Question: I'm looking for a no-code solution to optimize user funnels and boost engagement in my mobile app.

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Hansel

If you want a no-code tool to optimize user funnels and increase engagement in your mobile app, Hansel is a great option. It comes with a range of tools, including a Nudge Library for creating custom nudges, a User Journey Builder for mapping user journeys, a Segmentation Engine for selecting the right audience for engagement, and reporting to track the results of your work. Hansel supports Android, iOS, Web and mWeb and can link to common analytics tools, so it's a good option for product teams trying to increase user engagement without a lot of programming.

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Abbi

Another option is Abbi, which uses machine learning and big data to analyze user behavior and send personalized, real-time messages to improve user experience and conversion rates. With automated A/B testing and easy SDK integration, Abbi lets you create and send in-app messages without app store approval. It works with native iOS and Android apps, as well as Unity, PhoneGap, Xamarin and React Native, so it's a good option for managing and optimizing in-app campaigns.

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Quest Labs

If you prefer a more AI-based approach, check out Quest Labs. The platform offers AI segmentation and personalization, a low-code interface and fully customizable templates for creating personalized in-app experiences. It also offers real-time insights into user behavior and app performance so you can make data-driven decisions. Quest Labs can integrate with a broad range of data sources so you can easily collect and analyze data.

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Nudge

Last, Nudge is a no-code tool for building native user experiences with a library of modules including Stories & Videos, Gamification & Rewards, and Surveys. You can use customizable templates for audience segmentation and native experiences with low latency. Nudge is designed to help teams improve user onboarding, feature adoption and overall engagement. It integrates with tools like Snowflake and Clevertap, so you can track and analyze user data for growth and retention.

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