How recommendation engines can refine your processes
In today’s digital world, a recommendation engine is one of the most powerful tools at a company’s disposal. A recommendation engine is an information filtering system composed of machine learning algorithms that predict a given customer’s ratings or preferences for an item.
The idea of recommendation engines is something you might be familiar with. Whether it is product recommendations on Amazon, movie recommendations on Netflix or video suggestions on YouTube, recommender systems are already a crucial aspect of your online experience and are the bedrock of progress for most of these companies.
When used properly, these engines can increase revenue, customer satisfaction, and marketing efforts. McKinsey estimated that thirty-five per cent of consumer purchases on Amazon come from product recommendations.
Why focus on recommendation engines?
You may have seen a recommendation engine in action. If you have a Netflix account, you would have seen a “Recommended For You” section containing an assortment of TV shows and movies that you might like, based on your previous choices. Reports show that recommendation engine systems can improve customer service through personalisation and make it a more enjoyable experience.
Organisations can also use these engines to promote their product range without spending much on marketing because they can recommend new products based on a customer’s purchase history. It’s an incredibly effective strategy to retain customers and it’s one of the reasons why Netflix grew from a DVD-rental company into one of the biggest brands in entertainment.
Given the exceptional benefits of recommendation engines, we decided to conduct this three-part webinar series to explain how organisations can create their own recommendation engine.
We decided to run a three-part webinar series explaining how organisations can create a recommendation engine using SAS technology. We chose to split the webinar into three different parts to give proper attention to the complex nature of recommendation engines.
What are we covering in this webinar?
In part one of our recommendation engines webinar, we explained the basics of how to create an engine using Selerity BA and SAS Business Analytics. The second webinar was built on the foundation set in the first part and explains how you can build recommendation engines that are more powerful, dynamic, and better suited for working with complex datasets (you can find these webinars on our website).
For our third and final webinar on recommendation engines. Our keynote speaker, Michael Esposito, will explain how to refine your engine to deliver the accurate readings you need to support decision-making. Furthermore, he will also dive into how to leverage your findings to improve business operations and use data analytics technology to maximise customer retention and acquisition.
The webinar will take place on 3rd December 2020 at 10:30 AM!
We hope to see you there!
Want to sign up for the session?
Visit our webinar page to get the information you need and reserve your seat! We look forward to seeing you there and hope you walk away with a better understanding of how recommendation engines work and how it can work for you.
