Case Study: Little Spoon improves predictive LTV, retention, and ROAS with Pecan AI

Little Spoon improves ROAS and launches predictive models in weeks with Pecan

Little Spoon, a subscription service delivering fresh baby food and kids' meals, faced challenges with manual, imprecise lifetime value (LTV) estimates. This made it difficult to evaluate marketing channel performance, predict weekly orders, and identify upsell opportunities for sustainable growth. They turned to vendor Pecan AI for a predictive analytics solution.

Using Pecan AI's platform, Little Spoon built predictive LTV and order-likelihood models without needing a data scientist. This allowed them to improve ROAS and MROI by scaling effective campaigns and eliminating underperforming ones. The solution also strengthened retention tactics and unlocked new revenue opportunities through upsell modeling, with the investment in Pecan paying off quickly through early improvements in marketing efficiency.

Little Spoon