.png){kind=small}
Nancy Blattel is the Data Management lead at the University of California Berkeley. She spearheads the importing process of LiveAlumni data into their Ellucian Advance Database. Nancy executed this project so meticulously that she received recognition from the school’s Vice Chancellors for her team’s accomplishment. In this Talk, Nancy shares this procedure along with helpful tips and advice for anyone about to embark on matching and importing themselves, be it a first batch or subsequent LiveAlumni updates.
As with all LiveAlumni Talks, this is a round table discussion intended to bring the LiveAlumni community together to share knowledge.
Highlights
Employment Records are still the most requested info from Database Managers.
Nancy’s step by step matching and importing process,
Creating the Employment relationship one batch at a time.
Creating Master Employment Records for companies with complex hierarchies.
Laying the groundwork makes future batch importing much easier.
Should you add past employment to your records?
Understanding LinkedIn Industry Codes.
UC Berkeley uses Ellucian Advance which flows into their Salesforce CRM. They embarked on the project with LiveAlumni to include employment data in their database because it was the most requested piece of information from their fundraisers and they knew that LinkedIn data is the best source for that. They understood the critical nature of this data and said simply, “if you give us [employment] information, we'll figure out who a potential prospect is.”
Nancy's Pro Tip: Accurate employment data captured from LinkedIn helps fundraisers to identify potential prospects.
Master Employment Record
Nancy explained that her team created a new type of employment record called a master employment record. These are clearly marked and solely for recording employment. This way if an individual becomes a prospect and is employed, say at Google, a company that might have hundreds of Berkely graduates employed, the prospect is easier to identify. When contact information is available, it gets added to the master employment record as well rather than to Google's record. This is because Google has such a complex hierarchy with so many different offices that the employment record might get buried there. Furthermore, in today’s home office era, it just seems less and less important to know the actual physical address related to employment, so UC Berkeley has opted for letting go of that concept altogether.
Nancy's Pro Tip: Focus on employment and contact information over physical addresses.
Creating the employment relationship
First, LiveAlumni performs the Constituent ID matching. Nancy shared her thoughts on the accuracy of the matching, revealing that Level 1 matches for them are 96% accurate and level 2’s are 94% accurate. They have chosen not to match Level 3’s at this time.
After that, for the Organization Matching, Nancy’s team uses an internal algorithm created to best prepare organization records for matching. It suggests possible matches which have to be manually checked for veracity. This is by far the most time-consuming step in the importing process.
For simplifying, they started with the top 100 employers of their alumni and created master employment records for those companies in order to make matching with incoming employment data easier. This required researching their websites, alias names, etc. Their algorithm contains an “Exclude Table” for all the “bad” LinkedIn Job Titles and Company Names.
After loading their first batch of matches 25,000 records went to that exception queue and had to be manually checked. It seemed daunting at first, so they hired students and staff to clean it up for one semester.
But after three years, the job got easier and easier because of the time they took from the beginning to clean data as much as possible before bringing it into Ellucian. This as allowed their ROI on LiveAlumni to increase year on year, as the process of importing becomes less complicated.
Nancy’s goal was not to be perpetually creating thousands of duplicates. Currently, she's importing a batch of 50k LiveAlumni records but explains that the matching is so much more straightforward now in the third year. The data is quicker to clear the exception queue because the master employment records already exist.
Nancy's Pro Tip: Making the effort to import the data cleanly in year one may seem overwhelming but it's worth the effort because it gets easier and easier every year after that.
Adding past employment
About adding past employment records, Nancy commented that her development officers really appreciate the additional data, as it provides a person’s clear career path. It does make the matching job a little more complex, so it's not for everyone.
Nancy's Pro Tip: If the time factor implied for importing seems overwhelming, add only current employment.
For records that already had employment prior to LiveAlumni data, they added a second line for employment so as to keep both to indicate which line comes from campus research and which comes from LinkedIn. Importing the LinkedIn URL makes a quick double-check easy.
Nancy's Pro Tip: LinkedIn URLs can serve as unique identifiers.
In order to avoid a “scroll, scroll, scroll” situation, they opted for importing no more than 5 past employment records.
Importing Subsequent Updates from LiveAlumni
LiveAlumni creates reports to help identify new employment changes to avoid importing a massive file full of duplicated data. So each batch gets easier and easier to import with time because of the previous matches.
Nancy's Pro Tip: Use LiveAlumni reports to identify new employment changes and import only those - this means each importing project is easier than the last.
Measuring ROI from Employment Data
Nancy's Pro Tip: Measure ROI after a campaign by checking the list of donors to see which among them shows employment data that was imported from LiveAlumni.
What's next with LiveAlumni data?
Nancy mentioned that they are now beginning to import updates from shared alumni from other LiveAlumni customers that are updating their own databases. They are also looking at board memberships and adding the ones that seem like paid corporate board positions as employment. This way development officers can also see what organization boards alumni are volunteering their time on. This speaks to interests, which is another compelling data point that Nancy is going to look into next.
Nancy's Pro Tip: After employment data, don't forget to review compelling info such as board memberships and interests.
Importing Education Data
For adding education data, UC Berkeley imports the school name, degree and major before importing.
Import Personal or Company Industry?
There is no “right” way to do this. An individual can select their own industry, which they may attribute to their role or experience. This is referred to as Industry in LiveAlumni. Also, each company picks their Company’s Industry for their LinkedIn page. This is referred to as Company Industry in LiveAlumni. Some clients import both, some choose one over the other.
Nancy's Pro Tip: Industry guides can be found, in the LiveAlumni Helpdesk and will be helpful to those trying to decide which codes to import.
Hindsight
To conclude, Nancy mentioned that the only thing she might reconsider doing again is importing former employment simply because of the added layer of complexity it adds to the importing process. But - and it's a big but - she recognizes that the development team finds it useful. It’s an example of the rich data available in LinkedIn, which, when used to its fullest potential is incredibly valuable.
Want to watch more LiveAlumni Talks?
Nancy is just one of many inspiring members of the LiveAlumni community who have been sharing their strategies, tips and success stories. If you’d like to learn more you can (1) register to attend one of our future Talks or (2) watch recordings of past Talks.
Comments