Weather ≠ Climate
The metrics we measure are almost always proxies. Treating them as endpoints is where community strategy goes wrong.
In my part of New England, we have a heck of a time forecasting weather based on radar alone. It’s partially just the nature of the area - mountains, lakes, rivers, random ‘force fields’ as my town Facebook group has decided.
But don’t think that means we walk out the door everyday with things for every single weather type. Over the years, we all learn how to read the upcoming weather in other ways - take a little bit of what the meteorologist think, a few looks at the sky, observe what the leaves and birds are doing, and all that weird stuff.
So why am I starting off a nerd post with a chat about weather? It’s not small talk. It’s because I actually think it’s a great approach to community climate too. As I’m getting ready in the morning, I’m not looking at the humidity for just sh*ts and giggles. It’s a little metric that gives me big insight into what to expect.
Community metrics work exactly the same way - if you’ll let them.
But somewhere along the way of building communities, dealing with the analysis paralysis of looking at community dashboards, and trying to report on our observations - we seem to have stopped viewing engagement metrics as weather instruments and started treating them as the weather itself. A spike in comments doesn’t mean your community is thriving any more than a pressure drop means a hurricane has already made landfall. But it does means something is happening that you haven’t fully diagnosed yet.
The metrics we measure are almost always proxies. Treating them as endpoints is where community strategy goes wrong.
This distinction sounds pretty freaking obvious in the abstract. But it gets much harder to hold onto in a quarterly business review, where a stakeholder wants a number that goes up and to the right. And unfortunately for us community professionals, “Well, technically this is a leading indicator of an underlying condition we haven’t fully characterized” does not fit on a slide or satisfy the stakeholder.
Sigh.
So we simplify. Engagement becomes health. Post volume becomes vibrancy. Reply counts become belonging. None of these substitutions are unreasonable on their face (a community with zero activity is obviously not thriving), but the substitution itself is where the trouble starts. Once a proxy gets treated as the target, people start managing the proxy instead of the thing it was supposed to represent.
You have most certainly seen this play out - if not literally been the one played. A community manager under pressure to show engagement growth starts running more prompts, more polls, more “what’s everyone up to this week” threads. The numbers move. Leadership is happy. But nothing about the underlying health of the community has changed! You didn’t create more trust, more expertise-sharing, or more durable relationships between members. You created more weather readings. You made the barometer twitch without doing anything about the actual system generating the pressure.
And we’ve talked about this in other articles: some of what we can measure barely correlates with what we actually care about, and some of what we care about most can’t be measured at all.
More sigh.
Think about what actually predicts whether a community survives a rough year and what doesn’t. It’s almost certainly not last month’s post count. It’s almost certainly members trust each other enough to disagree in public without the whole thread turning into a psychological hazard. It’s whether institutional knowledge lives in more than one or two people’s heads. It’s whether someone would notice, and say something, if a longtime contributor went quiet for a month.
And of course - none of that shows up cleanly in a dashboard. All of it is more predictive of long-term health than anything your analytics platform will hand you on a Monday morning.
So what do you do with metrics that are proxies at best? You don’t throw them out with the barometer. A pressure drop is still useful information, even though it isn’t the storm. The move is to change what you’re asking the number to do for you.
A few shifts to consider:
Stop asking “is this number good or bad” and start asking “what underlying condition would produce a number like this.” A quiet month isn’t automatically bad news. It might be a maturity signal instead of a decline signal, and the only way to tell the difference is to look past the reading itself.
Pair every quantitative metric with a qualitative check before you report on it. If comment volume is up, go read the comments. Find out if you’re watching real exchange or a spike in low-effort reactions. The number alone won’t tell you which one you’ve got.
Get explicit with stakeholders about what a given metric can and can’t tell you, before they build a narrative around it themselves. It is far easier to set that expectation up front than to walk it back after someone’s already put “engagement is up 40%” in a board deck.
Build at least one measurement into your practice that captures something durable, even if it’s slower and harder to report on quarterly. Trust, knowledge distribution, and continuity of relationships move on a different clock than engagement metrics do, and they deserve their own instruments.
And if all else fails, do what us weird northern New Englanders do: walk outside, look at the sky, listen to the birds, and just run with what you see. Chances are it’s not far off from the right number.