Treat attention like a ledger. Each visit writes a line, each share adds a small sum, and the balance grows when the work earns a second look. Publish material worth saving: the checklist that ends a recurring headache, the explainer that names a thorn others describe in euphemism, the tool that gives a concrete answer. Write for a person with a problem, not an audience with vague needs. Avoid slogans. Precision cuts through noise the way a sharp blade parts a rope.
Make the path from reading to trying obvious. A single, honest invitation at the moment of clarity beats a parade of modals. Show what will happen next in plain text. If a trial begins, guide the first minute so the user touches the core outcome quickly: import one file, connect one source, send one call, see one result that looks like theirs. Every second spent asking for information you do not need squanders a mood that might have turned into adoption.
Measure like a naturalist. Cohorts over vanity totals, retention curves over spikes. Run lift tests where channels can be isolated. If a channel cannot be isolated, acknowledge that and treat its movement as suggestive rather than certain. Feed your model with what the model can eat: dates, referers, campaign tags where present and clean. Journal the campaigns in a public log so explanations do not drift with memory.
Some channels feed each other. A technical essay seeds search, a conference talk brings a week of direct visits, a tutorial video helps both convert. When the graph is honest, you will see compounding not as a secret trick but as a byproduct of consistency. The work that compounds tends to have the same qualities as a good tool: it is useful, it is clear, and it respects the reader's time.
Resist the theater of novelty. A quarterly rhythm of durable pieces will beat a monthly churn of light copy. When you run experiments, write the hypothesis as a sentence with a number in it. "If we publish a guide to X with three runnable examples, we will raise activation in segment Y by Z percent over two weeks." Afterward, publish the result internally. A team that sees honest outcomes learns to guess better. A team that only sees wins begins to distrust the scoreboard.
Attribution will always contain fog. Accept this and work with ranges. When debate turns circular, step outside and ask a simpler question: did we make a page or a product that a person would recommend to a friend. If the answer is no, the model is not the problem. If the answer is yes, keep going, and let time do some of the compounding for you.
Case notes
Teams who publish durable, problem"‘solving guides and measure by cohort rather than clicks see steadier activation. Public changelogs, when written with clarity, act as a compounding channel of their own.