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How to use AI for predictive analytics in marketing?

ROI answers

AI-powered predictive analytics in marketing uses machine learning algorithms to analyse your existing customer data – website behaviour, purchase history, demographics – to forecast future outcomes, like which customers are most likely to convert, or when they’re likely to churn.

  • Lead Scoring: Current systems include AI that automatically ranks leads based on their likelihood to become paying customers, allowing your sales team to prioritise effectively.
  • Churn Prediction: Identify customers at risk of leaving, enabling proactive engagement with targeted offers or support.
  • Personalised Recommendations: AI now features the ability to dynamically tailor product recommendations and content based on individual customer preferences, boosting conversion rates.
  • Campaign Optimisation: Predict which ad creatives and targeting parameters will perform best, maximising your return on ad spend.

As of early 2026, Australian businesses must also consider data privacy regulations like the updated Privacy Act. Predictive models need to be transparent and avoid discriminatory outcomes, ensuring fair treatment of all customers. Platforms like those integrated by ROI.com.au are designed with these compliance requirements in mind, utilising anonymisation and ethical AI practices. In 2026, we’re also seeing increased integration with Australian-specific data sources, like consumer sentiment analysis related to local events and trends.

Instead of navigating the complexities of data science, algorithm selection, and ongoing model maintenance, you can focus on growing your business. We can take care of all this for you. Contact ROI Growth Agency today to discuss how AI-powered predictive analytics can transform your marketing performance.


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