Here’s one way Optimization Culture works at NextAfter
We’re making new discoveries in the Lab every day. We’re watching 74 active experiments right now, and that number is set to spike in the next month.
We record and publish all of our insights in the Nonprofit Research Library and our monthly broadcasts are packed with actionable data and case studies.
Even when we run a test that underperforms against the control, we share the results so we can all learn from it — because the goal of a test is to develop a learning about our donors and prospects.
We’re extremely happy to give away our learnings. To everyone.
That’s part of the mission and it won’t change.
Speaking of which, did you subscribe to our weekly digital fundraising strategies?
So what’s the problem?
We’re making a concerted effort to share even more of what we learn to better assist those folks who are not our clients.
And that’s what started the argument…
Ok, it’s not really an argument; it’s more like two competing hypotheses. That’s the great thing about optimization culture – when you can test, you don’t have to argue.
And that’s where I need your help.
Instead of endlessly debating whose is the superior hypothesis, we decided to ask you.
So, here are the two positions – whose side are you on?
A. “All we need to do is scale up the status quo. Feedback on our webinars, training events, and resources are great. So, to reach more people, we should just do more of it and faster! Let’s not overcomplicate things.”
B. “Yes, we should share our learnings—all of them. However, the information that we share is often highly technical and produced by a team who are knee-deep in optimization tests! The torrent of information is overwhelming. We should offer some sort of overview or introduction on what, exactly, optimization is (and why it is so powerful). We can’t assume that everyone *gets* testing and optimization like we do – we do it every day!”
Thoughts? Would more of the same be most helpful? Or are we so deep in the weeds that we overwhelm you sometimes?
Either way, what are we missing that would make our research, tools, and communications more useful to you?
Will you share your ideas with us?
You can also leave a comment below – we’d love to hear from you either way.
Thanks for your help!
P.S. If you’d rather join us in the Laboratory as a NextAfter Research Partner, visit this page to apply.
