What's in an "MAU"?  ## Metadata - Author: [[Noele Flowers]] - Full Title: What's in an "MAU"? - Category: #articles - Document Note: --- tags: - #communitymanagement - #engagementmetrics - #MAU Author: Noele Flowers Source: Feedly (article) Reference: https://feedly.com/i/entry/WPPvDTi6P4Vtn6eGX84%2BkbPQNq5y0BsVLcVcR%2FEhH%2Fo%3D_18b8b65ea50%3A2e475a%3A7a92530f date created: 2025-08-23 00:00 --- # Title: What’s in an “MAU”? ## Table of Contents: - [📚 References](#-references) - [📝 Summary](#-summary) - [📖 Main Content](#-main-content) - [🗒️ Notes](#-notes) - [📖 References](#-references-1) - [🗣️ Paraphrase](#-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [📊 Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB (Diversity, Equity, Inclusion, and Belonging) Assessment](#-deib-diversity-equity-inclusion-and-belonging-assessment) - [✅ Logical validity](#-logical-validity) - [🔍 DARVO Analysis](#-darvo-analysis) - [🔍 SEO Evaluation](#-seo-evaluation) - [🎯 Conclusion](#-conclusion) ### References: - No external references were cited inside the article itself. ## 📝 Summary: The article argues that Monthly Active Users (MAU) is a useful proxy for community health when interpreted through trends (consistency and predictable growth) rather than a standalone percentage. MAU blends many inputs—acquisition, engagement, retention, lifecycle stage—so the most meaningful signal is whether MAU holds steady or grows predictably as the community scales. Interpreted this way, MAU reflects retention and can indicate downstream business impact. ## 📖 Main Content: - MAU as a proxy metric: - MAU offers a high-level snapshot of how well a community converts members into recurring participants. - It captures multiple forces: onboarding quality, content relevance, events cadence, product-market fit of the community, and lifecycle timing. - Limits of raw MAU percentage: - A single MAU percentage (e.g., 24% of the total member base) is weakly informative without context like seasonality, growth rate, or acquisition quality. - Raw MAU can mask churn or cohort decay if acquisition is outpacing disengagement. - What to watch instead: - Consistency: Does MAU avoid sharp fluctuations month to month? - Predictable growth: Is there a steady slope that correlates with known inputs (e.g., new programs, product releases, campaigns)? - Retention signal: If MAU grows predictably while the member base grows, retention is likely healthy; if MAU stays flat with rising membership, retention. - Business relevance: - Stable/predictable MAU suggests the community can reliably drive outcomes (support deflection, advocacy, expansion). - MAU trends can justify investment by showing compounding engagement rather than sporadic spikes. - Interpretation principles: - Context over absolutes: interpret MAU beside cohort retention, activation-to-first-action time, contribution rates, and seasonality. - Inputs matter: program changes, incentives, and content strategy should be tied to expected MAU movement and evaluated post-hoc. ### 🗒️ Notes - MAU = proxy for community health - Encapsulates engagement + retention rather than mere visits. - Best read as a trend line with context. - Raw % is insufficient - Needs supporting metrics: cohort analysis, activation funnel, DAU/WAU ratios, churn. - Sensitive to acquisition quality and lifecycle stage. - Consistency and predictability - Look for stable variance bands and explainable lifts/dips. - Use run charts and control charts to identify signal vs noise. - Retention lens - Predictable MAU growth → indicates compounding retention. - Flat MAU + growing members → retention risk or low activation quality. - Impact on business - Reliable MAU supports forecasting of advocacy, support savings, and product adoption. - Helps argue for resourcing and roadmap alignment. - Contextual interpretation - Consider seasonality (holidays, fiscal cycles). - Align with programming calendar and product launches. ## 📖 References: - Article contains no cited sources. For context on metrics, consider: - Reforge essays on retention curves and growth accounting. - Amplitude guides on behavioral cohorts. - The “North Star Metric” and “Input metrics vs Outcome metrics” literature. ## 🗣️ Paraphrase: - Original idea: “The actual percentage of MAU may not provide much information.” - Paraphrase: A single snapshot of what fraction of members were active this month tells you little without trend and context. - Original idea: “Tracking consistency or predictable growth can indicate retention and the overall impact on the business.” - Paraphrase: When MAU moves steadily and in line with known inputs, it’s a strong proxy for member stickiness and a leading indicator of business value. ## 📰 Newsletter: Learning web dev this week? Keep shipping—your future self will commit “git praise” later. In WordPress land, we’ve got fresh core chatter, community wins, and a couple of shiny plugins worth a test drive. - Learn: Brush up on PHP 8.x niceties and modern JS patterns in WP admin. Don’t forget CSS container queries—they’re finally practical. - Updates: Gutenberg keeps iterating on performance and UI polish; keep an eye on the changelog. Core discussions on performance and sustainability are heating up. - Community: Props to new contributors who joined this month’s onboarding cohorts. If you’re mentoring, pair folks with “first good issue” labels to accelerate impact. - New plugins: Try query-loop visual helpers and automated alt-text generators powered by on-device models. - Metrics tip: If you run a community or plugin, track MAU trends for your support forum or Slack—not as a vanity metric, but for consistency and predictable growth. It’s a quiet powerhouse for understanding retention. Helpful links: - WordPress developer resources: https://developer.wordpress.org/ - Gutenberg updates: https://make.wordpress.org/core/tag/gutenberg/ - Contributor onboarding: https://make.wordpress.org/ Stay curious, commit often, and may your builds be backward-compatible and forward-thinking. ## ✅ Action Items: Prompt for alignment with your role and goals: “Analyze how this article’s focus on interpreting MAU via consistency and predictable growth aligns with: - Open-source advocacy: Show how community MAU trends reflect contributor health, support deflection, and ecosystem sustainability in WordPress. - Contributor engagement: Map MAU to onboarding funnels (first PR/issue, first forum reply) and cohort retention across contributor programs. - Education: Derive curricula that improve activation (docs, workshops, mentorship) and measure impact through MAU trend improvements. - OSPO trajectory: Propose governance and reporting practices (dashboards, run charts, cohort retention) that make MAU a reliable input metric for policy and funding decisions. - Transparency and inclusivity: Recommend publishing anonymized MAU and retention dashboards, including disaggregated views (new vs returning, geos, roles), to foster trust and equitable support. - Sustainability: Connect predictable MAU growth to budget justifications for community tooling, moderation, and contributor experience. Deliver a brief outlining actionable steps, required data sources, and success criteria tied to MAU trend improvements.” ## 🧪 Hypotheses: - H1: Communities that publish regular programming (events, releases, content) exhibit lower MAU variance and higher retention. - H2: Improving activation (time-to-first-meaningful-action) by 20% increases MAU growth slope within two months. - H3: Higher acquisition quality (referrals vs paid) correlates with higher MAU consistency at equal membership growth. - H4: Public transparency (open dashboards) improves MAU via increased participation and trust. - H5: Contributor mentorship programs increase the proportion of returning actives, lifting MAU predictability. ### 📊 Methodology: - Data sources: Platform logs (forum, Slack/Matrix, GitHub), CRM, event RSVPs, newsletter analytics. - Designs - Summary: Community managers are focused on measuring the success of their communities and one important metric they track is Monthly Active Users (MAU). MAU gives a snapshot of how effective a community program is at engaging members and can be seen as a proxy metric for community health. However, interpreting MAU can be challenging because it reflects a variety of factors beyond just engagement. The actual percentage of MAU may not provide much information, but tracking consistency or predictable growth can indicate retention and impact on the business as a whole. - URL: https://feedly.com/i/entry/WPPvDTi6P4Vtn6eGX84%2BkbPQNq5y0BsVLcVcR%2FEhH%2Fo%3D_18b8b65ea50%3A2e475a%3A7a92530f | | | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | | | | | | --- | --- | --- | --- | | | | | | | --- | --- | --- | | | | | | --- | --- | | | | | --- | | | | | | | | | | | | --- | --- | --- | | | | | | --- | --- | | | | | --- | | **Hi Courtney,** As the end of the year approaches, community managers across the industry—from entrepreneurs who run communities of practice to full-time community managers at big brands—seem to all be thinking about one thing: measurement. **How should we think about the success of our communities over the past year,** and what should we aim for in the future? And while I tend to think that ["engagement metrics" are overused in the community industry and that the "holy grail" of community metrics are those that speak to the impact the community has on the business overall](https://noeleflowers.us17.list-manage.com/track/click?u=0b2719de083f15b373978be31&id=69598d2c08&e=e0f18787ef) (i.e., "community members churn from our core subscription product x% less often than non-members"), there is **one engagement metric I'll always track: Monthly Active Users**, commonly referred to as MAU. Most community platforms allow you to track MAU pretty easily by either showing it as a percentage or by showing you the raw # of active members within the past thirty days that you can use to calculate a percentage of the total. I like to track and report MAU because I think it gives a good "snapshot" of how effective a community program is at engaging members on the whole—**in other words, it's a decent "proxy" metric for community health.** A consistent or growing MAU % month over month is a signal that even as a community program grows, its programming is still effective. But, **MAU isn't always the easiest metric to interpret**, so I want to spent today's newsletter sharing more about how I think about interpretting these metrics once I've calculated them. When I start to talk about MAU, my clients always ask—"what's a good MAU percentage?" While it can be tempting to look for a "good" benchmark percentage and leave it at that, the reality is that **I've seen community programs that are both healthy and accomplishing their business goals that have an *extremely* wide range of MAU %**. In other words, a community with 10% active users can be healthy, and a community with 90% active users can be healthy, and everything in between. That's because MAU is an aggregate metric—**a metric that's reflecting the effects of lots of different inputs other than just "engagement."** The reality is that MAU may be "quietly" reflecting lots of information back to us—it may be reflecting pieces of information we want to know more about and that might change regularly (like how engaging or appealing our members find our programming, or how easy or hard it is for them to remember to use our communities) as well as pieces of information we already know and that are pretty static (like whether our community has a paywall, or how accounts were created for members). For example: in a community where members are paying $1000 a month to access, it would be really surprising and concerning to see only 20% MAU, but in a community where members are a part of it automatically alongside a core product and didn't join with much intent, 20% might actually feel like a big win. **This is a number we have to take with a lot of context.** So, if the actual percentage doesn't tell us much, why is this number so important to track? For me, what's important about tracking MAU month over month is looking for either ***consistency* or *predictable growth***. So, if I feel that given the conditions of my project, I'm at a healthy MAU % for October, I want to see about the same or a few points higher in November. This is a clue that I'm retaining members at a consistent rate as I grow. Once I reach a consistent MAU, that helps me understand the number of community members I'm meaningfully impacting through my program, and helps me see engagement metrics as a **leading indicator** for the type of impact I can expect to see my community have on my business as a whole. I hope this look into MAU has helped you think about measurement as we approach the end of the year! If you have any questions at all about metrics or any other topic you'd like me to address in a future newsletter, I'd love to hear from you—just shoot me a reply right here. A couple of final thoughts to close out the email: **Thank you to everyone who reached out about beta testing** my new On-Demand Coaching product a few weeks back. I was absolutely floored by the responses. I was looking for just 2-3 beta testers and I got over 60 volunteers, which means I had to turn a lot of folks away. Based on some of the responses I got and conversations I've had, though, I've decided to open up an **early access waitlist.** I will be offering a limited number of enrollments (& some ***exclusive bonuses***) in ODC prior the wide launch in early December via that list. You can learn more about this and sign up [here](https://noeleflowers.us17.list-manage.com/track/click?u=0b2719de083f15b373978be31&id=9b3d7c32b8&e=e0f18787ef). I'm also excited to share that I'll be speaking at the Community Everywhere Summit in a few weeks—if you're interested in catching mine or any of the other talks, you can register and view the agenda [here](https://noeleflowers.us17.list-manage.com/track/click?u=0b2719de083f15b373978be31&id=e5da478c6b&e=e0f18787ef) (I'm on day 2 at 12pm). And lastly—if you ever need more **1:1 help putting any of the ideas I share here into practice** for your community project, I would welcome hearing from you. I work with clients every day to help them with the most important strategic aspects of their projects—from measurement and ROI, to engagement plans, to community architecture and more. You can learn more about working with me and [get started booking a call here.](https://noeleflowers.us17.list-manage.com/track/click?u=0b2719de083f15b373978be31&id=434d0cdec7&e=e0f18787ef) Cheers, Noele Flowers Your Community Friend :) | | | | | | | | | | --- | --- | --- | | | | | | --- | --- | | | | | --- | | *Copyright © 2023 Noele Flowers, All rights reserved.* You are receiving this email because you opted in via our website. **Our mailing address is:** Want to change how you receive these emails? You can [update your preferences](https://noeleflowers.us17.list-manage.com/profile?u=0b2719de083f15b373978be31&id=a3331fe18b&e=e0f18787ef&c=a8117da1a8) or [unsubscribe from this list](https://noeleflowers.us17.list-manage.com/unsubscribe?u=0b2719de083f15b373978be31&id=a3331fe18b&e=e0f18787ef&c=a8117da1a8). | | | | |, What's in an "MAU"?, Noele Flowers, 01hean5pf8ag8g7bwant5dcc2s.