The Anatomy of a Search Engine: Benchmarking Your Social App for Growth

The Anatomy of a Search Engine: Benchmarking Your Social App for Growth

In the world of technology and online platforms, two key areas of focus are search engines and social apps. While they may seem unrelated, there are common points that can be explored to understand how to improve both.

Search engines have come a long way since their inception in the mid-1990s. The first web search engine, World Wide Web Worm (WWWW), had an index of 110,000 web pages and documents. Fast forward to 1997, and the top search engines claimed to index millions of web documents. Altavista, for example, boasted that it handled around 20 million queries per day.

The goal of search engines has always been to improve the quality of search results. This led to the development of Google, which aimed to create an environment where researchers could process large amounts of web data and produce interesting results. One key aspect that Google introduced was the concept of PageRank, which measures the importance or quality of a web page based on the number and quality of links pointing to it.

PageRank can be seen as a model of user behavior, where a random surfer is given a web page and keeps clicking on links without hitting "back." The probability that the surfer visits a page is its PageRank. The damping factor, represented by the variable "d," determines the likelihood that the surfer will get bored and request another random page. This factor allows for personalization and prevents deliberate manipulation of the system for higher rankings.

On the other hand, social apps have their own set of metrics for benchmarking growth. The core metric for most consumer social apps is daily active users (DAUs). The goal is to have people using the app every day. For apps with less frequent use cases, weekly active users (WAUs) can also be a starting metric. However, eventually, DAUs become crucial for securing a spot on the home screen.

When it comes to user growth, organic growth is ideal for social apps. Paid marketing may be necessary at times, but if more than 10-20% of users are coming from paid sources, it indicates a need to rethink the acquisition strategy. The growth should primarily come from the product itself, as social apps should be inherently viral, with users inviting their friends to enhance the experience.

To benchmark DAU/MAU (Monthly Active Users), a ratio of 25% is considered okay, 40% is good, and 50% or more is great. Best-in-class social apps have an L-ness curve that "smiles" or has a "crooked smile" that skews right. This means that users are making the app a regular part of their lives. Weekly L-ness curve, specifically L5+ (users in the app five, six, or seven days a week), indicates near-daily use behavior. For L5+ performance, 30% is okay, 40% is good, and 50% or more is great.

Retention is a crucial metric for social apps. N-day retention, focusing on specific points in time such as day 1, day 7, and day 30, allows for evaluation of how many users continue using the app over time. Benchmarking for n-day retention shows that 50% on day 1, 35% on day 7, and 20% on day 30 is okay. Good performance is 60% on day 1, 40% on day 7, and 25% on day 30. Great performance is 70% on day 1, 50% on day 7, and 30% on day 30.

Weekly retention can also be relevant for companies transitioning from a tool to a network. In this case, the benchmark for week 1 is 40% and week 4 is 20% for okay performance. Good performance is 55% on week 1 and 30% on week 4. Great performance is 75% on week 1 and 50% on week 4.

While point-in-time numbers provide valuable insights, evaluating cohorts over time is even better. Stable or improving metrics cohort by cohort indicate strong network effects, where the product becomes more valuable as more users join.

In conclusion, understanding the anatomy of a search engine and benchmarking growth for social apps can provide valuable insights for improving both. Three actionable pieces of advice are:

1. Focus on organic growth and ensure that the product itself drives user acquisition.
2. Pay attention to retention metrics such as DAU/MAU ratio, L5+ performance, and n-day retention.
3. Evaluate cohorts over time to identify trends and ensure that the product's network effects are strong.

By implementing these strategies, businesses can enhance the quality of search engines and optimize the growth of social apps.