Watch all the Transform 2020 sessions on-demand here.
Presented by IBM
Nobel Prize-winning author Andre Gide once said, “Man cannot discover new oceans unless he has the courage to lose sight of the shore.”
The typical organization has done much to empower its employees. Most progressive firms allow employees to drive basic decision-making, make financial and purchasing decisions, and freely allocate how they spend time.
One area yet to be democratized is access to data and insights. Sure, enterprises provide reporting and dashboards, but those are less about freedom and more about conformity. The advent of machine learning and visualization has unlocked an understanding of the way things work and predicting how they may work in the future. These are truly tools of discovery.
June 5th: The AI Audit in NYC
Join us next week in NYC to engage with top executive leaders, delving into strategies for auditing AI models to ensure fairness, optimal performance, and ethical compliance across diverse organizations. Secure your attendance for this exclusive invite-only event.
So, why isn’t there widespread use of these tools? Why don’t enterprises want to turn more employees into data scientists? Why don’t they want to make machine learning available to the masses?
The typical reasons fall into the three following areas:
- Data: There is too much of it, it requires a lot of “cleaning” and we don’t often know what data matters most.
- Culture: Organizations lack the courage to empower in a free-form manner.
- Skills: There is a lack of analytical skills, let alone data science skills.
So, how can employees discover new oceans — or, if not oceans, new paths to where they need to go?
By empowering their employees to use machine-learning techniques to help wrangle data and predict outcomes, GroupM, a media investment company, has seen conversion rates improve by as much as 50 percent.
The company made the most of a marketing investment by optimizing the timing and placement of advertisements. Consumer tastes and preferences change dramatically, and irrelevant ads are a waste of time for consumers and a waste of money for the brands behind the campaigns.
GroupM used machine-learning algorithms to learn which factors influence behavior, and gained greater levels of insight into the targeting, timing, and placement of ads to improve their marketing campaigns and ultimately, their conversion rates.
In this video, learn how GroupM applied an easy-to-use machine learning tool to positively impact business after only one month of experimentation.
https://www.youtube.com/watch?time_continue=1&v=vIWcnKTQXok
Dig deeper: Learn more about exploration and data discovery.
Sponsored posts are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. Content produced by our editorial team is never influenced by advertisers or sponsors in any way. For more information, contact sales@venturebeat.com.
