Zachary Perret engagement report
@zachperret - 644K followers on X
Measured over 6 original posts from a 30-day window, last computed on October 11, 2026.
Engagement
Early reading. We have captured 6 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 142 interactions against 644K followers, an engagement rate of 0.022%. Posts are seen about 36K times each, and 0.4% of those impressions turn into an interaction. That is about 5.53% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video, 17% are part of a thread and 17% link out. The account's strongest tracked post pulled 29K interactions, about 205x its own typical post. Only 6 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 6 original posts from a 30-day window, last computed on October 11, 2026.
Where this sits in the catalog
At 0.022%, Zachary Perret sits above the 10th percentile of the 204,694 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 15:00 UTC, and Wednesday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 50% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 17% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | -3% | -3% to -2% | 54K |
- 50% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 17% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 126 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 3% below the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- May 15, 2026205x their median
A preview for Pro users: a new personal finance experience in ChatGPT. Pro users in the U.S. can securely connect financial accounts, see where their money is going, and ask questions based on the information they choose to connect. Your full financial picture, now in ChatGPT. https://t.co/NjbJqOqFRi
- Jan 22, 202630x 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.
- Jun 3, 20268.8x 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.
- May 15, 20267.7x their median
Let’s see how this is https://t.co/ez4HEBlWfr
- Sep 4, 20266.5x their median
Grok users, it's happening. U.S. users can now securely connect your accounts to @Grok through Plaid. Ask about spending, savings, investments, cash flow, and anything else within your financial context. https://t.co/DpxEmP0MBX
- Jul 12, 20255.0x 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.
- Sep 25, 20263.5x their median
We're partnering with @Muse to help you manage the money side of your day. Reply and let us know how you're using Muse. We'll be RTing. https://t.co/PFVRatMYV5
- Aug 28, 20263.3x their median
I’ve struggled to find deep value in AI assistants. “Daily digest” style tasks provide some utility, but given the hype, I wonder what I’m missing. What are the highest-value things AI assistants help you do?
- Aug 14, 20253.0x 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
- Jul 29, 20252.7x 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.
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 142 interactions against 644K followers, an engagement rate of 0.022%. Posts are seen about 36K times each, and 0.4% of those impressions turn into an interaction. That is about 5.53% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video, 17% are part of a thread and 17% link out. The account's strongest tracked post pulled 29K interactions, about 205x its own typical post. Only 6 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 0.022%, based on the median interactions across 6 original posts from the last 30 days against 644,278 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.022%, Zachary Perret sits above the 10th percentile of the 204,694 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 15:00 UTC, and Wednesday is its busiest day, at roughly 0.5 posts per day across the measured window.