Nami ML
UnclaimedIntelligent platform for scalable subscription growth and monetization in high-volume consumer apps.
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TL;DR - Nami ML
- Optimize subscription funnels with no-code paywalls and landing flows.
- Gain unified insights into subscriber acquisition, growth, and retention.
- Empower product, marketing, and engineering teams with a single platform.
Pricing: Paid only
Best for: Enterprises & pros
Pros & Cons
Pros
- Enables rapid iteration and A/B testing of paywalls and flows without app updates.
- Provides a unified view of subscriber data across all platforms and tools.
- Empowers non-technical teams (product, marketing) to manage monetization experiences.
- Offers enterprise-grade speed, security, and data privacy (SOC 2, PCI-DSS compliant).
Cons
- Specific pricing details are not publicly available, requiring a demo or contact sales.
- Primarily focused on high-volume consumer apps, which might be overkill for smaller operations.
Key Features
No-Code Paywall BuilderSubscription Management (in-app, web, CTV)Subscription AnalyticsSubscriber CRMData Feeds & APIsOnboarding & Funnel OptimizationAdaptive ExperimentationCross-Platform Subscription Intelligence
Pricing Plans
Complete solution
Contact us
- Phone, tablet, CTV, web
- Volume pricing & SLA
- Carrier grade specs
About Nami ML
By Toolradar Team·
Nami ML is an enterprise-grade subscription monetization platform designed for high-volume consumer applications. It provides a complete solution for managing and optimizing the entire subscription journey, from initial acquisition to retention. The platform empowers product owners, growth marketers, and engineering teams to launch, test, and optimize landing flows, paywalls, and onboarding sequences with speed and control.
Key functionalities include a no-code paywall builder for instant design and updates, comprehensive subscription management across various platforms (mobile, web, CTV), and robust analytics to track key metrics and gain insights into subscriber behavior. Nami ML also features a Subscriber CRM for a unified view of customer data, and Data Feeds & APIs to integrate subscriber context across an organization's tech stack, enabling personalized experiences and data-driven decision-making.
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Nami ML FAQ
How does Nami ML enable growth marketers to iterate on paywalls without developer involvement?
Nami ML provides a no-code paywall builder that allows growth marketers to design, launch, and update subscription paywalls directly from their browser. This eliminates the need for code changes or app releases, enabling real-time iteration and A/B testing of different designs, pricing, and copy.
What specific types of data can product owners access through Nami ML's Subscription Analytics and Subscriber CRM?
Product owners can access detailed acquisition, growth, and retention metrics through Subscription Analytics. The Subscriber CRM provides a single view of each customer, including purchase history, platforms used, total spend, and subscription status (e.g., credit card declines), without needing to consult multiple systems.
Can Nami ML manage subscriptions across different platforms like mobile, web, and Connected TV (CTV) simultaneously?
Yes, Nami ML is designed to offer in-app purchases and subscriptions across mobile, web, and connected devices (including CTV) from a single service. It provides cross-platform subscription intelligence to give a unified view of what drives growth across these diverse channels.
How does Nami ML address 'paywall fatigue' for subscription apps?
Nami ML helps combat paywall fatigue by enabling adaptive experimentation and personalization. Marketers can target different paywall experiences to users based on their journey stage, language, and other contextual rules, optimizing conversion and reducing the negative impact of repeated, generic paywall exposure.
What kind of integrations does Nami ML support to enrich an existing tech stack?
Nami ML integrates with popular solutions across analytics, messaging, and customer support. It allows for the activation of unified subscriber data throughout an organization's stack, ensuring consistent messaging and leveraging subscriber context in various tools already in use.
Source: namiml.com