Framed Data: AI-Powered User Retention for App Developers

YC-Backed Framed Data Helps Developers Understand User Behavior and Improve Retention

This article from TechCrunch, published on February 3, 2014, introduces Framed Data, a startup founded by Thomson Nguyen and Elliot Block. The company aims to simplify the complex process of understanding user behavior for app developers, even those without a dedicated data science team. Framed Data leverages machine learning to analyze user data, identify patterns, and provide actionable insights to increase user retention.

The Challenge of User Retention

In the rapidly growing mobile app market, acquiring users is only the first step. The real challenge lies in retaining them. With the average American user having 25 apps on their smartphone, developers face stiff competition for user attention. Framed Data addresses this by offering tools that help developers understand why users stay or leave, moving beyond simple metrics to uncover the human element behind user numbers.

Framed Data's Approach

Framed Data processes millions of data points monthly, using machine learning models to analyze user pathways. The platform can ingest data from various sources, including Mixpanel, Segment.io, SQL, HDFS, Mongo, and CSV files. It categorizes users based on factors like time zone, operating system, or device, and predicts their likelihood of continued engagement or abandonment. A key feature is its "tipping point analysis," which highlights the metrics developers need to achieve to improve retention.

Key Features and Differentiators

• Machine Learning for User Insights: Framed Data uses ML to identify valuable users and predict churn.
• Data Source Flexibility: Supports a wide range of data inputs, including popular analytics platforms and databases.
• Actionable Recommendations: Provides specific insights, such as identifying user groups likely to churn or the key actions that correlate with retention.
• Ease of Use: Designed for developers who may not have extensive data science expertise.
• Tipping Point Analysis: Helps developers understand the critical metrics for improving retention.

Founder Background

Founders Thomson Nguyen and Elliot Block met at UC Berkeley and later worked together at Causes, an online campaigning platform. Nguyen's background as a data scientist and Block's experience as a software engineer at Microsoft (where he worked on Office Web Apps) provide a strong foundation for Framed Data's technical capabilities.

Differentiating from Competitors

Compared to analytics services like Appsee and Flurry, Framed Data positions itself as more "opinionated." It aims to provide direct answers about user value, churn reasons, and potential churn indicators, rather than just raw data.

Target Market and Vision

Initially targeting consumer app and SaaS developers, Framed Data aims to democratize data science by making sophisticated analytics accessible to smaller businesses. The founders believe that by automating these processes, they can free up product managers to focus on implementing strategies like A/B testing or customer outreach, rather than getting bogged down in data engineering.

Real-World Insights

Framed Data's analysis has yielded both expected and surprising insights. For instance, it identified that users who adjust app settings upon first use are often tech-savvy. More intriguingly, for a photo app client, Framed discovered that user retention was strongly linked to social network integration, with users being more likely to stick around if at least seven friends joined within a month, even if they shared few photos.

The Future of Data Science and Framed Data

Nguyen emphasizes that while software can assist data scientists, it cannot fully replace human creativity. Framed Data aims to augment the work of data scientists by handling the more routine tasks of data modeling and engineering, allowing them to focus on higher-level strategic thinking. The company also plans to expand its services to larger enterprises like Comcast.

TechCrunch Events

The article also promotes "TechCrunch All Stage," an event focused on founders and VCs, offering strategies, workshops, and networking opportunities. The event is scheduled for July 15th in Boston, with registration available.

Related Topics and Keywords

The article touches upon various aspects of data science and technology, including:

• AI and Machine Learning: The core technology powering Framed Data's analysis.
• User Behavior Analysis: Understanding how users interact with applications.
• User Retention: Strategies and tools to keep users engaged.
• Data Science Platforms: Tools that provide data analysis capabilities.
• Startup Ecosystem: Framed Data's origin as a Y Combinator-backed startup.
• SaaS and Consumer Apps: The primary target markets.
• Data Engineering: The technical backbone required for data analysis.
• Predictive Analytics: Using data to forecast future user behavior.
• SEO Keywords: analytics platform, developer, Framed Data, Startups, user behavior, user retention, Y Combinator, data science, machine learning, AI, analytics, startups, consumer apps, SaaS, data models, retention rates, predictive analytics, data analysis, tech-savvy users, social network integration.

Images and Media

The article includes several images and logos, including the TechCrunch desktop and mobile logos, social sharing icons, a product screenshot of Framed Data, and a TechCrunch event banner.

Social Sharing

Links are provided for sharing the article on Facebook, Twitter, LinkedIn, Reddit, and via email, facilitating wider dissemination of the information.