Meta’s Muse hits 10 million US downloads in 40 days, outpacing AI rivals in retention
Meta’s AI companion app, Muse, has reached 10 million U.S. downloads in its first 40 days, a milestone achieved by only 11 other apps. The app’s retention rates surpass competitors like ChatGPT and Grok, while its shopping features are driving high-value transactions—though operational costs keep it unprofitable for now.
Editor, Lazyfounder
30 SEC SUMMARY
- Meta’s AI companion app, Muse, reached 10 million U.S. downloads in 40 days, a milestone matched by only 11 other apps.
- Muse’s 7-day retention rate is 30%, outperforming competitors like ChatGPT, Claude, and Grok.
- Meta allocated 39% of its October ad spend to Muse, driving its rise to 21st in U.S. ad impressions.
- Shopping is the top use case, with average purchases exceeding $200, prompting Meta to collaborate with Stripe on credit limits.
TABLE OF CONTENTS
KEY HIGHLIGHTS
- Muse hit 10.2 million U.S. downloads within 40 days, joining an exclusive group of 11 other apps to achieve this milestone.
- Meta spent 39% of its total advertising budget on Muse in October, pushing it to 21st in U.S. ad impressions.
- Muse’s 7-day retention rate is 30%, and its 14-day retention rate is 23%, higher than ChatGPT, Claude, and Grok.
- Muse reached 2.5 million daily active users on October 16, with shopping as the dominant use case, averaging over $200 per purchase.
- Meta partnered with Stripe to address unexpectedly high purchase volumes, while Amazon, Schwab, and JPMorgan restricted or blocked Muse.
A rare launch milestone
Meta’s AI companion app, Muse, has joined an exclusive group of mobile apps by reaching 10.2 million U.S. downloads within 40 days of its launch. According to data from Sensor Tower, only 11 other apps—primarily mobile games—have achieved this milestone. The most recent app to do so was Meta’s own Threads in July 2023.
Muse’s rapid adoption is partly attributed to Meta’s aggressive marketing push. The company allocated 39% of its total advertising spend to the app in October, up from 23% the previous month. This effort propelled Muse to the 21st-largest brand in the U.S. by advertising impressions, rising from 73rd in September.
Retention outpaces AI competitors
Muse is not only gaining users quickly but also retaining them better than its rivals. The app’s 7-day retention rate stands at 30%, while its 14-day retention rate is 23%. By comparison, competing AI apps like ChatGPT, Claude, and Grok average 19% and 16% for the same periods, respectively.
Daily active users for Muse reached 2.5 million on October 16, representing a 15% week-over-week increase. The app has dominated the U.S. App Store, holding the No. 1 rank for all but one day since its launch, and has also topped Google Play’s rankings over the past 30 days.
Shopping drives engagement, but costs remain high
Shopping has emerged as the most popular use case for Muse, with users averaging purchases over $200. Meta’s collaboration with Stripe to raise credit limits reflects the unexpected volume of transactions. However, the app is not yet profitable due to high operational costs, which have limited its availability to the U.S. and Canada.
Meta is investing heavily in scaling Muse, with plans to improve its cost efficiency by more than 10x over the next year. The company expects revenue per user to eventually surpass the "several hundreds of dollars annually" it earns from each U.S. user of its other apps. Monetization will focus on subscriptions for heavy users and fees from businesses, rather than charging end users directly.
Resistance from financial and e-commerce platforms
Despite its growth, Muse faces resistance from major platforms. Amazon has blocked the app from accessing its site, while Schwab and JPMorgan have restricted its functionality, citing security concerns. These restrictions mirror broader industry pushback against third-party AI agents accessing sensitive financial or transactional data.
Meta has also addressed privacy issues, including a recent fix for share links that exposed users’ loan files and revenue data. A forthcoming feature, "Muse Confidential VM," aims to prevent even Meta from accessing user content.
Background: Meta’s playbook for scaling new apps
Meta’s success with Muse mirrors its strategy for Threads, which leveraged Instagram’s social graph and integration across Facebook and Instagram to scale rapidly. With a combined 3.6 billion daily active users across its apps, Meta can drive adoption of new products through cross-platform promotion—a advantage smaller startups lack.
What this means
Lazyfounder analysis — our interpretation, not reported fact.
Muse’s rapid growth demonstrates Meta’s ability to leverage its existing user base and advertising infrastructure to scale new AI-driven products. For founders, the app’s strong retention rates—outpacing competitors—suggest that AI companions can sustain user engagement when designed for specific use cases like shopping or productivity. However, Muse’s unprofitability and platform restrictions highlight the challenges of balancing scale, cost, and trust, particularly in industries wary of AI autonomy.
Key takeaways
- Muse’s rapid adoption signals Meta’s ability to leverage its existing user base for new product launches, a playbook founders can study for scaling AI-driven apps.
- The app’s strong retention rates highlight the potential of AI companions to sustain user engagement, a critical metric for competitors in the space.
- Meta’s aggressive monetization plans—including subscriptions and business fees—could set a precedent for how AI agents generate revenue without charging end users.
- Restrictions by Amazon, Schwab, and JPMorgan underscore the challenges AI agents face in regulated industries, particularly around security and autonomy.
Related on Lazyfounder
Sources
- TechCrunch · 2026-10-20
Meta’s Muse hits 10M U.S. downloads in 40 days, a milestone reached by only 11 other apps - The Next Web · 2026-10-23
Meta had to ask Stripe to raise limits as Muse shoppers poured in
This story is an original summary drafted with AI by Lazyfounder from the reporting listed above and checked by automated validation. Facts are attributed to their original publishers; sections marked as analysis are Lazyfounder's. Where a source is in another language, facts were machine-translated and quotations are reported, not reproduced. Read the original coverage via the links, and see our AI policy and corrections policy.
About the author
Editor, Lazyfounder
Tarun Mottlia edits LazyFounders, covering Indian startups, funding rounds, AI and product launches. Every story on the site is AI-assisted and checked against its cited sources before publication.
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