The Intersection of Benchmarking Social Apps and the AI Revolution

The Intersection of Benchmarking Social Apps and the AI Revolution

Introduction:

In the fast-paced world of technology, two major trends have emerged that are reshaping industries and pushing boundaries. Benchmarking social apps and the rise of artificial intelligence (AI) have become focal points for startups and established companies alike. While they may seem like separate domains, there are intriguing connections between them. In this article, we will explore the core metrics for benchmarking social apps and how they relate to the potential of AI in various industries.

Benchmarking Social Apps:

When it comes to benchmarking growth in social apps, the first step is to define the core metric. For most consumer social apps, the metric revolves around daily active users (DAUs). The goal is to have people using the product every day, making it an integral part of their lives. However, for apps with less frequent use cases, weekly active users (WAUs) can be an acceptable starting metric. Ultimately, the aim should be to upgrade to DAUs if the app wants to secure a coveted slot on the home screen.

Organic Growth and User Acquisition:

In the world of social apps, organic growth is highly desirable. It signifies that users are naturally drawn to the product and are actively inviting their friends to join. On the other hand, if a significant portion of users are coming from paid sources, it may indicate a flaw in the product or acquisition strategy. No amount of marketing dollars can fix a product that lacks inherent value. Therefore, it is crucial to ensure that growth primarily stems from the product itself.

DAU/MAU Ratio and User Retention:

The ratio of daily active users to monthly active users (DAU/MAU) is a critical metric to gauge user engagement. A healthy DAU/MAU ratio indicates that users are regularly using the app, making it an essential part of their lives. Benchmarks for DAU/MAU ratios can vary, but a ratio of 50% or higher is considered great.

Retention is another crucial aspect of benchmarking social apps. N-day retention, focusing on specific points in time such as day 1, day 7, and day 30, provides insights into user stickiness. Retention benchmarks can range from 20% to 70% depending on the timeframe. It is important to note that the slope of the retention curve tends to flatten after day 7 and plateau around day 20.

The Connection to AI:

While benchmarking social apps focuses on user growth and retention, the AI revolution has introduced transformative possibilities across industries. The emergence of Transformer models in natural language processing (NLP) has paved the way for large language models (LLMs) like GPT-3. The ability of machines to interpret and act on language-based information has the potential to revolutionize enterprises.

Applications of LLMs are already visible in code generation, sales and marketing tools, enhanced search, and interactive chatbots. The challenge for startups lies in determining whether to create a de-novo product/market or integrate AI into existing solutions. Experimentation and iteration are key in this process, as startups must adapt to the evolving landscape.

The Future of AI:

The potential of AI extends beyond social apps and into industries such as healthcare and law. AI-powered assistants could replace certain tasks performed by doctors and lawyers, streamlining processes and improving efficiency. However, the degree to which challenges in AI are scientific or engineering problems remains a topic of debate. Advances in algorithms, architecture, and semiconductor innovation will play crucial roles in realizing the full potential of AI.

Conclusion:

Benchmarking social apps and the AI revolution are two significant trends shaping the tech industry. By understanding core metrics for growth and retention in social apps, startups can strive for organic growth and user engagement. Simultaneously, the rise of AI, driven by large language models, opens doors to transformative possibilities across various sectors. To leverage these trends successfully, startups should focus on iteration, experimentation, and tapping into the potential of AI to create innovative solutions.

Three Actionable Advice:

• 1. Prioritize organic growth: Focus on creating a product that users naturally gravitate towards. Build features that encourage users to invite their friends and make the experience even better.

• 2. Embrace experimentation: Don't be afraid to try new approaches and iterate quickly. Startups thrive on innovation and learning from failures.

• 3. Stay informed and adaptable: Keep up with the latest advancements in AI and understand how they can be applied to your industry. Be open to reimagining existing solutions and incorporating AI technologies to stay ahead of the curve.

The future holds immense possibilities for benchmarking social apps and the integration of AI. By staying attuned to industry trends and harnessing the power of technology, startups can unlock their full potential and drive meaningful change.