👀 Observation 1.2

According to the charts, it is clear that the Binance smart chain has the number of active users above 57 million (40.7% of all active users). While this amount in other chains, such as Ethereum, Algorand and Solana, is 42 and 13 and 11 million, respectively.

👀 Observation 2.2

According to the charts, it is clear that the Ethereum has the number of active NFT sellers above 1.29 million (37.7% of all active users).While this amount is 927 and 926 thousand in other networks such as Solana and Cosmos respectively.

❓How sticky are the users on Flow?

Create a detailed analysis comparing user retention on Flow vs. other L1 chains like Ethereum and Solana. How often do users who make a transaction come back and make another transaction one month later? How do monthly active users compare between chains?

Bonus: add a section of your analysis comparing retention specifically with regard to NFT purchases. How often do users who purchase an NFT come back and make another purchase one month later?

📝 Introduction

Why focus on retention and not growth?

It’s still early days for DeFi.

DeFi has the potential to touch all seven billion people on the planet – and there’s going to be a multitude of products to serve all kinds of use-cases. No one product can serve all needs. People are incredibly diverse – a small business owner in China has different financial needs compared to a college graduate in Canada about to join the workforce.

By all optimistic measures, there are about 100,000 end-users using DeFi today.

In my opinion, it’s still early for the mass-market to adopt DeFi. There are a large number of unsolved usability, privacy and security issues that need to be resolved before marketing to a broader userbase is justified. It’s not all doom-and-gloom either: on Ethereum there’s a clear solution path to many of these problems. I’m confident that we are going to have a different landscape in just under six months.

So, why not take the time to research/iterate to the needs, aspirations, motivations and pain points of your target customer base before starting to focus on growing that userbase?

When DeFi takes off, you will be ready to capture that user growth sustainably.

The recipe for product-market fit

Note: This recipe is more geared towards dApps and consumer facing apps rather than protocols. We will have another follow up post for pick-and-shovel products like protocols, layer 1 chains and other infrastructure products.

Have a narrow and clear definition of the customer. In the DeFi space, it can be along two dimensions: a persona (eg: investor, trader, user, developer) and a geo-location (eg: Asia, English-speaking world).
Identify a financial use-case for this customer. It could be one of the verbs like “borrow”, “trade”, “lend”, “bet”, “earn” (or “steal” 👿👿👿 – sorry couldn’t help myself.)
Build a prototype to solve for this use-case. At this stage you don’t need a logo or even a marketing website.
Recruit a cohort of 5 people who fit that persona. Only after you’ve satisfied this cohort should your proceed to recruit another cohort. The recruitment processs will also teach you repeateable customer acquisition skills.
Resist the temptation of new revenue streams and new features. If you try to serve everyone, you serve no one.
Establish a tight loop with that cohort. Tighter the loop, the better it is. My choice of tools are Twitter direct messages, WhatsApp and Telegram. If a person is not willing to sign up for that level of intimacy, then they are not desperate for a solution. Cut them out of this cohort and you can come back to them when your product is more mature.
Rinse and repeat. You also need to keep an eye on retention - 40% weekly retention is a good place to start. We write about measuring retention further down in this post.
If you’re not able to recruit a cohort of 5 people, or not able to reach your retention goal – you’ll have to make changes. Either change the target persona or change the product.

How to measure retention

As you progress with your iterations, you should start to see your user base grow cohort-over-cohort. A side benefit of this process is that it has the potential to kick start word of mouth effects, specially if you have a memeable narrative.

Now that you have a tight control over who gets to use your product, the second item to focus on is retention. Keeping a close eye on retention ensures that you are continuing to solve a problem that’s critical to your customer’s workflow. If there’s only light usage, they’ll forgot about your product and either stop using it entirely or switch back to their previous workflow or another competing solution.

✍🏻 Methodology

In this dashboard, i use this table:
- flow.core.fact_transactions , Ethereum.core.fact_transactions , terra.core.fact_transactions , bsc.core.fact_transactions , avalanche.core.fact_transactions , algorand.core.fact_transaction , near.core.fact_transactions , solana.core.fact_transactions , cosmos.core.fact_transactions→ used for checking average between time difference in Flow , Ethereum , Terra , BSC , Avalanch , Algorand , Near , Solana and Cosmos blockchain transactions.
- flow.core.fact_nft_sales , Ethereum.core.fact_nft_sales , terra.core.fact_nft_sales , algorand.nft.fact_nft_sales , solana.core.fact_nft_sales → used for checking average between time difference in Flow , Ethereum , Terra , Algorand , Solana blockchain NFT sales.

📃 Purposes of dashboard

In this dashboard, time difference analyzed in some L1 blockchain at transaction and nft sales :

Average time difference between transaction on Flow , Ethereum , Terra , BSC , Avalanch , Algorand , Near , Solana and Cosmos.
Monthly count of active user at each chain.
Total count of active user at each chain.
Average time difference between Nft sales on Flow , Ethereum , Terra , Algorand , Solana chain.
Monthly count of active NFT seller at each chain.
Total count of active NFT seller at each chain.

Part 1 : Transactions

🟡 Part(1.1).Average time difference between transaction on Flow , Ethereum , Terra , BSC , Avalanch , Algorand , Near , Solana and Cosmos.

🟡 Part(1.2).Total and Monthly count of active user at each chain.

Part 2 : NFT Sales

🟡 Part(2.1).Average time difference between Nft sales on Flow , Ethereum , Terra , Algorand , Solana chain.

🟡 Part(2.1).Total and Monthly count of active NFT seller at each chain.

👀 Observation 1.1

On the above charts as we see:

the average time difference between the transactions on ==Flow== chain users is between 2 weeks till 1 month and the next ranks belong to the users with 1 till 3 months and Less Than 1 Hour time difference between their transactions.
the average time difference between the transactions on ==Ethereum== chain users is between 1 till 3 months and the next ranks belong to the users with Less Than 1 Hour and 2 weeks till 1 month time difference between their transactions.
the average time difference between the transactions on ==Terra== chain users is between Less Than 1 Hour and the next ranks belong to the users with 2 weeks till 1 month and 1 till 3 months time difference between their transactions.
the average time difference between the transactions on ==Binance smart chain== chain users is between 1 till 3 days and the next ranks belong to the users with Less Than 1 Hour and 1 hours till 1 days time difference between their transactions.
the average time difference between the transactions on ==Avalanch== chain users is between Less Than 1 Hour and the next ranks belong to the users with 1 hours till 1 days and 1 till 3 days time difference between their transactions.
the average time difference between the transactions on ==Algorand== chain users is between Less Than 1 Hour and the next ranks belong to the users with 1 hours till 1 days and 1 till 3 months time difference between their transactions.
the average time difference between the transactions on ==Near== chain users is between Less Than 1 Hour and the next ranks belong to the users with 1 till 3 months and 1 hours till 1 days time difference between their transactions.
the average time difference between the transactions on ==Solana== chain users is between Less Than 1 Hour and the next ranks belong to the users with 1 till 3 months and 3 till 6 months time difference between their transactions.
the average time difference between the transactions on ==Cosmos== chain users is between 2 weeks till 1 month and the next ranks belong to the users with 1 till 2 weeks and 1 till 3 months time difference between their transactions.

👀 Observation 2.1