What this article focuses on -

• crowd funding announcement

• using statistics/ML to measure a way to increase retention

• general growth metrics of farcaster

Crowd funding

Purpose - I'm analyzing Farcaster data to help builders grow high-quality users and retention through data analysis and statistical modeling. My research will be shared openly to benefit the entire Farcaster community.

Kinds of Questions i am looking to answer -

• Which activities increase quality user retention on Farcaster (e.g., welcome messages)

• Impact of airdrops on user engagement and retention

• Correlation between onchain activities (token/NFT holdings) and social behaviors

• Data-driven strategies for maximizing quality user growth

• etc

i will try to answer as many questions as i can working full time.

Why builders should care -

Builders want more high-quality users on Farcaster for their projects. By looking at the data from all the possible angles, they will have an easier time in deciding what THEY can do to maximize quality user growth. I believe that there is a lot on the table has not yet been explored from which builders could learn and explore.

My ask -

I believe that farcaster does have the potential to be the next big thing if done right. Which is why i believe that investing my time in Farcaster is the best course of action. i have been analyzing farcaster's data for almost 2 years however it would be impossible for me to go full time in analyzing Farcaster if i can afford to sustain myself.

If my crowdfunding reaches $2,000, I'll dedicate myself full-time to analyzing Farcaster data for a month, with the option to continue further.

Donate to the crowd fund here - https://warpcast.com/yesyes/0xb27126f1

I will weekly share all the insights i find in the form of an article such as one below(but more detailed) -

Impact of quoting/tagging a new user

rish asked me to check the retention of people onboarded by big accounts. I decided to check that. But then i realized that i could also just generally check the impact of mentioning or quoting someone in their first week joining. This will be helpful in deciding whether it's a good idea to pursue this behavior or not. So i decided run some analysis on that -

I check for those fids that were mentioned or quoted by a user in their first week of registering. And then i check whether they had casted after 30 days(but before 60 days). This analysis only takes into consideration those fids that casted at least once in their first week of joining. This contains fids from 100k to 900k for individual analysis.

Let's look at the performance of some top accounts -

interesting that linda had 21 users mentioned for sub 800k fids(and still 20 retained users. meaning the 4 users from 800k to 900k were not retained at all)

It's generally safe to say being that tagged or quoted by a big account greatly increases their chances of sticking around.

The general MoM casting retention of a new account is about 65%(see retention details later)

Now, Taking analysis this to a more general level -

I looked at the data of fids from 100k to 800k FID (FIDs 801k to 900k were left out for testing and cross-validation purposes in future analyses.). The fids that casted in the first week of joining were considered in this analysis. There were a total of 327,788 fids.

Out of these -

• 109k were mentioned or tagged by another user in the first week

• 218k were not mentioned or tagged by another user in the first week

out of the 109k tagged users

- 75k casted at least once after a month

- 33k did not cast even once between the 30 to 60 days.

out of the 218k non-tagged users

- 122k casted at least once after a month

- 95k did not cast even once between the 30 to 60 days.

Looking at the retention from this -

Those that were mentioned had a retention rate of 69%. Those who weren't mentioned had a retention rate of 56%.

Presenting the data in tabular form -

• Users who were mentioned or tagged by others in their first week showed a 13.2% higher retention rate compared to those who weren't mentioned

• While mentioned users represent only one-third of new users, they account for 38.1% of retained users

Given the large size, it is safe to say that this difference in rates is statistically significant. However, i will further perform chi-squared test and logistic regression to further understand how significant the difference is and whether mentioning people early should be encouraged more.

Chi Squared test

Here is the contingency table for the above data -

Null hypothesis - There is no significant association between being mentioned in the first week and activity after a month.

Skipping the calculation part, Here are the results of the chi-square test -

Chi-Square Test Results: Chi-Square Value: 5277.2128

P-Value: 0.000...(far less than 0.05)

Cramer's V: 0.1269

What this essentially means is that since p-value is much lower than 0.05 then it is safe to say that there is a significant association between being mentioned in the first week and activity after a month.

(hence we reject the null hypothesis)

However, a low cramer v value suggests that the association is not too strong.

Logistic Regression

I also decided to run logistic regression on the data to determine a rough increase in odds after being mentioned/tagged in the first week of joining.

Here are the results of training the model

Here is the odds ratio - 1.7635

what this essentially means is that users who were mentioned in their first week are 1.76 times more likely to be active after a month compared to users who were not mentioned. This represents a 76.35% increase in the odds of being active.

Conclusion of the analysis

Overall, it is obvious that quoting/tagging someone in the first week of their joining increases their likelihood of being retained a month later. The difference it makes is statistically significant though not super substantial.

Still, it is advisable to quote/tag a new user if you want them to stick around. It will definitely help in retaining them.

General metrics

Now, let's look at some general metrics regarding Farcaster's growth.

DAUs return back to their baseline

The DAU figure seems to have returned to baseline after seeing a nice spike in March. The spike was caused by new and returning users(because the storage rents also went up but not that much).

This spike was most likely caused by the aggressive marketing push by Farcaster. Stuff like 'Make money on Farcaster' and the push for airdrops brought eyeballs towards farcaster.

Unfortunately, These users weren't very sticky and faded after a while. Understanding why these users left could be key to understanding how to make Farcaster grow.

new user storage rents show a troubling picture

New user sign ups are at the lowest point since going permissionless. This is a bit concerning. What's interesting to note is that Farcaster seems to have switched from 'make money on farcaster' to advertising its mini-app ecosystem as well its builder friendly nature. So perhaps, this marketing will pay off more in the long term.

General MoM retention -

Notice that caster cohorts are getting big again after being tiny around october. The retention of the recent cohorts seem strong but this does not yet include April data which will probably shed some important light on the retention of these cohorts.
We will soon be revisiting this chart with April data. Stay subscribed for that!

This was a demo article for my crowd fund. I hope to release longer, more frequent articles with deeper insights if i get crowd funded. Please consider crowd funding if you found this article insightful and want more insights like these.