During this year’s Symposium, I attended several sessions that explored possible applications for Machine Learning. These all have the potential to boost the experience that is offered to customers while adding significant value to organizations.
The first session was by Michael Greenberg and explored thirty possible use cases for machine learning today. These include prioritizing offers or sale items for customers, invites for subscriptions, recommended products, creating segments, creating personas, lead scoring, potential value of new customers, and so on. All of these use cases can be utilized by marketers and content authors to deliver better experiences to the users.
The second session was by Una Verhoeven. She provided a detailed example of how information from social media (e.g. Twitter) can be analysed using Machine Learning algorithms to create an analysis of a person’s personality and then provide a set of books that they may be interested in purchasing. This is accomplished using IBM Personality Insights to get an analysis of a person’s personality and interests, contact and purchase data from xConnect, a set of books that we can provide recommendations from, and finally IBM Watson to model the data and get the final set of recommended results. This can increase sales and help customers find their desired products quickly.
The third and last session was by Klaus Petersen and provided an overview of Churn analysis. Churn is essentially attrition or loss of customers - for example, this could be subscribers choosing to unsubscribe, or customers cancelling a monthly service. Churn analysis can predict which clients may potentially leave the organization, and this in turn allows the organization to decide whether to invest in retaining these clients. In general, services with high acquisition costs would benefit the most as retaining existing customers may potentially be more profitable than attracting new customers. This can provide a lot of value to an organization at a low cost.
Overall, the applications of Machine Learning are numerous and can add great value to organizations and their customers. This is becoming more and more apparent to many, driving increased demand for machine learning solutions. Sitecore 9.1 comes with its own Machine Learning toolkit, The Sitecore Cortex.