Data Hygiene

Data hygiene is the ongoing discipline of keeping your records clean: no duplicates, no stale or missing fields, consistent formats, valid relationships between records, and dead entries removed. It applies to your CRM, your customer database, your email list, your spreadsheets, anywhere the business stores facts it later relies on.

The reason it matters is that dirty data quietly poisons every decision and automation downstream. Two records for the same customer split their history and break your reporting. A blank owner field means a deal goes unworked. A stale email tanks your deliverability. For a lean founder running on automation and AI, the stakes are higher: an agent acting on bad data acts confidently in the wrong direction, and you may not notice until it's done.

A few concrete cases. Say you're running your pipeline in Pipedrive and the same prospect got entered twice, once from a webform and once by hand: their deals, notes and emails split across two cards, so your win-rate report lies and a rep works a "new" lead a colleague already lost. Or say you're sending a launch campaign through Brevo on a list you haven't cleaned in a year: the dead and typo'd addresses bounce, your sender reputation drops, and even your good contacts start landing in spam. Or say you're enriching inbound leads with Dealfront but half your company records have the domain in a free-text notes field instead of a proper field: the match fails and you pay for enrichment that never lands.

Good hygiene is partly prevention, validation on entry and duplicate checks before insert, and partly maintenance, a regular pass that flags and fixes drift. Clean data isn't a one-off project; it's a habit that keeps everything built on top of it trustworthy.