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Zachary Perret engagement report

@zachperret - 574K followers on X

Measured over 2 original posts from a 30-day window, last computed on August 26, 2026.

Engagement

Per follower
0.012%
of 574K followers
Per impression
0.22%
32K views on a typical post
Reach
5.59%
of its followers see a post
Typical post
70
interactions (median)
Saved
0.016%
5 bookmarks on a typical post
Posting rate
0.1/day
active 10% of days
Peak time
04:00 UTC
Monday

Early reading. We have captured 2 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 70 interactions against 574K followers, an engagement rate of 0.012%. Posts are seen about 32K times each, and 0.22% of those impressions turn into an interaction. That is about 5.59% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.1 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 04:00 UTC, and Monday is the busiest day of the week. Of the 2 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 4.3K interactions, about 61x its own typical post. Only 2 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 2 original posts from a 30-day window, last computed on August 26, 2026.

Where this sits in the catalog

At 0.012%, Zachary Perret sits above the 25th percentile of the 36,960 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.

p100.002%
p250.012%
p50 (median)0.08%
p750.435%
p902.10%
p99159.8%
Engagement rate as a share of followers, across the 36,960 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 106,518 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.435%
90th percentile2.10%
99th percentile159.8%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 04:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 04:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 04:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%51K
01:00 UTC-2%52K
02:00 UTC-3%51K
03:00 UTC-4%54K
04:00 UTC-6%44K
05:00 UTC-4%42K
06:00 UTC-4%49K
07:00 UTC-5%53K
08:00 UTC-4%61K
09:00 UTC-3%70K
10:00 UTC-2%73K
11:00 UTC-3%79K
12:00 UTC-2%87K
13:00 UTC-2%96K
14:00 UTC-4%99K
15:00 UTC-2%102K
16:00 UTC-3%99K
17:00 UTC-2%92K
18:00 UTC-1%85K
19:00 UTC-2%80K
20:00 UTC-1%75K
21:00 UTC-1%67K
22:00 UTC-2%58K
23:00 UTC-1%52K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%233K
Monday0%292K
Tuesday-3%284K
Wednesday-1%253K
Thursday-2%246K
Friday-3%255K
Saturday+3%229K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Jan 22, 202661x their median

    Given some rumors, wanted to post a few clarifications: Farcaster is not shutting down. The protocol works and will continue to work. There were 250,000 MAU in December and over 100,000 funded wallets. The acquirer, Neynar, is a venture-backed startup and plans to shift Farcaster in a more developer-focused direction. As for Merkle, we’re planning to return the full $180M raised back to investors. Over the last 5 years, we tried to be a good steward of investor capital. Finally, I bought my house with Coinbase IPO proceeds.

    3.3K2785591871.2M viewsView on X
  • Jun 3, 202617x their median

    Today, we’re launching @TownAI: the AI assistant that learns you. We’re coming out of beta with a $55M Series A led by @ARampell at @a16z, with participation from @KirstenGreen at @forerunnervc and continued support from @firstround, @altcap, and @conviction. Right now, getting real value from AI means prompting, configuring, building workflows, managing agents. We think that’s backwards. The future of AI is a companion that already knows you and how you work. Town connects across your inbox, calendar, Slack, docs, messages, and workflows to understand what you need, then starts doing the work with you. Drafting. Scheduling. Project tracking. Follow-ups. Context gathering. Multi-step tasks. And it only acts when you say so. All adapting to your voice, priorities, routines, and relationships over time. Your Townie is the AI assistant you actually need.

    8379518999648K viewsView on X
  • May 15, 202616x their median

    Let’s see how this is https://t.co/ez4HEBlWfr

    1.0K856161.4M viewsView on X
  • Jul 12, 202510x their median

    JPMorgan Is Charging for Access to User Data. This Is a Pivotal Moment for Financial Infrastructure JPMorgan is moving to charge fintech companies for access to customer data. This data includes transaction histories, balances, and behavioral signals generated by end users interacting with the banking system. Until now, this information has been accessible through data aggregators or direct APIs, enabling fintech innovation across payments, budgeting, lending, and more. By introducing a pricing model on top of this access, JPMorgan is making a calculated move. It is asserting ownership over data that is generated by users but stored inside infrastructure the bank controls. This is not a one time policy update. It is a structural shift that tells us something fundamental about where the legacy system is headed. The pattern When a platform gains enough market power and dependency, the default next step is to extract from it. This is not new. Operating systems, app stores, payment networks, and telecom infrastructure have all followed the same curve. In the beginning, the focus is on distribution. Then it shifts to control. Finally, it becomes about rent. The moment a core financial entity begins charging others simply to read user authorized data, you are watching that final step in real time. The technical concern Financial APIs are not like public protocols. They are controlled endpoints with rate limits, usage restrictions, compliance gates, and contractual dependencies. By charging for access to these APIs, banks can determine who is allowed to build and what those builders can afford to offer. The more critical the API becomes to the product experience, the higher the leverage. This is not a technical innovation. It is a toll. And once data becomes a revenue stream for the infrastructure provider, the incentive is to fragment it, lock it in, and sell it at margin. This fundamentally limits what can be built on top. Why crypto matters here Public blockchains invert the architecture. Data is written to globally accessible networks with permissionless read and write access. State is maintained by consensus, not by counterparties. Identity is tied to cryptographic credentials, not private account systems. Code is open and composable, rather than licensed or restricted. In this model, access is not a business development negotiation. It is a property of the system itself. Smart contracts execute logic predictably across all users. Data lives on a ledger that is equally available to every participant. Protocols can be composed together without friction or arbitration. Builders do not need to ask for access, and users do not need to trust an intermediary to store or release their own information. This creates a fundamentally different environment for innovation. It also creates an escape path from platforms that want to monetize every layer of user activity while preventing competition from emerging. The global context This issue is not specific to the United States. In Europe, PSD2 created mandatory data sharing between banks and third party providers, but many institutions have resisted compliance or introduced friction through authentication flows. In China and India, national financial infrastructure is increasingly centralized, combining state linked identity with payment systems that reduce user level portability. In Latin America, superapps are racing to consolidate finance, identity, and commerce into vertically integrated platforms. The common theme is the same. Centralization leads to restriction. Restriction creates dependency. Dependency turns into control. We are watching the same structure repeat, just with new actors. The decision in front of us There is a version of the future where every financial interaction is intermediated by systems that monitor, price, and gate access to your own data. Where portability is limited, composability is artificial, and new products are taxed by the incumbents who control infrastructure. That is the natural trajectory of closed systems. We have seen it before, across industries and geographies. It is happening again now. Crypto presents an alternative. But that alternative is not guaranteed. The question we need to ask is whether we are actually building toward something more open, or simply recreating the same constraints under new names. Regulatory engagement and institutional maturity are not bad. In many cases, they are necessary to scale. But if those efforts result in recreating the same forms of control that define the legacy system, then the project has already lost its edge. We should not be optimizing for defensibility through restriction. We should be leveraging our position and profitability to build better access, more open architecture, and more composable systems. That means investing in protocols, not just platforms. It means participating in shared infrastructure, not just extracting value from it. At @krakenfx , we are attempting to do both. To support and secure the protocols that define this industry, and to build on top of their rails. Not just ours. Not just one chain or one stack. A multi chain, multi environment, multi purpose world. The goal is not just uptime or product coverage. It is staying true to what this system was designed to enable in the first place. Global permissionless always on access to financial infrastructure that anyone can build on and anyone can benefit from. If we are serious about that, then we need to avoid the trap that every generation of infrastructure builders has fallen into. Closed gardens are easy to justify. They offer control, reliability, and short term leverage. But they are also the reason we are here in the first place. We should not spend a decade building open systems only to end up recreating the same constraints with better branding.

    4861527115152K viewsView on X
  • Aug 14, 20256.1x their median

    1/ Today, we sent a letter from over 80 CEOs across industries urging @POTUS to support open banking and oppose anticompetitive fees on consumer data access set to take effect next month. #OpenBanking #FinancialFreedom https://t.co/hwCHtpEeTN

    332511234594K viewsView on X
  • Jul 29, 20255.5x their median

    For as long as I've been following the landscape, I've been impressed with JPMC's long-term orientation in doing business: be stable in all business environments, and do right by partners. So this latest ham-fisted attempt to crush competitors and end permissioned data-sharing is very odd coming from them.

    3401427581K viewsView on X
  • Apr 22, 20265.0x their median

    Build your own finance app with Replit using @plaid Plaid is now natively integrated into Replit, giving you secure, real-time access to your financial data. Connect your accounts → prompt what you want → get a working app. Spending dashboards, AI financial assistants, investment trackers, and more. Start building.

    28635211196K viewsView on X
  • Jun 27, 20264.4x their median

    Levels of Individual Agency: L0 — I don’t know how to do this. L1 — IDK. Please teach me. L2 — How do I teach myself? L3 — I did the task. Can you check it? L4 — I did the task well. What’s next? L5 — I did all the tasks. L6 — …silence…

    284139050K viewsView on X
  • Jun 30, 20263.9x their median

    It's been fascinating to watch Slack become the most important interface for Enterprise AI.

    232729644K viewsView on X
  • May 20, 20262.7x their median

    Launched some new banks on @Plaid recently: Coinbase Card, https://t.co/QEbQUZXGc1 Card, Erebor, Rho, Flex, River, Rho, Bushel, PenFed CU. More coming.

    167417424K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 70 interactions against 574K followers, an engagement rate of 0.012%. Posts are seen about 32K times each, and 0.22% of those impressions turn into an interaction. That is about 5.59% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.1 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 04:00 UTC, and Monday is the busiest day of the week. Of the 2 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 4.3K interactions, about 61x its own typical post. Only 2 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is Zachary Perret's engagement rate on X?
Zachary Perret (@zachperret) has an engagement rate of 0.012%, based on the median interactions across 2 original posts from the last 30 days against 574,400 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.012%, Zachary Perret sits above the 25th percentile of the 36,960 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @zachperret have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @zachperret post?
Most posts go out around 04:00 UTC, and Monday is its busiest day, at roughly 0.1 posts per day across the measured window.

Keep going

Zachary Perret (@zachperret) Engagement Rate - 0.012% | PlayerSells