Participatory science project leaders wear a lot of hats. And one of the most underappreciated, and frustrating to some, roles is that of a communicator. You’re expected to maintain a social media presence, send newsletters, and overall build an engaged community of participants — all on the side while you’re doing the job of actually running your project.
A lot of people who put effort into their communications approach them as a task-based chore: Post your post, send your email, check the boxes. But far fewer have a good sense of whether checking these boxes is actually accomplishing anything.
The good news is, you probably already have the mental toolkit that will help you approach this challenge more efficiently and effectively, especially if you’ve spent any time working with researchers or consider yourself one. And the better news is, it might even put you ahead of some professional marketers.
Think like a scientist, and realize that your communications plan is actually an experiment. If you design it well, you can learn from it, understand what you should change next, and achieve the outcomes you want.
The Problem with Engagement Metrics
If you’re tracking the “success” of your communications at all, chances are you’re looking at stats like impressions, email open rates, and social media followers. These numbers are relatively easy to access if you know where to look in your communications platforms, and they feel like tangible data. But the problem is, they’re not actually connected to anything that matters to your project.
There are three levels of metrics associated with a communications plan:
- Activity: What you actually did — number of posts published, emails sent, blogs posted, and so on
- Engagement: Direct responses to your activities — social impressions, email opens, link clicks, new subscribers
- Outcomes: What actually changed that affects your project — new participants recruited, observations submitted, donations received
Engagement metrics can make you feel like you’re tracking success because they’re tangible and directly connected to your activities. But 500 email opens isn’t actually a win if none of those people took the action you wanted.
But that doesn’t mean engagement metrics are useless. They’re great for troubleshooting — they’re where you should start when you want to investigate why your activities aren’t leading to the outcomes you want. If email open rates are low, that means people aren’t opening your emails in the first place. But if email open rates are high, but click rates are low, people might love reading your emails, but something about them isn’t getting them to take action. But troubleshooting is only helpful if you know what you’re trying to fix.
Connecting Activities to Outcomes
One of the most frustrating aspects of marketing communications is connecting your activities to your desired outcomes. Sure, some engagement metrics feel like they connect the dots, like how many people clicked on a sign-up link in a specific email, or how many names you collected at your booth at the science fair. But what you don’t know is how many times that person that just signed up has seen your communications before, and what you did that planted the seed that led to their eventual action.
Our efforts are a lot more like putting up a billboard than we might think. We want to point to a specific action and say: This link was clicked, so this email was good. But the reality is, it was more likely the cumulative impression of the 10 emails before it that led to the eventual click. The cause and effect is murky.
The only real way to test whether a certain action is leading to a certain outcome is to run the experiment. Change one thing at a time, and wait long enough to see if your outcome actually budges. Even then it’s still not scientifically rigorous proof — at the end of the day, you’ll have a correlation — but it’s as close to concrete evidence as you’re going to get. If your outcome doesn’t budge, then look at your engagement metrics to look for clues as to what part of your action experiment is underperforming.
One last reason not to focus too much on engagement metrics: Most participatory science projects are operating in relatively small audiences. Most of us are getting 12 likes on a social post, not 1,200. At that scale, your sample size is low, and effect sizes are small, which means your “experiment” is under-powered (meaning, unwise to draw conclusions from). If you’re posting once a week, and one post gets 3 likes and one post gets 30, that’s not a statistically significant difference in engagement. That might just be a Tuesday.
But the fickle engagement data isn’t the data you’re drawing your conclusions from — outcomes are. And if you go from 3 participants to 30, you’ve achieved something real.
Putting This Into Practice
If you’re ready to put these ideas into action, start by picking one outcome you care most about right now. That might be increasing your number of participants, increasing the amount of “acts of participation” your project receives, or something else entirely. If your desired outcome isn’t already a measurable, tangible thing — say it’s something like “participant satisfaction” — think of a way to quantify it, like sending a survey.
Then, identify a single communications channel that you think is most likely to have an impact, and try something out — it could be a qualitative change, like a different style or format, or a quantitative change, like ramping up frequency. See what happens to your outcome.
This requires patience, which can be especially hard to come by when you want results now. When that’s the case, it’s tempting to throw spaghetti at the wall to see what sticks. But although that can lead to results, it doesn’t tell you what worked, which doesn’t help you build a working communication plan for the long haul. And that’s what you really need: A path forward that allows you to make more deliberate, effective communications decisions that don’t make you work harder than you have to.
Thinking like a scientist doesn’t mean having more knowledge. It means knowing how to set yourself up to learn from what you do — so your next decision is always better informed than your last.
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Anna Funk is a communications consultant and the founder of Ampliflora, a consulting studio that works with organizations in science and conservation. She has a Ph.D. in plant ecology, and has worked as a science journalist and marketing professional. Today she brings science, storytelling, and strategy together to help mission-driven organizations amplify their impact.Interested in developing a communication strategy tailored to your project? Anna Funk is teaching Strategic Communication for Participatory Science Practitioners, a fall cohort of this 5-session course in AAPS Connect, launching September 14.
