And why businesses should look for a simple and automated integration.
When using ML for business decisions, it’s not enough to have the technology. You need to expose it to your team in a way that fits how they already work and think.
It's Monday morning. You open the email you open first every day: "New sales lead qualification predictions."
The attached spreadsheet shows new leads along with a machine learning prediction of how likely they are to convert to customers. After a quick column sort, you now know exactly what you should focus on for the day.
You have an idea for a new piece of data that might help make predictions even more accurate. You're not a data scientist, but within five minutes, you’ve uploaded the new data and created a new machine learning model. It’s a strong improvement, and you did it using excel!
At a meeting, you use your improved machine learning model to simulate how changes in marketing strategies can shape sales lead quality. When you tweak a parameter, like choice of marketing platform, the machine learning model predicts its likely impact on sales. Your team gains new understandings of where to focus their efforts, and the levers that will drive change.
By starting with a powerful tool that doesn’t necessitate code or a data scientists: