What Is Machine Learning and Why Is It Important?
Facial recognition. Text-to-speech recognition. Spam filters. Credit card fraud detection.
Machine learning is at work in all these technologies. Machine learning (ML) enables computers to learn how to do a task without being programmed to do so. Let’s learn how artificial intelligence (AI) and machine learning work—and the ways they’re changing the nature of how marketers make decisions and deploy campaigns.
What is machine learning?
Say you need a computer to accurately identify images of cats. You could feed the computer examples of images containing cats. Then, the computer will learn to find and analyze statistical patterns in the data, using the results to identify cats in other images.
The key aspect of machine learning is that the computer—not a programmer—is identifying those patterns to sort future data. The task is explained with examples, not instructions. The more images of cats the computer processes and analyzes, the more precise its predictions will become.
Machine learning allows computers to efficiently detect and sort patterns that would be difficult, or impossible, for people to pick out of mountains of data.
Why is machine learning important to the customer experience?
Marketers seek to understand and interpret a customer’s journey by engaging them at the right place and time. It used to be as simple as tracking customers through the sales funnel, from top to bottom:
- Awareness
- Consideration
- Decision
Now, customers expect companies to anticipate their wants. Marketers must agilely interpret a buyer’s intent by creating a personalized shopping experience with custom recommendations. Consumers are almost two times more likely to view personalized offers as important versus unimportant. Additionally, in exchange for personalized offers and discounts, 88 percent of consumers share personal data with companies before they buy.
How are marketers using machine learning?
Smart marketers are investing in AI enhancements to deepen customer intimacy, to develop effective customer engagement, and to deliver a higher level of customer service. Here are just a few ways companies are using machine learning:
- Sentiment analysis: Determining whether an online interaction, such as surveys, emails, or social media comments, is positive or negative to better understand their brand’s reputation.
- On-platform personalization: Offering personalized recommendations based on each unique visitor’s preference and user history.
- Predictive analytics: Anticipating what users will do next to prevent churn or to yield conversion for a better ROI.
Machine learning allows marketers to harness data to find valuable insights to anticipate and enhance a buyer’s journey.
Real-World Examples
Looking for more inspiration from marketing mavens? Here are three real-world examples of major brands using the power of machine learning:
1. Spotify
You’re logged into Spotify, jamming to your tunes for the millionth time. Ready to switch up your listening experience? Unlike other streaming music platforms, Spotify recommends genres and artists that complement your tastes instead of just playing bands that mimic or repeat what you’re already listening to. Using technology bolstered by AI and machine learning, Spotify can create personalized playlists for audiophiles everywhere, delivering a customized user experience.
2. Lyft and Uber
Rideshare services are now widespread, worldwide. When you open the Lyft or Uber app on your phone to hail a ride, machine learning drives the user experience. Algorithms analyze date from previous users’ trips and real-time traffic to determine how far your driver is from your given location, as well as an estimated time of arrival to reach your final destination. Accurate time estimates can mean the difference between a satisfied customer with a successful pickup and an annoyed customer canceling their request.
3. Pinterest
Say you’re recently engaged and ready to dive into wedding planning. Enter Pinterest and its content discovery. Start a pin board dedicated to art deco-themed inspiration and algorithms powered by machine learning will assist with curated content. You’ll have a board with visually related recommendations in no time.
Sources:
Breaking the Marketing Mold with Machine Learning, MIT Technology Review Insights and Google, 2019.
Humans + Bots: Tension and Opportunity, MIT Technology Review Insights and Genesys, 2018.
State of the Connected Customer, Salesforce, 2018.
What Is Machine Learning?, OxfordSparks, 2017.
