“Everyone received everything, rather than really segmenting and targeting people.”

For Margo Schwartz, Salesforce admin for Institute of Design at Illinois Inst. of Technology, finding a way to revitalize her company’s records was a top priority. The first challenge was to cleanup existing dirty data that had been migrated to Salesforce from a homegrown solution. The second challenge was to figure out a way to keep the data clean.
Using Cloudingo, Margo was able to identify her bad data problems, handle the data clean up, and establish a plan for ongoing maintenance to tame bad data.

Meet IIT Institute of Design

The Institute of Design at Illinois Inst. of Technology is a graduate design school located in Chicago, Illinois. The Institute focuses on preparing individuals and organizations to take on the world’s complex, fast-changing, and unpredictable problems such as competitiveness, digital media and learning, health and wellbeing, social innovation and more. These global challenges influence the well-being of individuals, societies and the planet.

The Story

Courtney Schexnayder, Cloudingo team member: How long has the Institute of Design been using Salesforce?

Margo Schwartz, Data Specialist at Institute of Design at Illinois Inst. of Technology: We started using Salesforce when we realized that our homemade database was no longer viable. We went live in November 2013. That’s also when we started using Cloudingo.

CS: Migrating data from a homegrown system to Salesforce is a major project. What was that process like for you?

MS: To prep for the migration I literally looked at over a million cells of information! Among our small staff, we tried to divide and conquer. In theory, we were all supposed to check our contacts to make sure the information was correct. I had a whole color-coded system. We sorted our lists in various ways to check for duplicates and formatting issues. We were working with a consultant who wanted our data in two weeks! It took us well over two months.

CS: Wow, what an accomplishment! Comparing Salesforce to your homegrown CRM, what have been the benefits?

MS: Salesforce has allowed us to segment and target people according to their interests. We use it to not only house information about our current and prospective students, but also about people who attend our events and those interested in the school. We host several conferences, lectures, and alumni events globally. There are a lot of people who aren’t prospective students but who are still interested and involved with ID.

CS: What were the signs that dirty data was affecting your business and that something needed to be done?

MS: We’d known for a while that a lot of our emails were old. We had a lot of contacts who were inactive, and we wanted to make our list valuable, not just big. We were getting a lot of bounced emails and marketed as spam. We weren’t getting through to people. Everyone received everything, rather than really segmenting and targeting people. Cleaning our data helped us make better decisions about what to send and to whom. It also proved that we needed to update our records.

CS: What was the biggest source or cause of your duplicate records?

MS: We mainly experienced duplicates when importing event attendance lists. Lots of the same people attend our events so they were getting imported into Salesforce multiple times.

CS: How are you keeping your data clean, organized, and structured now?

MS: I try to do maintenance work and deduping weekly or bimonthly. And now when I import event attendance and other lists, I use Cloudingo to dedupe those lists.

We also started working with Form Assembly. We sent out surveys asking our contacts to make sure we have the most updated information for them – their personal information, business information, and their areas of interest so we know what kind of information they want to receive from us. The hope is that we’ll send this out at least once a year and that people will stay engaged with us.

CS: Finally, what advice would you give to another admin who is thinking about data quality?

MS: Decide what information is really important and focus on that rather than driving yourself crazy with the tiniest of details that are almost never really needed.

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