Paul1804
commented
8 months ago the comrade writes very right things !
Open venezuela01 opened 8 months ago
Paul1804
commented
8 months ago the comrade writes very right things !
venezuela01
commented
7 months ago venezuela01
commented
7 months ago Quote from Google Play Console's definition of user metrics:
| Metric | Definition |
|---|---|
| Users | An individual Google Play user; a user may have multiple devices. |
| Active users | The number of users who have your app installed on at least one device and have used the device in the past 30 days. |
| New users | Users who installed your app for the first time. |
| All users | New and returning users. |
| Active devices | The number of active devices on which your app is installed. An active device is one that has been turned on at least once in the past 30 days. |
| All devices | New and returning devices. |
| Daily Active Users (DAU) | The number of users who opened your app on a given day. |
| Monthly Active Users (MAU) | The number of users who opened your app in a rolling 28-day period. |
It's important to note that Google's official definition includes some wording that could be confusing.
Active users refers to users who 'use the device', whereas Monthly Active Users are described as users who 'open the app'.
venezuela01
commented
6 months ago Update 2023-12-21
| Source | DAU | MAU | DAU/MAU Ratio |
|---|---|---|---|
| Official number from OPTF (Synthesis Formula) | - | over 900K | - |
| Estimation using storage server | 144K | 842K | 17.1% |
venezuela01
commented
5 months ago Update:
| Month | Average DAU (90% CI) | MAU (90% CI) | DAU/MAU Ratio | Source |
|---|---|---|---|---|
| 2024-01 | 151,040 to 160,000 | 905,472 to 937,984 | 16.7% to 17.6% | 5 Storage Servers |
| 2024-02 | 160,512 to 163,840 | 920,576 to 974,336 | 16.6% to 17.6% | 5 Storage Servers |
| 2024-03 | 144,896 to 151,808 | 920,064 to 957,696 | 15.4% to 16.3% | 5 Storage Servers |
| 2024-04 | 148,480 to 157,952 | 923,648 to 1,001,728 | 15.0% to 16.2% | 5 Storage Servers |
| 2024-05 | 134,144 to 149,504 | 847,360 to 978,432 | 14.8% to 15.8% | 5 Storage Servers |
| 2024-06 | 134,912 to 148,992 | 906,240 to 970,240 | 14.2% to 15.4% | 5 Storage Servers |
Notes:
namespace, mixing 1-1 messages and closed group messages, which resulted in a 1% to 3% inflation in prior statistics. Statistics since March 2024 rectify this issue by applying a filter on namespace to exclude closed group messages and keys.
DDOXEN
commented
5 months ago Great
venezuela01
commented
5 months ago KeeJef: That data is 4 months old and the line underneath mentions DAU is 126k, also data taken from a single snode and extrapolated
@KeeJef @jagerman I have latest data from 5 nodes if you read my comment last week.
Session User Engagement Report
Edit: read https://github.com/oxen-io/oxen-improvement-proposals/issues/60#issuecomment-1921187399 for latest update.
Introduction
This report provides a detailed analysis of user activity statistics sourced from the
storage.dbof the Oxen Storage Server, with data fetched in the end of October 2023. The report delivers an exhaustive review of user engagement, showcasing metrics for Monthly and Biweekly Active Users at both the individual server and the network-wide scale. It also emphasizes the distribution of user activity, indicating that the top 15% of the most active users account for more than 80% of the message traffic, thus demonstrating a pronounced manifestation of the Pareto distribution.Data Preparation
storage.dbwas procured.pubkey_to_swarm_space_position()function, in conjunction with the methodology outlined in Oxen Storage Server Issue #470, was employed to filter out outdated messages. This step is essential to bypass a known bug and to avoid overestimating the number of active users on a single storage server.Monthly Active User (MAU)
On a Single Storage Server
By ensuring that no obsolete messages were included and by conducting a thorough data cleanup, we were able to tally distinct owner IDs in the message table. Our server interacted with 2,961 active users for the month.
Network-Wide Estimation
To approximate the Monthly Active Users across the entire network, we calculated the swarm space coverage ratio of our storage server.
The ratio was determined by:
swarm_space_positionusingpubkey_to_swarm_space_position()swarm_space_positionand identifying the minimum and maximum valuesswarm_space_positionby2^64, where the denominator denotes the total swarm space.Consequently, we deduced that our server covers 1/256 of the network space.
By extrapolation, we estimate the network comprises 758,016 (758k) Monthly Active Users (2,961 multiplied by 256).
Edit: Starting from 2024-02-01, we no longer use the min-max estimation for swarm width. Instead, we use the
get_service_nodesJSON-RPC call to obtain all swarm IDs of all nodes and calculate the precise swarm boundaries. The results are almost the same as those obtained through the min-max estimation approach, but the precise approach via JSON-RPC is more sensitive in detecting swarm bugs, allowing us to intervene manually when necessary.Biweekly Active User Analysis
We dive deep into biweekly active users because regular user messages have a 14-days Time-To-Live (TTL). Regular user messages were extracted by filtering messages according to their TTL value. This procedure enabled us to focus on regular user messages and to exclude configuration messages.
The refined dataset contained 283,365 messages from 1,917 users over a biweekly span.
Network-Wide Projection
Applying the same coverage ratio as before (1/256), we project that there are approximately 490,752 Biweekly Active Users network-wide. The same scaling factor is applied in the following analysis.
Pareto Distribution of User Activity
Note on Message Ownership: In the current design of Session, when a user sends a message, a copy is also sent to their own swarm; when a user receives a message, their swarm receives the message. The term 'owning' a message encompasses both sending and receiving; this adds a layer of complexity to the analysis, which we will simplify for the moment by aggregating all such activities under general user engagement.
Distribution of Message Ownership Among Users
Our analysis of user behavior within the network has revealed a pronounced imbalance: a relatively small fraction of users are engaged with a disproportionately large share of messages. This aligns with the Pareto Distribution, which suggests that a small number of individuals often account for a large portion of the effects.
The following table illustrates the cumulative percentage of active users in comparison to the cumulative percentage of messages they are engaged with:
This data indicates that in a two weeks span, about 3.5% of the most active users engage with 50% of the messages, and around 15.2% of users account for about 80% of the messaging activity. A similar distribution was noted when analyzing the data based on message storage size instead of message count.
Distribution of User Activity Across Time Buckets
To better understand how often users are active, we split two weeks' worth of messages into 14 daily groups. We tracked how many days each user engages. Then, we group users with the same number of active days together and counted number of users in each group.
The results are displayed in a Pareto chart reflecting user activity frequency.
Our findings show that, out of 491k biweekly active users, 200k (approximately 40%) were active on only one of the 14 days, 83k were active on two days, and so on. Only 15k users consistently engage with Session everyday. It's crucial to distinguish this 15k figure from the Daily Active Users (around 126k DAU) metric, which measures the number of unique users who interact with the app within a 24-hour interval, without any guarantee of their return the following day.
It is also noteworthy that with 758k monthly active users and 491k biweekly active users, there are approximately 267k users who have periods of inactivity exceeding 14 days. This raises a concern that they may miss messages due to the 14-day Time-To-Live (TTL) policy.
Daily Active Users (DAU)
We splitted messages into 14 time-based buckets and calculated the number of daily active users. After scaling up with a factor of 256, we extrapolate a DAU between 111,616 and 137,472 on a network-wide basis. On average, we estimate there are approximately 126,244 daily active users across the network.
DAU / MAU Ratio
The DAU/MAU ratio is a key performance indicator that measures user retention and engagement. For our network, this ratio is calculated as follows: 126,244 / 758,016 = 16.7%.
Comparative Analysis with Other Products
We compare the DAU/MAU ratio of Session with other products:
Session's DAU/MAU ratio is considerably lower than the industry average, potentially signaling its immaturity. This is further supported by the current average rating of the Session Android app, which stands at approximately 3.6, lagging behind the overall average app rating of 4.0 as reported by AppBrain.
Insights and Considerations
Cross-validation of User Statistics: The official number of monthly Session users is reported using a synthesis formula approach. It would be beneficial to cross-validate this method with other approaches and calibrate parameters as necessary. A discrepancy between different metrics does not necessarily mean one is incorrect. For instance, if the synthesis formula by OPTF yields a higher user count than the Oxen storage server data, it could be that many users download the Session app but struggle with account creation or finding friends to communicate with. Another possibility is that a significant percentage of users are using multiple devices, which would be counted only once when calculated using Oxen storage server data.
Community Perception vs. Official Figures: Persistent doubts among community members regarding their perception of the number of Session users compared to official figures may find some explanation in our Pareto distribution analysis. The most active 3.5% of biweekly users (approximately 17k out of 491k) account for 50% of the messages, which corresponds closely with the 15k users consistently engage everyday, yet this figure is much lower than the total MAU. Moreover, the DAU/MAU ratio for Session is notably lower than what is typical in the industry, which may contribute to the community's perception of a smaller user base.
Potential for Monetization: The concentration of activity among a small group of users suggests that we may be closer to achieving monetization than previously considered. If we target the most enthusiastic users and address their common pain points, monetization could be promissing. Assuming that the willingness to pay correlates with user engagement, the most enthusiastic 17k users, representing 3.5% of biweekly or 2.3% of monthly users, might be willing to pay $5 per month. This could potentially generate close to $1 million in annual revenue.
Openness to New Features: The same group of highly active users may also be more open to trying new features, such as making payments in Oxen. Their willingness to engage with new aspects of the platform could be crucial for the success of Oxen.
Privacy Risks with Token Changes: The significant concentration of activity among a small subset of users raises concerns about the increased risk of deanonymization if the Oxen coin is replaced by a transparent token. If the most active users correlate highly with those most willing to pay, then introducing Session Monetization with a transparent token could either significantly inconvenience these active users or substantially elevate the risk of deanonymization for core users. These core users, who most require privacy, are comparable to the hubs or critical nodes within the network. Making privacy transactions optional would be akin to eliminating mandatory onion routing from the Session network. Should the privacy of these core users be breached, the fallout could extend to their contacts, potentially compromising the privacy of a significant proportion of the network. For further details, see Privacy Implications of Replacing the Oxen Privacy Coin in the ONS Registration Process.
Appendix: Synthesis Formula of MAU from OPTF
Source: https://t.me/Oxen_Community/381121