Your Salesforce org is only as good as the data inside it. That sounds obvious until you watch a forecast built on stale close dates, or a rep chase a lead that already converted six weeks ago, or a marketing campaign send to three duplicate versions of the same contact. None of those failures look like data problems on the surface. They look like process problems, coaching problems, or tooling problems. Underneath, they are almost always hygiene problems.
Data hygiene is the ongoing practice of keeping CRM records accurate, complete, and consistently structured so the numbers your team makes decisions from actually reflect reality. The key word is ongoing. Even a perfectly clean org degrades the moment new data starts flowing in again, which is to say immediately. This guide covers what dirty data actually costs, why it happens, and a practical sequence for cleaning it up and keeping it clean.
What dirty data costs
The numbers are worth sitting with. Gartner has estimated that poor data quality costs the average organization millions of dollars per year in missed opportunities, wasted effort, and bad decisions. One widely cited Salesforce study found that the average database contains roughly 90 percent incomplete contact records, with a large share of the rest needing updates. Separate research has put the amount of time sales reps waste sorting through bad CRM data at around 30 percent of their week.
