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Using AI in Predictive Analytics: A Marketer’s Guide

Using AI in Predictive Analytics A Marketer's Guide

Online astrology websites have been the first movers on using Predictive Analysis. They’ve been using data and data-base driven technologies, for eons, to generate your horoscope within seconds. And today with AI, it can happen in real time, with real time data. 

By analyzing large amounts of data, AI can identify patterns and predict future outcomes, such as which marketing channels are most effective or which customers will convert. By focusing on the most effective channels and strategies, marketers can optimize their campaigns for maximum ROI, reduce costs, and increase conversions by targeting the best prospects.

It is possible to perform predictive analytics using several tools. Your digital agency or a specialist service provider is most likely to provide this service. Before choosing your partner, you should familiarize yourself with the following programming languages and platforms:

  • Scikit-learn, TensorFlow, and PyTorch are some of the popular Python libraries and frameworks for data analysis and machine learning.
  • R is a statistical programming language that can be used for data analysis and predictive modeling. It has many libraries and packages for machine learning and predictive analytics, including caret, mlr, and randomForest.
  • A cloud-based platform for data analysis and machine learning, IBM Watson Studio provides tools for predictive analytics, including automated machine learning, data visualization, and model deployment.
  • A cloud-based platform for machine learning and artificial intelligence, Google Cloud AI Platform provides tools for predictive analytics, such as automated machine learning, data preprocessing, and model deployment.
  • It offers tools for predictive analytics, including automated machine learning, data preprocessing, and model deployment. Azure Machine Learning is a cloud-based platform for building and deploying machine learning models.
  • SageMaker is a cloud-based platform for building and deploying machine learning models. SageMaker provides tools for predictive analytics, including data preprocessing, automated machine learning, and model deployment.

The choice of predictive analytics tool depends on factors such as the complexity of the data, the size of the dataset, and the specific project requirements. With artificial intelligence, marketers can analyze large amounts of data to identify trends and patterns that can be used to predict future outcomes. This can help them optimize their campaigns for maximum ROI.

Here are a few examples of brands using predictive analysis in paid media campaigns

  • Kotak Mahindra Bank, has used predictive analytics to boost customer acquisition and improve marketing campaigns. Kotak Mahindra Bank optimizes their marketing spend and improves their ROI by analyzing customer data and predicting which customers will respond to their marketing campaigns.
  • During the festive season, Amazon India used predictive analysis to optimize their advertising campaigns. By analyzing customer data and predicting which products were likely to sell well, Amazon India was able to maximize ROI on their advertising campaigns.
  • By analyzing customer data and predicting which customers were most likely to respond to their social media ads, ICICI Bank optimized their targeting and increased return on investment.

By leveraging data and analytics, these brands were able to optimize their strategies, improve their customer experience, and achieve better results.

According to studies, predictive analysis can significantly increase the return on investment of paid media campaigns. Aberdeen Group, for instance, found that companies that used predictive analytics in their marketing saw an increase of 22% in conversions and a 46% increase in customer retention on average. In another study, Forrester Research found that companies that used predictive analytics increased their marketing ROI by 10-20%.

In the context of paid media campaigns specifically, predictive analysis can help optimize ad targeting, ad placement, and ad messaging to reach the right audience at the right time with the right message. This can lead to increased engagement, higher conversion rates, and improved ROI.

According to the industry, target audience, and campaign objectives, predictive analysis can have a different impact on paid media campaigns. In order to ensure that brands are effectively leveraging predictive analytics in their paid media campaigns, it is important for brands to work with experienced data analysts and marketing professionals.
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