XMBoost or TGStat: which one fits your task
These tools answer different questions, so the choice depends on how you currently win clients. TGStat measures channels: reach, subscriber dynamics, advertising prices, comparison between placements. XMBoost reads open chats and passes on messages where someone describes a task, scored from 1 to 100 with an explanation. If your clients come from buying posts, the first tool lowers the cost of choosing badly. If they come from conversations and referrals, channel analytics changes nothing.
What TGStat is good at
It is an analytics product for the advertising side of Telegram. It tracks channels rather than chats, and it answers planning questions: which placement reaches your audience, how the audience is changing, what a post costs, how one channel compares with another.
For anyone whose growth comes from buying posts, that is genuinely valuable. Placement decisions are expensive to get wrong, and guessing without data is how budgets disappear.
It is worth saying plainly: within that job we do not compete with it and do not try to. We have no channel reach data and no advertising price index, and adding them would not make sense for the problem we work on.
What XMBoost is good at
It watches open chats, which are a different object from channels. A channel is one way publication; a chat is where members write themselves, and that is where somebody types that they need a contractor.
The product reads those communities continuously, interprets each message, and forwards the ones that look like a request, as a card in your working Telegram with a link to the original message and its author. The catalogue holds 108 119 open sources and up to 1000 chats are watched per project.
What it does not do: it does not measure channels, does not price advertising, and does not build audiences. Asking it for a media plan is asking the wrong tool.
The practical test
Look at your last 10 clients and recall how each appeared. If most came from a post you paid for, analytics is your tool and this comparison ends there. If most came from a conversation, a recommendation or an answer you gave somebody, then no amount of channel data will change your acquisition.
A second, cruder test: does anyone on your team reply to strangers within the hour? Chat monitoring only pays for itself when somebody does. Analytics has no such requirement, which is one honest advantage it holds.
Teams that do both usually keep them separate: analytics for planning placements, monitoring for daily conversations. They rarely substitute for one another.
Where people get confused
The word monitoring is used by both products and means different things. In analytics it means watching metrics of a channel over time. Here it means reading messages and deciding which ones are requests. Same word, different object.
The second confusion is about volume. Analytics reports large audience numbers, and monitoring reports a much smaller number of requests. That is not a weakness of the second: people with a live task are always a small fraction of people in a topic.
The third is legality, and it deserves care rather than a slogan. We read only open communities and only public messages; private conversations are never read and are technically inaccessible. Whether a message is public does not settle every legal question on its own, and the detailed discussion sits on our separate page about the legality of monitoring.
Cost structures differ, so compare carefully
Analytics is usually priced per seat or per data volume, and its value shows up as better placement decisions. Monitoring is priced by the number of sources under watch, and its value shows up as conversations started.
That makes a direct price comparison meaningless. The only comparable figure is cost per closed deal, measured over at least one full sales cycle in your market.
A note on our own numbers: we do not quote a cost per request without saying how many requests it assumes. Demand density varies enormously between markets, and a price stated without the denominator is a marketing figure rather than an economic one.
If you are still unsure
Test rather than argue. Both approaches can be tried cheaply, and a fortnight of real use settles questions that comparison tables cannot.
For our side of it, the trial runs 5 days across 150 chats. That is enough to see the order of magnitude of public demand in your niche: requests arriving steadily, occasionally, or not at all. It is not enough to prove demand is absent, and we do not present it that way.
What we will not do is promise a number of leads. Volume depends on how much your market discusses its tasks in public, which we can measure but not create.
Common questions
Do these products overlap at all?
Barely. One measures channels for advertising planning, the other reads chats for requests. Teams that use both keep them for separate jobs rather than substituting one for the other.
Can I find leads with channel analytics?
You can find where your audience gathers, which is useful for placing advertising. It will not tell you who has a task today, because that information is not in channel metrics.
Is chat monitoring legal?
We read only open communities that anyone can join, and only public messages. Private conversations are never read. The fuller discussion, with the caveats it deserves, is on our page about legality.
Which is cheaper?
They are priced on different bases, so the question has no direct answer. Compare cost per closed deal over a full sales cycle instead of comparing subscription prices.
What if my clients come from both routes?
Then keep both tools and measure them separately. Mixing their metrics is the most common way teams end up unable to tell which route is actually paying.
Updated: 2026-08-29