Optimize for your industry and objective
Business-ready AI means optimizing for your goals from step one.
What's your industry? 
What are you predicting?
Solutions: Industries
The mobile app is perhaps the most critical use case for getting predictive right. When a company’s future hinges on what happens in the first 90 days after user acquisition, descriptive analytics can be ineffective.
To achieve success in a highly dynamic market, ecommerce businesses must be able to stay one step ahead of their customers—by predicting their behavior and interests in advance.
Direct-to-consumer products are booming. But as incumbent brands adopt subscription models for product lines, DTC companies need to stay laser-focused on the immediate future with predictive analytics.
When patterns of supply and demand keep changing, traditional data-driven decision making can fail to stack up. With predictive analytics, CPG manufacturers and retailers can stay at pace with new customers while retaining existing ones.
Predictive analytics is a perfect fit for established insurance companies and insurtech companies. Anticipate customers’ insurance needs and boost share-of-wallet by predicting customer behavior.
Solutions: Case Studies
After only a few hours contributed time, a retailer with multiple brands saw an effective upsell model built from raw sales and customer data.
A mobile game maker wanted to increase player engagement. By using Pecan, they were able to cut the player churn rate in half with models built in a matter of days.
A multinational fast-fashion clothing company needed granular sales forecasting—by day, by store. With Pecan’s models, they saw a reduction of up to 50% in overstock amounts, leading to 10-25% more sales.
A grocery delivery app with over 12,000 suppliers was struggling to deploy data science. By using Pecan, they turned raw sales and inventory data into an effective demand forecast model in days instead of months.
A top tier supplier of custom radio frequency (RF) components saw a fully trained demand forecast model in 14 days.
An auto insurance company with more than 3 million customers needed to improve customer experience while reducing operational costs.
A direct-to-consumer food and beverage service was experiencing unexpected customer churn for its subscription-based beverage program.