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Data Management Tips for the Lone Wolf Admin

Being a solo administrator is no small challenge. When you’re not answering questions, training users, or fixing broken things, you’re trying to make the latest and greatest improvements to your Salesforce instance. It’s an even bigger challenge in nonprofit environments; being a Salesforce administrator is likely one of a dozen hats you wear on a day-to-day basis, and the odds are good that it’s not even the first hat you’ll put on when you walk in the door.

When you’re a solo administrator, you don’t have the time to pore over each and every individual record to make sure that your data is clean and useful. You’re stretched far too thinly for that, but clean data is essential to the health and wellbeing of your organization and your beloved Salesforce instance. Nothing will undo leadership’s confidence in their investment in Salesforce faster than bad data.

As a solo admin, you’re a lone wolf, but it’s a big, dangerous world out there. The time to get smarter about managing your organization’s data has arrived. Here are a few tips to get you started.

ETL Tools: Learn Them. Love Them.

For people who love data, cleaning up a few thousand records with just a few clicks is a kind of magic, and ETL (Extract, Transform, Load) tools are your magic wand.

Here’s one common scenario: your organization has recently participated in a conference, and you get handed a few thousand contacts who need to be added to the database. A worst practice is to make the intern type them all in by hand. Don’t do that.

A slightly better practice is to create accounts and contacts for each in Salesforce using Salesforce’s data loader (which is an ETL tool as well!) This will save countless hours of manually keying in records and all the resulting human error that process entails.

Here’s the best practice, though: use a tool like CRMFusion’s PeopleImport to evaluate the contents of your spreadsheet against the data already in Salesforce, map the fields in the spreadsheet to fields your existing database, and create account and contact records only for people who don’t already exist in your database. It will save you time, but more importantly, it will help limit the number of duplicate records in your database. Better tools can help lead to better data.

Here’s another fairly common scenario: much to your horror, you learn that a department has been using a field in a way that doesn’t make sense. For example, having previously lacked a better place to put it, your colleagues have been storing data about constituents’ gender in the contact “Description” field. They just type in “Female” or “Male” as appropriate. Rather than sifting through each of these records one by one, you could use a tool like Apsona to evaluate the contents of each of these fields, and where they were equal to “Female”, update the “Gender” field with the appropriate value without having to move data around in a spreadsheet. It can save a lot of time.

My own favorite ETL tool is DemandTools, and that’s largely due to its single table deduplication function. It can look for common factors in records–for example, first name, last name, and e-mail address for contact records–and merge records together based on strict or loose matches between records. That way, if you have fifteen Jean Smiths with the same e-mail address in your database, it can merge all of those records together in one fell swoop. It can save countless hours deduplicating records, and it’s a great tool to have at your disposal if you’ve inherited a messy database.

With any ETL tool, just be aware that they work purely on logical criteria. They can’t know that certain special records may be exceptions to the process you’re trying to run unless you tell them. These tools can really mess up your data if you aren’t careful, so it’s best to limit access to them to people you trust to use them responsibly.

For-profit organizations will often pay thousands (or even tens of thousands) of dollars every year for excellent ETL tools, but DemandTools, PeopleImport, and Apsona are free for nonprofit organizations. Check them out!

Validation Rules: How to Play Hardball with Data Cleanliness

Unless you’re working with literary luminaries like bell hooks or e. e. cummings, everybody in your database is should have a capitalized first and last name, but I’m willing to bet that your database doesn’t reflect that.

Here are some worst practices: first, go record by record fixing capitalization errors by hand before your big mailing goes out; next, yell at your colleagues that they’re doing everything wrong.

Here’s a best practice: use a validation rule! Validation rules are fantastic tools for a lone wolf admin. They will block creating or editing records when they meet certain criteria that you define. There are a million potential use cases, and Salesforce has helpfully put together a number of samples to work and learn from. For example, you might create rules that require donation amounts to be positive, that require an address field to be populated for donations that need acknowledging, or ensure that US phone numbers are made up of ten digits.

Validation rules are usually constructed as regular Salesforce formulas, but you can also deploy a little Regular Expression (usually abbreviated as RegEx) to enforce more stringent rules than Salesforce formulas will permit. Though RegEx can be a little complicated if you haven’t programmed before, there are some great libraries on the internet that can either give you exactly what you’re looking for or at least point you in the right direction. A tool like Expresso can also help you develop and test your RegEx expressions without having to know what can be a tricky language.

Validate Your Addresses

You’ve written them by hand a million times, so they probably seem simple. However, there are a lot of ways an address can go wrong. Is “3rd Street” written as “3rd Street”, “Third Street”, “3rd St.”, “3rd St”, or some other way? Ask five users and you might get six different answers. This not only makes your data look messy, but it can cause delivery problems when you’re sending out printed solicitations.

The solution? Validate, validate, validate. Address validation tools look at the addresses your users enter, try to match them to a known good address, and then reformat your data into a standard, consistent, USPS-friendly structure. It’s a great time saver, and it can help save your organization a lot of money when sending out printed mailings.

If you’re lucky enough to be using Nonprofit Starter Pack 3.0, there is built-in address verification through Google, Cicero, and SmartyStreets. If you’re on an older version of the Nonprofit Starter Pack or if you’re using another solution, a tool like GeoPointe can do the same thing, and it’s quite reasonably priced for nonprofits. DemandTools, mentioned above, can also validate addresses on an ad hoc basis for a small fee.

Document and Teach

Last but not least, help your users figure things out for themselves. When you’re creating fields in Salesforce, include help text that shows users what an appropriate input should look like using concrete examples. Use discrete page layouts for different record types and user profiles to make sure that users only see the things they need to see, thus limiting the number of places they can put information erroneously. Finally, make sure that at least one person in each of your organization’s departments is expertly trained on how to use the database for their purposes. Let them be the expert for you.

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