Fast-growing companies have lots of data, so no matter who you are, you’re probably sitting on a mountain of data right now. Unfortunately, most revenue operators struggle to generate insights in a fast and meaningful way. Erik Mathiesen, CEO at Infer, is here to show us how Infer uses AI to help companies understand and optimize data–without hiring a data science team.
“I’ve found that, in a lot of businesses I worked with, we weren’t always great at understanding our customer base.” - Erik Mathiesen
Are you struggling to understand your customer data? Can you answer questions like which exact customers will churn this quarter and next, or which deals in your pipeline are most at risk? If you’re willing to spend hours in a spreadsheet crunching numbers, you might be able to answer these questions. Or you can head over to Infer and learn about how they use machine learning methods to query data directly in your database.
“What is a churn customer? How do you define it? How do you make sure that an analysis is done correctly? The ops person is the expert in this field.” - Erik Mathiesen
The Infer platform operates on three data analytics components:
Using a machine learning model that updates every hour, Infer adds another layer of analysis to your CRM data that supercharges your forecasting to help you predict the probability of close deals and deal sizes. The model never gets old and is constantly retrained using your latest data. You can compare these insights with your CRM forecast to better understand your progress.
If you’re not very familiar with SQL, don’t worry, Infer has a no-code interface called Coworker. Coworker helps you figure out exactly what you can do with your data sets and uses predictive modeling to build a segmentation model and customer personas to identify who’s going to churn and who’s your ICP.
“We believe so strongly that, within a week, you should have something up and running that's providing very high value.” - Erik Mathiesen
Infer integrates with a number of popular systems including:
Typical Infer customers make greater than $5 million in revenue and have hundreds (if not thousands) of opportunities in their CRM, making it worthwhile to spend time on predictive analytics. While customers can analyze everything from marketing spend, lifetime value, and even usage consumption, most get started on Infer by focusing on new business-related use cases.
When it comes to implementation, the work can be completed in a matter of days. You can continue to tweak models, iterate, and upskill your people as your needs grow. Most customers can self-service onboard but Infer is always available to offer support.
Infer is easy to use and highly customizable so get ready for deep analytics and insights without having to become a data scientist yourself. Reach out to Infer to get in touch, have a quick conversation about your specific business needs, and see a demo today.
