All this while, the Sitecore community had been trying to bring in Sitecore ML in the former versions, but luckily, now we have Sitecore Cortex that offers a skeleton, making it easier to incorporate machine learning models within content authoring and marketing workflows.
Marketers today are empowered with the ability to understand user behaviour and predict relevant content to the corresponding persona.
With Sitecore 9.1, achine learning algorithms as well as Natural Language processing (NLPs) are used to study the patterns of user behaviour to develop ML models for prediction purpose.
Sitecore Version 9 is a “one connected platform” and has the ability to tag, track, measure and optimize the customer digital touchpoints or end-to-end journey in a lucid way.
The Situation till now
While Azure Machine Learning increases site engagement by helping companies to deliver the most pertinent content to the customer, most organizations struggle to maintaining multiple platforms serving different parts of their customer journey, making it all the more difficult to build an accurate picture of customer behaviour and opportunities for improvement.
Why Did We Choose Azure Machine Learning
If you’re looking to drive even more business value from your xDB data, experimenting with ML models is now easier than ever.
Sitecore Cloud on Azure offers excellent performance in deploying and scaling infrastructure on-demand, significantly reducing development costs. Using native Azure services and a pay-as-you-go usage-based model can simplify IT operations.
Let's now take a close look at the six reasons for using Azure Machine Learning and Sitecore for one-to-one personalization:
This is how the skillset mix works:
The drag and drop facility in the Microsoft Azure ML Studio
Content Tagging Process in Sitecore Cortex
Read our blog: How Automation of Content Tagging in Sitecore Cortex works in the presence of Azure ML Studio.
What Future Holds
For now, we have just used the xDB data along with the data tags. In case we want to define the scope of Personalization using Azure Machine Learning in the future, the following features can be bought to use to mileage the one-to-one personalization with the viewer.
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