From PM’s Pain to $330M Gain: The Untold Story of Sprig

This founder left a well-paying job to solve a personal problem — now it’s a $330M company.

Industry leaders like Figma, Notion, and Coinbase are already using it to maximize user feedback.

Here’s how Sprig went from a simple SDK to becoming a platform used by some of the best product teams in the world:

(This analysis is based on 11 in-depth conversations, including interviews with 6 Sprig team members, 3 customers, and 2 competitors.)

𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟭: 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 (𝟮𝟬𝟭𝟴) 𝗮𝗻𝗱 𝗧𝗵𝗲 𝗙𝗶𝗿𝘀𝘁 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 (𝟮𝟬𝟭𝟵)

Ryan Glasgow was a product manager Weebly (later acquired by Square) when he noticed a huge problem:

Getting qualitative feedback from millions of users was painfully slow and clunky.

Most PMs would’ve moved on, but Ryan decided to build a solution from scratch. They built an SDK with three rotating questions on quality, functionality, and usability.

No targeting. No customization. Just raw simplicity. Square became their first big customer, validating their product with real-world use.

𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟮: 𝗧𝗵𝗲 𝗟𝗼𝗻𝗴 𝗚𝗮𝗺𝗲 (𝟮𝟬𝟭𝟵-𝟮𝟬𝟮𝟬) 𝗮𝗻𝗱 𝗧𝗵𝗲 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗕𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 (𝟮𝟬𝟮𝟬)

While most startups race to launch, Sprig took a different approach.

They spent two years refining the product, working with design partners like Dropbox and Robinhood. Every survey was custom-built, every piece of analysis verified by hand.

In 2020, Sprig introduced event-driven architecture. This was a game-changer: teams could target surveys based on specific user actions, capturing feedback immediately after key experiences.

By year-end, they were processing over 10 billion API interactions each month.

𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟯: 𝗧𝗵𝗲 𝗠𝘂𝗹𝘁𝗶-𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 (𝟮𝟬𝟮𝟭-𝟮𝟬𝟮𝟮) 𝗮𝗻𝗱 𝗧𝗵𝗲 𝗔𝗜 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 (𝟮𝟬𝟮𝟯-𝗣𝗿𝗲𝘀𝗲𝗻𝘁)

At that time, product research was expanding beyond researchers to PMs, designers, and engineers. Sprig responded with a wave of features: Figma integrations, video surveys, multi-language support, and more.

Sprig had been building AI for years and today, their AI analyzes open-ended responses, groups feedback into themes, and even generates product recommendations.

With this, AI at Sprig became more than a feature — it’s an engine for product insights.

𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟰: 𝗦𝗽𝗿𝗶𝗴 𝟮.𝟬: 𝗕𝗲𝘆𝗼𝗻𝗱 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀 (𝟮𝟬𝟮𝟰) 𝗮𝗻𝗱 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗩𝗶𝘀𝗶𝗼𝗻

In September 2024, Sprig launched Sprig 2.0, expanding beyond surveys with the vision to “Build for people, not data points.”

In the future, Sprig is aiming to build self-optimizing products that constantly learn from user behavior.

With autonomous AI agents as PM assistants, Sprig’s vision is ambitious — and they’re already on their way with over 30K customers.

“But how do they build products?”

“How did they get to a $330M+ valuation with just a 25-person product team?”

I do a whole 7 layers of the iceberg, how they build product, and their market position analysis in the newsletter.