When you run a young company, you can lose a surprising amount of time to poor-quality data – and you may not even notice it. For example, if you phone an outdated number, you’re likely to be frustrated when you can’t get through to the prospect, but are you really going to use that as a trigger to scour your whole database for outdated numbers? Probably not. So, what ends up happening is that you continuously lose a bit of time here and there as you try to contact wrong numbers, or you launch marketing campaigns out into a void of inaccurate recipient data. It all ultimately adds up to a lot of lost time and resources. So, to avoid a potentially huge but silent loss of time and resources, every founder should pay close attention to data quality. Here’s how:
Make a place for phone checks in your routine
When you import leads, you should check the phone fields before you ask anyone to call them. If this seems like a mammoth task, use a service like Trestle to review large batches. Ideally, you’ll still need someone to review the results and remove entries that don’t match the rest of the contact record, but validation services can speed things up significantly. Check phone numbers regularly, as people often alter their contact details and get new numbers.
Naming rules stop errors from spreading
Things can get very confusing very quickly when you let everyone enter their contact details in different styles. For example, if one person enters full names and another uses initials, you’ll end up with inconsistent data that can have a bigger impact on things like data-led marketing than you might think. If you want the system to be clear, usable, and useful, you should decide how names and numbers should appear and stick to that consistently across the board. Tell everyone to follow that format every time they touch a record. If you leave that choice to guesswork, you’ll make searches harder and duplicate contacts easier to miss.
Quick fixes save repair jobs later
When you spot an error during normal work, you should fix it there and then. For example, you should update the record after the call if you hear that a contact changed jobs or numbers. It takes seconds to make a correction when the record is already open, and much longer to make the same corrections when you leave them for weeks, resulting in a pressured backlog.
Imports can multiply the same mess fast
When you load a spreadsheet into your CRM, you can spread one mistake through the whole team in a few seconds. You may pull old records from an event list or a form and assume the file looks fine because the rows appear complete. If you import stale numbers or duplicate contacts, you push those errors into later work as soon as the import ends. If you check the file first, you’ll catch more of those problems before they touch the live system. You can save much more time with that early check than with a later cleanup.
Routine checks keep the database usable
When you treat data hygiene as part of your weekly work, you can stop many avoidable mistakes before they pile up. You should decide who checks imports and who reviews records periodically. You should also make room for those checks during the working week, rather than hoping someone will squeeze them in later. If you want your staff to trust the record in front of them, you need a routine that catches errors while the work is still fresh. You can begin with phone fields and contact names, and keep the process steady as the company grows.
