What is Retention?

User retention refers to the ongoing utilization of a product or feature. To assess overall retention, it is crucial to establish clear criteria for what constitutes user engagement, such as logging in, accessing a specific page, or performing essential actions. When measuring the retention of a particular feature, it is helpful to consider individuals who have used it at least once. The metrics used in this analysis aim to determine if the feature successfully retains these users. User retention is a reliable and unbiased measure of user behavior, making it a trustworthy and valid indicator.

Introduction

Cohort analysis is a powerful tool for measuring user retention by categorizing data into groups with shared characteristics before conducting analysis. It helps organizations isolate, analyze, and identify patterns in the user lifecycle, ultimately improving user retention and gaining a deeper understanding of user behavior within specific cohorts.

To better illustrate how cohort analysis works, let's consider an example from Bill Su:

Imagine you have a customer named Bob who discovered your online store four months ago when you offered a 50% discount. Bob browsed through your products and purchased a small trial set of avocado cosmetics [1].

As a business owner, you naturally wonder if customers like Bob return to your store as a result of their initial trial set purchase. To answer this question, you instruct your store attendant (named "Cookie") to track the behavior of customers similar to Bob and monitor whether they come back and make subsequent purchases, as well as the frequency of their returns.

In this scenario, the group of customers attracted by the 50% discount, including Bob, forms a cohort. The objective is to analyze whether these customers continue to revisit the store on a monthly basis.

Here's a real-world example of how cohort analysis can be used: Suppose you have an app, and you want to measure the number of users who initially launch the app and then revisit it within the next 10 days. By employing cohort analysis, you can track and analyze this specific behavior to gain insights into user retention and engagement patterns.

Cohort analysis enables businesses to assess the effectiveness of various acquisition strategies, evaluate the impact of specific events or promotions on user behavior, and make data-driven decisions to optimize user retention efforts.

From the above retention table — Triangular chart, we can infer the following

• 1358 users launched an app on Jan 26. Day 1 retention was 31.1%, day 7 retention was 12.9%, and day 9 retention was 11.3%. So on the 7th day after using the app, 1 in 8 users who launched an app on Jan 26 were still active users on the app.

• Out of all of the new users during this time range (13,487 users), 27% users are retained on day 1, 12.5% on day 7, and 12.1% on day 10.

Cohort Analyze in Blockchain

The blockchain industry boasts an abundance of blockchains and decentralized applications (dApps). Nowadays, with the prevalence of EVM compatible Layer 1 (L1) blockchains, one can observe the widespread deployment of similar dApps across multiple platforms. Consequently, the growth of an L1 blockchain is contingent not only upon attracting users but also on their sustained retention month after month. To achieve continuous expansion and success, L1 blockchains must prioritize strategies that focus on retaining users throughout extended periods.

Methodology

What is a cohort? — In this analysis, I’m considering the users who joined in a particular month (i.e. the month in which the first transaction was done) as part of the same cohort. Then, I calculate how many of these users are transacting again in the next months.

What does the cohort size show? — The cohort size for each month shows how many new users joined that L1 in that month.

How to read the tables? — To read the tables, start with the month name in the “Cohort” column and then add the month number in the “Month 1, 2, 3 …” columns. E.g. Cohort of April ‘22 will have June ’22 as Month 2.

Flow

Let's dive into the data for Flow, specifically focusing on the period starting from January 2022, as captured in Flipside's tables.

• In January, an analysis reveals that 37% of the users from that cohort continued to use Flow in February. However, as we progress beyond February, the retention rate experiences a decline, dropping to 29%. This downward trend persists, and by the end of 12 months, only 12% of the initial users from January remain actively engaged with the platform.

• Shifting our attention to the February cohort, we observe a similar pattern. Only 60% of the users from this cohort were retained in the subsequent month, with the retention rate dwindling to a mere 12% after 12 months.

• June was a weird month for Flow, so that five months later, 80% of users returned to Flow, while one month later, only 1% of them stayed with Flow.

• In November, something changed, while a huge number of new users came to Flow, only one percent of them came from the previous month.

These findings highlight a significant decrease in user retention for both cohorts as time progresses.

Ethereum

Let's shift our focus to Ethereum and explore a similar time period as we did with Flow.

• The January cohort stands out as the largest, comprising 5.4 million wallets. Over the course of 12 months, the cohort remains relatively stable, with approximately 5.1 million wallets still active from the January cohort.

• When it comes to retention rates, Ethereum demonstrates a lower level compared to Flow. In the first two months, only 33% of the January and February cohorts are retained. By the sixth month, the retention rate drops to nearly 19%, and after 12 months, it reaches 10%.

• As we examine the March cohort, the retention rate declines further to 12% in the ninth month and eventually settles in the high single digits in the subsequent months.

While Ethereum's initial retention is a little lower compared to Flow, the retention levels has experienced lower volatility. This suggests that Ethereum faces challenges in retaining users over the long term and may need to focus on strategies to improve user engagement and retention beyond the initial months.

Avalanche

Let's dive into the data for Avalanche, similarly focusing on the period starting from January 2022.

• In January, an analysis reveals that 45% of the users from that cohort continued to use Avalanche in February. However, as we progress beyond February, the retention rate experiences a decline, dropping to 34%. This downward trend persists, and by the end of 12 months, only 9% of the initial users from January remain actively engaged with the platform.

• Shifting our attention to the February cohort, we observe a similar pattern. Only 47% of the users from this cohort were retained in the subsequent month, with the retention rate dwindling to a mere 10% after 12 months.

Although these findings highlight a significant decrease in user retention for both cohorts as time progresses in Avalanche, in comparison with Flow, its retention rate is so much better and its users are more loyal than Flow users.

Polygon

Now let's turn our attention to Polygon and examine the same time period starting from 2022. As we analyze the data, several noteworthy observations emerge:

• In the cohort table's first row, we notice that the monthly cohort sizes for Polygon are considerably smaller compared to Ethereum.

• However, what stands out is the significantly higher user retention for Polygon in the subsequent months. For instance, in the second month, the retention rate for the February '22 cohort is 45%, surpassing Ethereum's 33%. Moreover, the retention rate from February to March is nearly twice as high as Ethereum's and slightly lower than Avalanche's, demonstrating a strong retention trend.

These findings indicate that while the initial cohort sizes for Polygon may be smaller than Flow and Ethereum, Polygon exhibits higher user retention rates in the following months. This suggests a potentially more engaged and loyal user base on the Polygon network, which could be attributed to factors such as improved user experience, unique features, or targeted user acquisition strategies.

Cosmos

Finally we looked at Cosmos user retention over the same period time:

• In the cohort table's all row, we notice that the monthly cohort sizes for Cosmos are considerably higher compared to all above chains.

• However, what stands out is the significantly higher user retention for Cosmos in the consecutive months. For instance, in the second month, the retention rate for the February '22 cohort is 58%, surpassing all Polygon’s 45%, Avalanche's 47% and Ethereum's 33%. Moreover, the retention rate from February to March is over twice as high as Ethereum's and significantly lower than Flow's, demonstrating a strong retention trend.

These findings indicate that while the initial cohort sizes for Cosmos may be smaller than Flow in some few months, Cosmos exhibits significantly higher user retention rates in the following months. This suggests a potentially more engaged and loyal user base on the Cosmos network, which could be attributed to factors such as improved user experience, unique features, or Inter-Blockchain Communication (IBC) and targeted user acquisition strategies.

Conclusion

Based on the provided information, let's compare Flow's user retention rates with the other assessed blockchains:

1. Ethereum: Flow's user retention rates appear to be lower than Ethereum. While both platforms experience a decline in retention over time, Ethereum's retention rates are relatively higher at each milestone. Flow may need to focus on improving user engagement and retention efforts to match Ethereum's performance.

2. Avalanche: Flow's user retention rates are lower than Avalanche. Avalanche demonstrates higher retention rates in the subsequent months compared to Flow. Avalanche's users appear to be more loyal and engaged with the platform. Flow could benefit from studying Avalanche's retention strategies to improve its own user retention.

3. Polygon: Flow's user retention rates are lower than Polygon. Despite starting with smaller cohort sizes, Polygon exhibits higher retention rates in the following months. Polygon's users show stronger engagement and loyalty. Flow could explore the factors contributing to Polygon's success and implement similar strategies to enhance its user retention.

4. Cosmos: Flow's user retention rates are lower than Cosmos. Cosmos demonstrates significantly higher retention rates compared to Flow. Cosmos attracts larger cohort sizes and exhibits strong retention trends. Flow could analyze Cosmos' strategies and user experience to improve its own retention efforts.

In comparison to the assessed blockchains, Flow's user retention rates appear to be relatively lower. Flow may need to focus on implementing effective user engagement and retention strategies to enhance its user loyalty and retention rates. By learning from the success of Ethereum, Avalanche, Polygon, and Cosmos, Flow can aim to improve its retention metrics and foster long-term user engagement on its platform.

key takeaways

1. Retention Variation: The analyzed blockchains, including Flow, Ethereum, Avalanche, Polygon, and Cosmos, exhibit varying levels of user retention over time. Each blockchain platform has its own strengths and challenges in retaining users beyond the initial months.

2. Flow's Challenges: Flow, in particular, faces challenges in retaining users over the long term. The retention rates for Flow cohorts decline steadily over time, indicating a need for improved user engagement and retention strategies.

3. Ethereum's Moderate Retention: Ethereum demonstrates moderate user retention rates compared to the other blockchains assessed. While its initial retention may be lower than some, it experiences relatively stable retention levels over the 12-month period.

4. Avalanche's Better Retention: Avalanche showcases better user retention rates compared to Flow and Ethereum. Although there is a decline in retention over time, Avalanche retains a higher percentage of users at each milestone, indicating a more engaged and loyal user base.

5. Polygon's Strong Retention Trend: Polygon exhibits strong retention trends, surpassing Ethereum's retention rates. Despite smaller cohort sizes initially, Polygon shows higher user retention in the subsequent months, suggesting a more engaged and loyal user base.

6. Cosmos' High Retention: Cosmos stands out with significantly higher user retention rates compared to all the assessed blockchains. It retains a larger percentage of users in the consecutive months, indicating a highly engaged and loyal user base.

7. Importance of User Engagement: The findings emphasize the importance of effective user engagement and retention strategies for blockchain platforms. Building a loyal and engaged user base is crucial for long-term success and growth.

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