Machine learning isn’t just self-driving cars and personal assistants — companies like Netflix, Facebook and eBay use it to predict customer behavior, prevent fraud, improve the supply chain, boost customer retention and more. For insight into how you can leverage the power of machine learning, don’t miss this interactive VB Live event.
“10 years ago, we struggled to find 10 machine learning-based business applications,” said Gartner’s VP of Research, Alexander Linden, during his speech at the Gartner Business Intelligence & Analytics Summit in India. “Now we struggle to find 10 that don’t use it.”
Machine learning is already the foundation of industry giants. It drives Google’s RankBrain, which processes more than 3.5 billion search queries every day, continuously comparing billions of pages to move the most relevant to the top to improve your results.
Netflix uses machine learning to not only boost user engagement but keep customers coming, by processing ever-changing title ratings, viewing statistics, and geographical information to ensure content served to viewers is what they more likely want to see.
At Facebook, they’re trying to keep you logged in, and keep you interested in the ads you see on your sidebar and in your news feed, not just with age, interests, education data, and more helping them constantly refine their targeting and improve their retargeting, but based on the things you liked, groups you joined, and the pages you follow.
eBay and Amazon want to keep you shopping, so they’re investing in machine learning to uncover exactly what products you want to see and are likely to buy. And the more time you spend shopping, the more they learn about your habits and interests, and the deeper they crawl into your secret wishes and find you the velour jumpsuit you didn’t know you wanted.
Machine learning is the answer to the question many companies asked when they were faced with the possibility of big data — what’s the point of all this data? And isn’t most of it useless? Businesses were reluctant to invest in analytics platforms without having a data strategy, and the flood of information made it nigh-impossible to sift through and figure out, first of all, what matters, exactly.
And they weren’t wrong. With data analysis often relying on a trial and error approach, it is actually impossible to analyze every bit of data collected. By the time you’ve gotten through it, it really is pointless.
That’s where machine learning comes in: to analyze information, uncover patterns and extract actionable insights you didn’t know were lurking in that ocean of facts, figures, and statistics — up to billions of transactions with ease, in real time. All the data, regardless of its volume, can be mined; no data is left behind. And that means improved real-time customer segmentation, reduced churn, predictable LTV — and all many other applications.
Sound useful? Join our latest VB Live to learn how to ensure that you’re making the right decisions with the right data with machine learning. Because the more data you have, the better those decisions will be.
Don’t miss out!
In this VB Live event, you’ll:
- Learn how cognitive technologies scale across mobile devices (including cars)
- Evaluate the value of a machine learning product to your organization
- Tailor your data structure to optimize for future machine learning initiatives
- Stewart Rogers, Director of Marketing Technology, VentureBeat
- Quinn Banks, Senior Product Marketing Manager, Farmers Insurance
- Wendy Schuchart, Analyst, VentureBeat