We know that there is no standards in measuring web analytics and ad analytics among the various web measuring tools. Despite that, the terminology is almost standard in this industry though. Thus, which metrics and benchmarks do you use to measure? I would start with:
1. unique visitors
2. repeat visitors
3. time spent on site
4. how many comments
5. how many replies
6. how many threads started

What do you think?

Dani AI

Generated

Good starter from and useful additions from , and . Those posts cover volume, sources and signups — useful baselines. To make growth actionable, add metrics that measure member value, retention and operational cost so you know whether growth is sustainable, not just bigger.

  • DAU/MAU (stickiness): how often people return relative to monthly reach.
  • Contributor ratio: percent of members who post or reply in a period (shows reliance on a small core vs broad participation).
  • Activation rate: share of new accounts that take a defined first meaningful action (first post, first comment, first profile completion) within X days.
  • Retention cohorts: cohort-based retention at day 1, 7, 30 to see whether changes improve long-term use.
  • Median time-to-first-response: faster replies = healthier, more welcoming community.
  • Resolution/answer rate: percent of questions or threads that receive a useful answer or solution.
  • Quality and moderation signals: helpfulness/upvote ratio, content flags per 1k posts, moderator time per active user.

Practical workflow: pick 3 KPIs tied to the community’s goal (support, product feedback, brand advocacy). Establish a 30–90 day baseline, segment by acquisition source, instrument events (first post, reply, accept/resolve), then review weekly and run small experiments (adjust onboarding, tweak prompts, highlight top contributors). Correlate each KPI with a business outcome so you can prioritize changes that move the needle.

Quick formulas and cautions:

DAU/MAU = daily_active_users / monthly_active_users
Activation rate = new_users_with_key_action_within_7_days / new_users
Median response time = median(time_to_first_reply)

Use medians for skewed times, filter bots and duplicate accounts, and avoid optimizing vanity figures in isolation. Combine a few of the metrics above to form a simple “community health” dashboard you review every cadence.

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We know that there is no standards in measuring web analytics and ad analytics among the various web measuring tools. Despite that, the terminology is almost standard in this industry though. Thus, which metrics and benchmarks do you use to measure? I would start with:
1. unique visitors
2. repeat visitors
3. time spent on site
4. how many comments
5. how many replies
6. how many threads started

What do you think?

For some of my clients the other important ones, based on Google Analytics, involve the popularity of pages, referring sites, and exit pages. For companies like my client, they have multiple product offerings and vertical target markets and they have separate page content for each so the ones I mentioned help to guide them in terms of revamping and refreshing page content.

time on site
unique page views
membership signup

We know that there is no standards in measuring web analytics and ad analytics among the various web measuring tools. Despite that, the terminology is almost standard in this industry though. Thus, which metrics and benchmarks do you use to measure? I would start with:
1. unique visitors
2. repeat visitors
3. time spent on site
4. how many comments
5. how many replies
6. how many threads started

What do you think?

Google has a good benchmark system I didn't see this posted here but the best way to see how people like your site is to have them login and than see which pages people view the most, what people do, even comments they post like "I wish this page had (enter wish here) it would make it so much better." Also another good way to see what people think about your site is to check twitter. I know people rant on twitter about websites... and even about twitter. All you would have to do is search for the name of your site and see what people complain about and than if any of the complaints appear to have any useful content or ideas of how you can update your site than try to improve it or put out a beta version that users can use and see what they think.

I know twitter isn't very reliable on somethings but when it comes to looking for complaints twitter is the place to be.

Thanks for the good comments. So the upshot here is for monitoring, it is good to use twitter search and then correlate referred traffic to possible tweets. Second, monitor closely any conversions on the site as benchmarks. I personally have not used Google Analytics for clients, just for my blogs, but it does seem it do the job of providing important metrics.

Thanks for the good comments. So the upshot here is for monitoring, it is good to use twitter search and then correlate referred traffic to possible tweets. Second, monitor closely any conversions on the site as benchmarks. I personally have not used Google Analytics for clients, just for my blogs, but it does seem it do the job of providing important metrics.

I find Google Analytics good for showing customers quantifiable data that helps justify necessary changes to websites. I have used it recently to show a client how they were throwing away money on an adwords campaign without updating the landing page content. They spent $500+ dollars in one month to get top 3 position in adwords and Analytics let me show them that 95% of the clicks on the ad ended with the person entering and exiting their site from the landing page with an average site visit of less than 1 minute. Needless to say they have started a massive redesign of the page.

Thanks for sharing that story. The type of insight that Google Analytics provides can help businesses optimize their internet marketing and revenue making opportunity.

Also there are some more simplistic ways to measure online community growth like RSS feed subscribers, podcast subscribers, facebook fans, twitter followers, etc. For some clients these numbers are just as important if not more so than the analytics data.

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