Since Qlik AutoMLTM became generally available earlier this fall, more businesses from a variety of sectors have started using it to supplement their decision-making with the strength of predictive analytics for the 90% of use cases that don’t call for the in-depth knowledge of trained data scientists.
Every industry uses machine learning, but due to a lack of resources and bandwidth for data scientists, its application and usefulness have been constrained. By providing a straightforward, code-free method for analytics users and teams to use machine learning to train models, generate predictions, and make choices on their existing analytics use cases, Qlik AutoML is bridging that gap. Teams from across the organisation can now explore predictive data and test what-if scenarios directly in Qlik Sense thanks to Qlik AutoML, which can then set off alerts and automations that can be used throughout the company.
By modelling anticipated outcomes and adapting strategies based on predictions, businesses like Chef Works, RevLocal, and Bentley Systems are all implementing Qlik AutoML to better predict churn, drive efficiencies, and engage and keep clients. Another such is Polygon Research, which provides useful market research to the mortgage business. By providing options for refinancing or loan modifications, Polygon is using Qlik AutoML to make predictions about things like loan repayments to assist lenders in making the proper interventions.
“This is where AutoML really shines”, “You can get down to individual loans, see the percentages on every single variable and then see the cumulative decision: is this borrower going to prepay or not? What’s the prediction? And what’s the strength of that prediction?”
Greg Oliven, CTO of Polygon Research
Every division of an organisation can use AutoML in common situations. Better predictions that encourage proactive engagement can benefit business users in Sales (forecast/churn/retention), Marketing (customer lifetime value and demand forecast), Finance (risk management and investment optimization), HR (employee retention/satisfaction/recruiting), and Supply Chain (inventory predictions/bottlenecks and transportation optimization).
“Modern analytics, when augmented with machine learning, can take the guesswork out of the future and help decision makers know what is likely to happen, why that outcome is likely and, crucially, what changes will influence the outcome”, “Qlik AutoML is helping organizations drive more value from their data and empowering their teams to look around the corner when making decisions that impact outcomes.”
Josh Good, Vice President, Product Marketing at Qlik