The best techniques and technology in the world won’t help you if you don’t know how to use them. Annoyingly, with it being so new, it’s hard to tell what machine learning marketing use cases there are to base your efforts on.
In other fields, the breakthrough tech is being used in medical diagnoses, spam filtering, fraud detection, translation and more. All you need is some inspiration to get started with your own uses.
That’s why this post exists.
I’ll cover, in detail, the key ways machine learning is affecting marketing, and how it can be used to handle some of your business process automation, provide actionable data insights and predictions, and even win $1 million on Jeopardy.
Machine learning marketing uses
Getting content suggestions for news and new ideas
RSS feeds are vital for keeping on top of the latest industry news and learning new tips and techniques in your field. It’s also a great way to fill in your dead time (e.g., on your bus ride home) and let you read more, which is a great way to generate blog ideas for your own content.
Feedly is an awesome example, with their mobile app letting you subscribe to various blogs, websites, and content aggregators to make reading the best articles around a case of scrolling through a single feed.
The main problem comes when you’re trying to find the websites to subscribe to. It’s hard enough to keep on top of recent articles without having to spend time vetting new sites for valuable content.
That’s where Feedly’s machine learning element comes into play.
Instead of recommending sites based on vague categories, Feedly assesses the user-assigned tags of every website and uses them to assign categories and relevant topics. Other factors like follower count and engagement amount are then used to dictate which websites are recommended with a higher priority, with the entire model being assessed and automatically updated based on current user tags and interactions.
The result is a recommendation system which detects the best relevant websites to offer to make getting the best content easier than ever before. Don’t sit around – get inspired.
Enhancing existing tools
Marketers rely on analytics and predictions on who to target, what they will interact with, where the best place to find them is and so on. This is usually done using a formula, looking at recent trends, as part of an overarching technique (eg, targeting relevant keywords) or via the highest paid person’s opinion (HIPPO).
Trouble is, customer behavior is changing constantly, meaning any plans or formulas currently being used by your marketing department will become inaccurate and need updating sooner or later.
That’s where machine learning can help through services like Salesforce Einstein.
Using machine learning to crunch data and automatically update predictions for everything from customer reactions to conversion rates, Einstein lets Salesforce users take advantage of the power of machine learning without the need to create their own tool.
The result is a …read more
Read more here:: B2CMarketingInsider