Filters, paths and tidy data
The Signal pipeline from last week was deliberately simple: watch, filter, tidy, file. Real work is rarely that linear. Sooner or later you want a Zap that makes choices — do this for press releases, that for preprints — and copes with the mess that real data arrives in. That is what this instalment is about: the four building blocks that turn a toy automation into something you’d actually trust.
Filters: the bouncer on the door
A Filter does one job: it lets a Zap continue only if conditions are met, and quietly stops it otherwise. “Only continue if the source is on my approved list.” “Only continue if the headline contains one of these terms.” It is the single most useful step you will add, because most automation problems are really too much happening problems. A good filter is the difference between a queue you read and a queue you avoid.
The craft is in being neither too tight nor too loose. Too tight and you silently drop things that mattered; too loose and you’re back to noise. When in doubt for editorial work, lean loose — a few extra items to skim beats a missed story you never knew about.
Paths: when the answer is “it depends”
Filters are pass/fail. Paths let a single Zap branch: if the item is a regulatory announcement, do one thing; if it’s a journal article, do another; otherwise, do a third. Each path has its own conditions and its own actions, all inside one Zap you can see end to end.
This is where automation starts to mirror how you actually think. You don’t treat an FDA warning letter the same as a conference abstract, and now your Zap doesn’t have to either. Resist the urge to build a maze, though — two or three clear branches you understand beat ten you don’t.
Formatter: making messy data behave
Data arrives ugly. Dates in five formats, names in inconsistent case, links wrapped in tracking junk, text with line breaks where you don’t want them. Formatter is Zapier’s quiet workhorse for cleaning all of that: reformat a date, trim whitespace, change case, extract a number or an email from a block of text, split a field, find-and-replace.
It is unglamorous and it is essential. Most automations that “don’t work” aren’t broken — they’re choking on data that arrived in a shape the next step didn’t expect. A Formatter step in the right place fixes more problems than any amount of clever logic.
Schedules, delays and lookups
Three more tools worth knowing, briefly. Schedule lets a Zap run on a clock — every weekday at 7am, say — rather than only when something happens, which is how you’d build a daily digest. Delay holds an action for a set time or until a specified moment, useful when you want a pause before a follow-up. Lookup checks whether a record already exists before creating it, which is how you stop a Zap filing the same item twice.
The principle underneath
Every one of these is a small, legible piece of logic. The skill is not memorising features; it’s decomposing your own process into steps clear enough to hand over. If you can write down, plainly, “when X arrives, check Y, and if so do Z — otherwise do W,” you can build it. The tools are easy. The thinking is the work, and the thinking is yours.
Next: 13. Zapier: giving your Zaps a brain — adding AI steps, Tables and chatbots, so your automation can start to interpret, not just move.
Zapier for health communications is a practical series. New post every week.
— Ned