- B
- Blockchain
- C
- Customer Churn
- Counterterrorism
- Cybersecurity in the Public Sector
- Credit Card Fraudulent Transactions
- Credit Default Rates
- Conversion Modeling
- Claim Payment Automation Modeling
- Claim Development Modeling
- D
- Drug Delivery Optimization
- Disease Propensity
- Digital Wealth Management
- Direct Marketing
- E
- Estimating Sepsis Risk
- F
- Finding Duplicate Customer Records in Your Database
- Fraud detection
- Finding New Oil and Gas Sources
- Fraudulent Claim Modeling
- G
- Google AdWords Bidding
- H
- Hospital Readmission Risk
- I
- Inventory Forecasting
- Insider Threat in Public Sector
- Insurance Pricing
- L
- Loyalty Program Usage
- Life Insurance Underwriting
- M
- Multichannel Marketing Attribution
- Modeling ICU Occupancy
- N
- Next Best Offer
- Next Best Action
- P
- Product Personalization
- Q
- Quality Assurance
- S
- Supply Chain Management
- View global site search results

Customer Churn
Problem: How to Keep Customers Coming Back
Acquiring a new customer costs time, money and lots of effort, while retaining customers is essential to the health of your businesses. That’s why understanding customer churn patterns is critical to the growth and profitability of your business.
Certainly, the pandemic has not made things any easier. According to Gartner, half of C-Suite executives at companies of $100 million in revenue are concerned about economic disruption and customer churn related to changing consumer behavior due to the pandemic.
At DataRobot, we understand that this can be overwhelming. Customer retention teams in the retail industry generally have limited resources. That’s why using AI to understand which customers are more likely to churn is important for your team, allowing them to properly allocate retention efforts.
Takes a deep dive into the many ways that companies can put their AI to work for better customer success.
Solution: Using AI to Accurately Predict Customer Churn
With more options available than ever before, consumers have more power and access to information. Companies that understand and embrace this new zeitgeist are ready to adapt—with the help of AI.
According to Forbes, companies who utilize and understand the power of AI now will avoid losing customers in the future and improve their own offerings to better serve their customers’ needs.
Customer churn modeling with AI can accurately predict which of your current customers are most likely to defect to your competitors. Having this knowledge empowers your retention team to focus their resources on the customers most at risk of churning and offer them incentives to stay.
You can’t afford to lose loyal customers. By using AI to reduce customer churn, you can keep your existing customers happy while focusing efforts on onboarding new customers.
Why DataRobot: The Modeling Your Team Needs
DataRobot allows you to stay ahead of the game by automatically identifying the individual reasons why each customer is likely to churn. This knowledge allows you to understand the factors driving your churn rate and adjust business processes accordingly, as well as customize your retention efforts. The age of the consumer is upon us and there are key opportunities for growth coming out of the pandemic. Knowing what your customers want and what drives them to potentially look elsewhere for their needs keeps your sales and marketing teams in the know, helps to drive campaign narratives, and ultimately improves customer retention and your bottom line.