketing platforms make personalized content delivery possible, and at scale.

These tools are able to target consumers based on their interests and preferences and then recommend the most personally relevant content to each consumer, leading to higher engagement. By delivering personalized website experiences, OneSpot customers have even seen deeper engagement, increased content consumption and more quantifiable business results.

From displaying individually targeted content through websites to delivering seamless experiences for consumers across mobile and desktop channels, AI optimized the analysis of available content and ensures the most optimal piece is selected and surfaced so that brands can reach potential customers with experiences that are most likely to drive results.

2. Boost Email Efficiency

Consumers receive hundreds of millions of emails every day. Only the ones that are intelligently delivered get opened and acted upon. As marketers, we rely on email automation to time, test and segment our messages and enhance email delivery. And this is where AI can help to optimize operational efforts and greatly improve performance.

For starters, machine learning can easily analyze millions of data points to more efficiently handle the executional tasks associated with running email personalization programs. This includes tasks such as content selection, content development and list building. Our research shows that most marketing teams spend more than 36 hours per week on these manual email segmentation efforts. AI can take over these types of manual processes, making the processes more efficient and freeing up man-power to focus on strategic initiatives.

3. Provide Individualized Content Experiences

Deep content analytics go beyond traditional website metrics like pageviews and sessions, and focus on the metrics that provide real insight on engagement, like Active Content Users.

Machine learning algorithms analyze this data at scale and in real time, based on in-the-moment content engagement patterns. AI-based personalization tools use those insights to automate cross-channel content distribution to individual users based on their behaviors, preferences and interests.

To learn more about the benefits of AI and machine learning on content personalization and how you can leverage this technology to create deeply engaging customer experiences, contact us. Or download our guide: How to Master Individualization to Delight Your Customers for more information about the benefits of individualization.

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