You can rely on data science to analyse user behaviour, preferences, feedback and characteristics to predict behaviour and deliver unique, personalised experiences. This helps you to increase engagement and offer dynamic, one-to-one touchpoints with ease.
While AI personalisation can offer better targeting and conversion-rate optimisation 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 personalisation extend beyond workflow efficiencies. You can achieve gains in several key areas.
Machine-learning algorithms are more suited to optimise content accurately and swiftly at a scale that human analysis and decisioning can’t match.
By leaning on AI personalisation to understand audiences better, you minimise risks due to biased or flawed decision-making.
AI personalisation 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.
Personalisation activities improve investment returns, lift cross-sell and upsell results and generate higher revenues than non-personalised 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 Optimisation, Progrexion
How does artificial intelligence help with personalisation?
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 personalisation help with content curation?
By observing user behaviours, along with online habits of peers, AI helps select content for repurpose or retargeting by speeding up the process of filtering through vast libraries of content.
How does AI personalisation help with content curation?
AI personalisation can assist with delivering the optimal content or design template to your audience, but it cannot yet organise data into creatives.
How does AI personalisation help build audience intelligence?
Algorithms assist with surfacing and scoring user traits, preferences and behaviours, along with contextual identifiers like location or time of day.
Is AI personalisation worth the investment?
It assists immensely with quickly scaling your personalisation efforts. Targeted recommendations from machine learning have been shown to contribute up to 30 per cent in revenues for leading brands.
Is AI personalisation limited to email and website content?
No. Personalisation driven by data science can be applied across all digital touchpoints, delivering increasingly relevant content across channels and connected screens and devices.