You can rely on data science to analyze user behavior, preferences, feedback, and characteristics to predict behavior and deliver unique, personalized experiences. This helps you increase engagement and offer dynamic, one-to-one touchpoints with ease.
While AI personalization can offer better targeting and conversion-rate optimization opportunities, marketers have seen challenges with adopting data science because it’s so complicated.
Leadership hesitant to give up control.
Lack of functionality control.
Fear of automation complexity.
Lack of development expertise.
The benefits of AI personalization extend beyond workflow efficiencies. You can achieve gains in several key areas.
Machine-learning algorithms are more suited to optimize content accurately and swiftly at a scale that human analysis and decisioning can’t match.
By leaning on AI personalization to understand audiences better, you minimize risks due to biased or flawed decision-making.
AI personalization leads to more relevant content being delivered as real-time data informs user experiences. By combining data from first-, second-, and third-party sources, machine learning engines can improve relevancy faster.
Personalization activities improve investment returns, lift cross-sell and upsell results, and generate higher revenues than non-personalized campaigns.
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“Increasing the relevance of the customer experience, that was always the main goal. To have a more relevant conversation.”
- Rob Jackson,
Co-Founder, DBI
![It's important for us to understand why [customers] are there. Then we can deliver an experience that matches up with that intent](/content/dam/dx/us/en/experience-cloud/topics/ai-personalization/54658.en.exc.feature.progexion.490x183.jpg.img.jpg)
“It's important for us to understand why [customers] are there. Then we can deliver an experience that matches up with that intent”
- LJ Jones,
Director of Optimization, Progrexion
How does artificial intelligence help with personalization?
It adds a cognitive component to traditionally human-powered and automated tasks. Machine-learning algorithms allow you to process large amounts of data and suggest the most effective combination of content, product, and offer.
Does AI personalization help with content curation?
By observing user behaviors, along with online habits of peers, AI helps select content for repurposing or retargeting by speeding up the process of filtering through vast libraries of content.
How does AI personalization help with content curation?
AI personalization can assist with delivering the optimal content or design template to your audience, but it cannot yet organize data into creatives.
How does AI personalization help build audience intelligence?
Algorithms assist with surfacing and scoring user traits, preferences, and behaviors, along with contextual identifiers like location or time of day.
Is AI personalization worth the investment?
It assists immensely with rapidly scaling your personalization efforts. Targeted recommendations from machine learning have been shown to contribute up to 30 percent in revenues for leading brands.
Is AI personalization limited to email and website content?
No. Personalization driven by data science can be applied across all digital touchpoints, delivering increasingly relevant content across channels and connected screens and devices.