Honestly, why is data cleanliness so hard in todays world? For Aptify clients, truthfully it’s all our own fault. We allow bad data to enter our database, we somehow think Aptify will just clean itself or were waiting on amazing tools from Aptify. As much as I would love to see more data cleaning tools in Aptify… Associations are too different when it comes to the specifics of their data. I’ve been working with many Aptify clients since 2007 and everything has subtle differences which makes making generic services extremely difficult.
So what can an Aptify clients do? Well your going to need your Leadership team to buy in, that’s for sure.
Here are my top three vastly underutilized features used by Aptify clients.
After Validate Process Pipeline Event
Are you aware that when you click that little “Save” icon in Aptify there are a series of events that are executed? Are you aware that you can put your own custom business logic and processes into these events? Let me rock your world with the After Validate event. By default, Aptify does a generic validation of the data when you save a record. If the field is an Integer (numeric) field, is the value being entered a numeric value? Basic things like that. After Aptify has done it’s basic validation it then calls the After Validate event where you can take control and introduce your own business logic.
For instance, lets say a Person can only be a specific member type “Company Member” if their Company has a Member type of “Corporate Member”. Using the After Validate event, you can add in, If Person is of member type “Company Member” and their Company is not member type of “Corporate Member” then the validation fails and an error is shown to the staff member. This prevents the saving of the record, hence preventing bad data from being saved to the database.
Another example, properly formatted email addresses. Everywhere you have an email value in your Aptify it should have at least been validate that it’s at least of a valid format: sometext@somewhere.something.
Now I totally understand there are exceptions to all rule (especially in the Association world). But here’s the thing, you data is the backbone of your association. Reports, stats, leadership decisions, etc are all effected by your data these days. Look at your data issues and are their rules that you can enforce? If so, use After Validate. As well, because your using the After Validate event your rules apply to any application saving the record, Aptify Desktop, Aptify Web, eBusiness Classic and eBusiness 6.
Remember, I used an example using Persons, but this applies to ANY service/entity in Aptify.
Another way to use After Validate, you own custom Duplication logic checking. Keep reading as the third technique can be paired with After Validate for even more advanced validation.
Before/After Save Process Pipeline Event
Yep another process pipeline event, mostly Aptify clients only really look at these for when an Order Ships. Everyone forgets that Aptify itself is essentially a staff member. So if a Person record is updated with some value, which then means a value on another record needs to be updated… Why have someone do that manually? Why not just have Aptify automatically do it?
Seriously, I want you to really look at your data entry processes. Then find everywhere that you can say “when this happens, that happens” or “when I update a record with this, I update this record with this”. Take all of those processes an automate them! Now if any of the data entry people are reading this, no this automation will not replace you (yes I’ve had people say they didn’t want the automation because they thought if would threaten their job), it’s making your life easier so you can do the fun parts of your job and not the repeatable mundane stuff.
Integrating With Third Party Services
I’m going to use the two primary examples, Email and Addresses. I’m amazed at how many Aptify clients don’t use some of the amazing services out there to assist with there data cleanliness.
Lets start with Email. Email is super easy to get a valid format: sometext@somewhere.something. That’s great but what about if it’s an actually email address? Don’t we all love the reports on how many emails bounced or didn’t make it to sender? Two great services our their are Kickbox and Melissa Data (there are other, I’ve just done integrations with these two before). These service will do a much deeper dive into the email address to validate that there is an actually inbox for the address. Now lets tie this with what I mentioned above, After Validate and Before Save. If you feel really strong about the validation of email addresses or your organization really realizes on them, maybe the entire record save should fail if Kickbox saids it’s a bad address. Or you could be a little more loose and use the Before Save to flag the email address as bad so someone can dive into the details later.
This is the same thing for Addresses. Melissa Data has some great services for address validation. What if every time an address was validated with Melissa Data and if found valid you too their formatting of the address? Well you would not only have valid addresses they would always be formatted the exact same way. There is also a bunch of additional information Melissa Data will return to your about the address. That could also be valuable to you.
And you know, talking about Melissa Data, what about phone numbers?
Their’s Always More
These are just the three I personally feel Aptify clients vastly underutilized. There are all sorts of different things you can do to assist with your data cleanliness.
Aptify Clients
What is your organization doing? Is there anything that has made a huge difference?
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