PatronManager

Today’s guest blog post is written by John Kollmer, Assistant Client Success Manager here at Patron Technology.

In recent years there has been a huge push in the business world to collect, study, and use data on our patrons. Although this was once only a concern for big box franchises and Wall Street firms, the importance and usefulness of data-awareness quickly spread to small businesses and non-profits; what was once out of reach is now quickly becoming standard practice, whether you have one employee or 100. It should go without saying (but I’ll say it anyway) that the only good data is clean data, but what exactly is “clean data” and how can you ensure that your data is good?

The answer lies in the system that your organization is using to obtain and store your data. Collecting data is easy enough to do; but once you have that data, what does your organization do with it? Take a look at your system and your staff’s procedures, and figure out what, if any, changes are needed to improve the health of your data — a solid foundation is the key to maximizing the potential later. Let’s look at some examples of how many organizations collect data on their patrons, with an eye for what is working and not working.

Sometimes databases are set up in a “set it and forget it” format. The system is configured in the beginning, and the data sources — like web sign-up forms — are put in place, and everyone sits back and watches the data pour in. This is a satisfying feeling, and a quick way to get data into your system!

However, then the question of cleanliness comes up. When you go to analyze this data, it can take you loads of time to manually filter out duplicates. Or worse, you might find that you have a ton of partially empty records that are useless to you. It’s kind of like watching Cookie Monster annihilate a cookie, with bits of cookie flying everywhere as he yells in ecstasy. With a critical eye, it’s pretty easy to spot a disturbing amount of cookie debris left over. Bits of cookie on the floor don’t do anything to sate your chocolate-chip cravings, and similarly, bad data in your system can leave your organization wanting more.

Okay, so letting the computer do all the work may not be best, since analyzing dirty data becomes difficult later. What about manual entry then? Many organizations employ this tactic, carefully entering every donation, ticket order, sign-up, etc. by hand. This process can also be daunting for your organization: It’s time-consuming, and there’s still the risk of human error. In this scenario, collecting and inputting the data is like watching Count von Count count to 100…it would take FOREVER. There’s a reason that The Count’s segments are often separated into small chunks — with all the laughing and the slow faux-Dracula dialect, it takes him a really long time to count things. So although manual entry would presumably be easier, because you can train staff or volunteers to input data in a consistent manner, it’s definitely not the most efficient way to collect and keep patron data.

All right, totally relying on the computer is out, and manual entry isn’t good either — I bet you know where I’m going. We need that combination magic. Setting up your system to pull data in automatically and training your staff to review the incoming records allows for a much cleaner (and more efficient!) end result in your database.

A computer doesn’t know that Bobby Smith on Maple Lane is the same Bobby Smith from Oak Street after an address change — but you do. If you keep a watchful eye on the data as it feeds into the system, it will help you catch errors before they become a larger problem in your system, and give you a much stronger source of information to work with in the future. I’m going to make one last Sesame Street Muppet reference: The system I describe here is like Oscar the Grouch. I’m serious — watch him next time someone hands him a piece of trash; he looks it over, decides he likes it, and then organizes it for safekeeping inside his trash can. You, too, can be like Oscar and keep a watchful eye on your database without losing all your time to cleaning up errors, because you’re going to stop them before they happen in the first place.

Your data is one of your organization’s most important assets, so you’ll want to make sure that you know exactly how your system handles it from import to export. Look at the process by which you collect and manage your data, and turn a critical eye toward the condition it’s in when it arrives at your front door. Then, make sure that everything you try to put in gets stored exactly where and how you like it. You’ll also want to know exactly how you can use that data in the system, because just collecting it isn’t enough — but that’s a different blog post!

Finally — and this is an important one — think about ways that you can improve data collection and analysis often, and then do something about it! Bad data isn’t a mystery, or an unavoidable phenomenon; it’s the result of less-than-stellar handling — it is 100 percent avoidable, and you are capable of stamping it out.

Now, if you’ll excuse me, it’s almost time for Sesame Street.