Skool analytics is the admin dashboard of your community. According to Skool's help center, it shows members, monthly recurring revenue (MRR), the About page conversion rate, retention, members joining and leaving per month, engagement cohorts, ARPU and LTV, cash flow and free trials. On top of that, the Growth tab shows visitors and joins per source. Each member also has an activity chart. Per-post analytics, such as views per post, aren't described in the help center (as of September 2026). Three questions are enough day to day: are new members becoming active, where do they come from, and who leaves? The dashboard largely answers all three, but only if you know the definitions. You read what happens in posts and calls yourself anyway.
I run my German community Claude Practitioners on Skool, and Susi, one of my AI employees, analyzes the numbers behind it. How the rest of the work around the community is split is described in Community Management with AI Employees. If you're new to Skool, start with Skool: What It Is and How It Works.
What the Skool analytics dashboard shows: the metrics at a glance
Skool has a dedicated help article defining every dashboard metric (last updated November 24, 2025). The most important Skool metrics, summarized or quoted:
Two definitions are worth knowing before you interpret any number. First: "Active is defined as having at least one page view to that group in a given month." So a member counts as active after a single visit a month, without writing or liking anything. Second, LTV at Skool is a calculation: ARPU divided by the churn rate, capped at "60 times the ARPU (5 years worth of retention)". In a young community that's a projection, not experience.
Skool community analytics per member and in the Growth tab
Besides the dashboard, each member has an activity chart. According to Skool it counts likes, posts, comments and poll participation, shown in UTC. For the question of whether someone actually takes part, it's more telling than the dashboard's definition of active, because a page view alone doesn't count there.
The Growth tab in the admin settings shows visitors, joins and conversion per source. Skool names three rules for it. Skool credits a join to the last source someone used before ("last-touch attribution"). The window is 90 days for most sources and 14 days for the Skool network and affiliates. And once set, an attribution doesn't change.
One plan question belongs here. In December 2025, Skool's pricing page listed "Advanced analytics" as a Pro plan feature, and the page code still contains the upgrade prompt "To see advanced analytics." The current pricing page no longer shows that line, and Skool doesn't describe which of the metrics above fall under it. If you create a new community on Skool* and start on Hobby, check it in your own dashboard. What else separates the plans is covered in Skool Pricing: Hobby vs Pro and the Fees.
* Affiliate link: if you create your own Skool community through this link, Skool pays me a commission. Your price stays the same.
Reading sources: where new members come from
For me, the source view is the most useful part of the dashboard, if the sources are right. Skool writes: "When a source is not available, it will default to direct." So what shows up as "direct" is often a visit whose origin simply wasn't passed on.
I learned that on my own website. For a long time, the Skool links on kevinwelter.com carried the noreferrer attribute. So the browser didn't tell Skool where the visit came from, and Skool counted my website as direct traffic. Since the attribute was removed, Susi lists kevinwelter.com as a separate source in her analysis. On top of that, every Skool link on my website carries campaign parameters per placement, and on my side I count, in a privacy-friendly way, which button was clicked. How those campaign parameters are built and which mistakes spoil the numbers is covered in UTM Parameters: Examples and Common Mistakes.
How well the combination of Skool's source and your own question works shows in the first purchase I could trace through the website, in September 2026: someone came to my homepage via Google search, read a blog post, clicked the Skool button and joined the $9 tier. In the membership question asking how they had found the community, they wrote "Google search". I had added that question as my third membership question shortly before. Which other channels bring new members is covered in How to Grow a Skool Community.
Skool churn rate: reading cancellations correctly
Skool shows churn mainly in two places. "Monthly Member Count" shows how many members left in a month ("Churned"), and "Monthly MRR" shows revenue that dropped to zero in a month. Retention is defined by revenue: the share of MRR at the start of last month that is still active at the end of last month. For the LTV calculation, Skool itself uses "Churn rate … 1 minus the Retention Rate".
Two things follow that are easy to miss:
- Retention looks at the completed month. A cancellation today shows up there at the earliest once the current month is over.
- Cancelled doesn't mean gone right away. According to Skool, the member count explicitly includes "members with a paid subscription who have cancelled, but still have time left on their subscription". Until the end of the paid period, cancellations look like members in the dashboard.
You calculate your member churn rate from Skool's own numbers: "Churned" for a month from "Monthly Member Count" divided by the previous month's "Total", the count at its end. Note that, according to Skool, "Churned" also includes members who joined and left in the same month. In a paid community with a free trial, it pays to look at trial starts separately, because they're part of the member count but not of revenue. For monthly memberships, Skool's Pro plan also offers a cancellation video that members see in step two of cancelling, and Skool's own starter course in the help center has a chapter "How to reduce churn".
To me this is the most honest metric. You can push member numbers up with ads and referrals, while cancellations tend to show whether the first weeks deliver what the About page promises. If they rise, look at onboarding first and only then at price or ads.
Activation: are new members becoming active?
The third metric that matters to me, Skool only delivers indirectly: whether new members really arrive in their first days. The engagement cohorts show it per join month, but with the generous definition of active. The per-member activity chart is more precise, but tedious.
So combine three signals: who is active in their join month according to the cohort, who has posted or commented in the first days, and what they wrote in the membership questions. My three questions are, translated: "What do you want to tackle first with Claude?", "Which AI tools have you used?" and "How did you find out about the community?". Skool allows up to three questions, and the answers can be downloaded with the Export button on the Members tab. We found no other export in the help center. What should happen in the first days so that a join becomes an active member is covered in Skool Onboarding: The First Seven Days.
What posts tell you that no metric shows
Views or reach of individual posts aren't described in the help center. That's less of a problem than it sounds, because the most revealing signals of a community are in text, not numbers.
What I see in my coffee calls, Susi counted in the transcripts in August: our members aren't people who just want to try AI. They already pay for Claude and want to get more out of it than they manage so far. The most frequent questions were about the right plan and model, the difference between chat, Cowork and Code, why Claude seems to forget, how to set up an AI employee, and how to keep AI texts from sounding like AI.
A second observation: my poll "What has actually saved you time here?" didn't get a single answer. Real success stories came anyway, unprompted, in posts where members shared their progress. How to write posts that invite answers is covered in Writing Skool Posts with AI, with Approval.
If you want to go deeper, compare buyers and non-buyers. How that works with posts, comments and call transcripts I show using the anonymized case of a coaching community from my client base with a free and a paid area, in Buyer Persona with AI from Community Data.
Beyond your own dashboard: benchmarks with SkoolStats
Skool analytics only shows your own community. Whether your price is high or low for your topic, whether other communities in your niche grow faster, and who might be a good partner for a collaboration isn't in there. For those questions I looked at SkoolStats*, a database of Skool communities. According to the provider it covers more than 121,000 communities, updated daily, using only publicly visible information. SkoolStats is an independent tool and not part of Skool. To be upfront: I have a partnership with the provider.
It can do three things:
- Comparing prices. I filter by keyword and language and see price, member count and growth per community. Searching for "Claude" among German-language communities returned 30 results in October 2026: 13 free, 17 paid. The 14 with a monthly price ranged from $8 to $98, with a median of $32. My community sits below the median with its $27 Standard tier (since October 19, 2026). That's not a pricing recommendation, but it's context my own dashboard can't give me. How I turn that into a price is in How to Price Your Skool Community.
- Watching growth. The table shows member growth over a week, a month or three months, each community has a history, and up to ten can be compared in one chart. That tells you whether a change in your numbers is the market or your community.
- Finding collaboration partners. I look for communities with a related but different topic and a similar size, whose members would also benefit from mine. The list is the starting point. Whether it fits only shows once you look inside the community, and I reach out through the channels the owners offer themselves.
Two limits apply. First, "Est. MRR" is an estimate that, according to its tooltip, is "derived from member count and price". For my community, SkoolStats multiplies 101 members by $9, the Standard price until October 18, 2026. It doesn't know who is on a free tier and who booked a more expensive one. Read it as an upper bound, not as revenue; why, I show in How Much Do Skool Communities Make?. Second, SkoolStats costs €149 a month or €1,499 a year, with no free tier and no trial (as of October 2026). It's worth it while you're actively working on pricing, positioning or partnerships, not for a one-off look. What else the tool does is in SkoolStats Review: Skool Benchmarks. I don't use the owner email addresses SkoolStats also offers for promotion: in Germany, marketing emails without consent are generally not allowed, even between businesses. This isn't legal advice.
* Affiliate link: if you subscribe through this link, I earn a commission. Your price stays the same. I have a partnership with SkoolStats.
In my business, Susi analyzes the numbers
At my company, Susi, my AI employee for Meta ads, is also responsible for the community numbers. She analyzes the metrics Skool's admin dashboard shows and the answers to the membership questions, and connects both with what she knows about ads. One rule runs through her work: every number is only valid as of the date of its source, and she answers a status question with a current snapshot, not an old one.
What Susi doesn't do: decide. Whether I change onboarding, adjust the price or start a campaign is my decision. Susi provides the basis and its reliability. Why the analysis happens outside of Skool, and which routes Skool offers officially, is covered in Skool API and Automation: What Works. If that feels like a lot at once: in the community I show how Susi is set up, and you can post your numbers there for feedback.
Frequently asked questions
What does Skool analytics show?
According to the help center: members, MRR, the About page conversion rate, retention, joins and churn per month, engagement cohorts, ARPU, LTV, cash flow and free trials. The Growth tab shows visitors and joins per source. Each member also has an activity chart. The help center doesn't describe per-post analytics, as of September 2026.
How do I calculate the churn rate in Skool?
For revenue, Skool's LTV calculation sets the churn rate as 1 minus the retention rate, smoothed and per completed month. For members, divide "Churned" for a month from "Monthly Member Count" by the previous month's "Total". Note: according to Skool, cancelled members with time left keep counting as members until their period ends.
Why does my website show up as direct traffic in Skool?
Usually because the link doesn't pass on its origin; without a source, Skool's help center says the visit defaults to "direct". In my case it was the noreferrer attribute on the Skool links of my website. Since it was removed, kevinwelter.com shows up as a separate source. So check your links before you attribute anything to "direct".
Does Skool have analytics per post?
The help center describes no per-post analytics, neither views nor reach. What you see are likes and comments on the post itself, and according to Skool the feed sorts by recent engagement by default. So you read a post's effect from the replies and from the questions that come up in calls afterwards.
Do I need the Pro plan for Skool analytics?
Both plans have a dashboard. In December 2025, Skool listed "Advanced analytics" as a Pro feature, but the current pricing page no longer shows that line. Skool doesn't describe exactly which metrics belong to it. Check what you see on Hobby in your own account before switching plans for the numbers.
Can I see the numbers of other Skool communities?
Not in your own dashboard, which only covers your community. Member count and price of other communities are public on their About page and in Skool's Discovery directory. Third-party tools like SkoolStats add history, growth rates and filters by topic and language. Their revenue figures are estimates from member count and price, not actual revenue.
Where to go from here
Open your dashboard and write down three values for last month: joins per source, the share of new members who became active, and churned members. Then check your links for noreferrer and redirects, and add a membership question about where people found you if you don't have one. In four weeks you'll have a comparison that says more than any single number. How Susi analyzes this for me is something I show in my English community AI Employee Framework.
* Affiliate links: if you subscribe through the SkoolStats link, I earn a commission; I also have a partnership with SkoolStats. If you create your own Skool community through the Skool link, Skool pays me a commission. What you pay SkoolStats or Skool stays the same.
