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.