Sourced customer field report

What an 11-person Web3 agency learned from two weeks of Telegram analytics

A transparent field note based on a contemporaneous Entergram company post. The customer is partially identified, the source is public, and the results have not been independently audited.

Emil's Web3 marketing agency

Web3 marketing, 11-person team

The team had no shared view of quiet hours or individual response and messaging patterns across its Telegram work.

2 weeks

Observation period reported

2-5 PM

Team-wide quiet window found

89%

Reply rate reported for one junior teammate

The agency connected its team to Entergram Analytics and reviewed the activity heatmap, message volume, response ratios and deleted-message signals after two weeks.

The agency moved standups after the heatmap exposed a 2-5 PM coverage gap. The same review identified uneven message volume and highlighted one junior teammate reported at 340 outbound messages per week with an 89% reply rate and no deleted messages.

Product context

Where each signal in this report comes from

The agency did not install anything or tag conversations. Analytics starts collecting when a Telegram account is connected on a plan that includes it (Pro, or a Pro seat), and the first sync runs on Entergram servers. Everything below describes the product views behind the observations, not additional findings.

The quiet window came from the Activity Heatmap

The heatmap plots messages by weekday and hour. Darker cells mean more activity, and it can be filtered to incoming, outgoing or all messages. A pale band across working days is what a coverage gap looks like, which is why it is the view to read before moving a standup or scheduling outreach.

Uneven volume came from the breakdown by seat

The message breakdown can be pivoted by Telegram account or by workspace seat. Each row shows messages sent and received, response rate, average first reply, deleted messages and active chats, so a teammate carrying more of the load shows up as a row, not a hunch.

Reply rate follows a strict definition

A trigger is every incoming private message, plus mentions and replies to your messages in groups. A response counts only inside a fixed window after the trigger. Unanswered triggers lower the response rate but stay out of the average time, so rate and speed have to be read together.

Deleted-message counts are a signal, not an accusation

Deleted counts appear per seat and per chat. People fix typos, so the count is informational on its own. Workspace owners who need stronger guarantees can block message deletion and editing with the privacy controls.

Owners see aggregates, not private chats

Workspace-wide analytics depend on the owner setting that lets members see all analytics. In workspace scope, chats that belong to another seat are marked Private: the numbers are visible, the conversation is not.

Running the same review on your own workspace

Connect the Telegram accounts the team works from and let the first sync finish.
Open Analytics, confirm the scope in the header, and pick the date range. Custom ranges are a Pro feature.
Read the Activity Heatmap for quiet hours, then pivot the message breakdown by seat.
Compare response rate with average first reply for each seat before drawing a conclusion from either.
Export the analytics data, or connect an AI client through the Entergram MCP and ask it for a recurring read-only brief.

Run the same review on your own accounts

Connect a Telegram account and analytics starts with the 3-day Pro trial. No credit card.

Start Free Trial Book a Demo