By Peter Wylie and John Sammis
(Download a printer-friendly PDF version of this paper: Online behaviour of alums)
For a number of years John Sammis and I have been pushing colleges and universities to examine the data they (or their vendors) collect for alums who are members of their online communities. For example, we encourage them to look at very basic things like:
- The number of e-mails an alum has opened since it’s been possible to get such data
- The number of “click throughs” an alum has made to the website in response to an e-mail, an e-newsletter, and the like
- The number of times an alum visits the website
- The date and time of each visit
Why do we think they should be recording and examining these kinds of data? Because (based on some limited but compelling evidence) we think such data are related to how much and how often alums give to their alma maters as well as how engaged they are (e.g., reunion attendance, volunteering, etc.) to these institutions. To ignore such data means leaving money on the table and losing a chance to spot alums who are truly interested in the school, even if they’ll never become major givers.
Frankly the response to our entreaties has been less than heartening:
- “We don’t have an online community. If we get one, that’s probably a year or two away.”
- “With the explosion of social media, we’re more interested in what we can learn about our alums through Facebook, LinkedIn, Twitter … I mean those are the sites our alums will be going to, not ours.”
- “You want us to get record-by-record data from the vendor who maintains our site? Surely you jest. We’re lucky if they’ll send us decipherable summary data on email openings and click-throughs.”
But we’re nothing if not persistent. So what we’ve done here is put together some data from a four year higher education institution that has a pretty active online community. Granted, it’s only one school, but the data show a pronounced relationship between number of website visits and several different measures of alumni engagement and alumni giving.
We have to believe this school is not a glaring exception among the thousands of schools out there that have online communities. Our hope is that you’ll read through what we have to show and tell and conclude, “What the heck. Why don’t we take a similar look at our own data and see what we can see. Can’t hurt.”
Nope. Can’t hurt, and it might help – might help a lot.
A View of the Overall Distribution of Website Visits and the Distribution of Visits by Class Year
Table 1 shows that almost exactly two thirds of the alums have never visited the school’s website as an identifiable member of the school’s online community. The remaining third are roughly evenly divided among four categories: one visit; two to three visits; four to seven visits; and eight or more visits.
Table 1: Frequency and Percentage Distribution of Website Visits for More Than 40,000 Alums
As soon as we saw this distribution, we were quite sure it would vary a great deal depending how long people had been out of school. To confirm that hunch we divided all alums into ten roughly equal sized groups (i.e., into deciles).
Table 2: Count, Median Class Year, and Minimum and Maximum Class Years for All Alums Divided into Deciles
As you can see in Table 2, there are some very senior people in this alumni universe, and there are some very junior people. For example, the majority of folks in Decile 10 (CY 2006 – CY 2010) are probably in their 20’s. What about Decile 1 (CY 1926 –CY 1958)? It’s a safe bet that these folks are all over 70, and we may have at least one centenarian in the group (which we think is pretty cool).
If you look at Table 3, you can see the percentage distribution of website visits for each Class Year Decile. However, the problem with that table (and most tables that have lots of information in them) is that (unless you’re a data geek like we are) it’s not something you want to spend a lot of time looking at. You’d probably prefer to look at a chart, a graphic display of the data. So what we’ve done here (and throughout this paper) is display the data graphically for the folks in Decile 1, Decile 5, and Decile 10 – very senior people, middle-aged people, and very young people.
Table 3: Percentage of Website visits by Class Year Decile
Clearly our hunch was right. The distribution of website visits is highly related to how long people have been out of school:
- Over 90% of alums who graduated before 1959 (Decile 10) have not visited the website.
- In the youngest group (Decile 10) only a bit over 25% of alums have not visited the site.
- You have to look at Table 3 to see the trend, but notice how “the 0 Visits” percentage drops for Deciles 7-10 (a span covering alums graduating in 1992 up to 2010): 68.9% down to 64.3% down to 46.5% down to 27.7%.
The Relationship between Number of Website Visits and Alumni Engagement
If you work in higher education advancement, you probably hear the term “alumni engagement” mentioned several times a week. It’s something lots and lots of folks are concerned about. And plenty of these folks are finding more and more ways to operationally define the term.
Here we’ve taken a very simple approach. We’ve looked at whether or not an alum had ever volunteered for the institution and whether or not an alum had ever attended a reunion.
Table 4 and Figures 4 to 6 show the relationship between number of website visits and volunteering. Just to be clear on what we’re laying out here, let’s go through some of the details of Table 4.
We’ll use Class year Decile 1 (alums who graduated between 1926 and 1958) as an example. Look at the alums in this Decile who have never visited the website; only 17.1% of them have ever volunteered. On the other hand, 42.9% of alums who have visited the website 8 or more times have volunteered. If you look at Figure 4, of course, you’ll see the same information depicted graphically.
Table 4: Percentage of Alums by Number of Website Visits for All Deciles Who Ever Volunteered
There are two facts that stick out for us in Table 4 and Figures 4 to 6:
- Alums who have never visited the website are far less likely to have volunteered than those who have visited even once.
- In general, there is a steady climb in the rate of volunteering as the number of website visits increases.
If you look through Table 5 and Figures 7 to 9, you’ll see a relationship between number of website visits and reunion attendance that’s very similar to what you saw between number of website visits and volunteering. The one exception would be for the youngest group of alums – those in Decile 10 who graduated between 2006 and 2010. These alums simply are too young to have attended a five year reunion. (Although it would appear that several of them found a way to make it back to school anyway – good for them.)
Table 5: Percentage of Alums by Number of Website Visits for All Deciles Who Ever Attended a Reunion
The Relationship between Number of Website Visits and Giving
There is no question that advancement offices are interested in alumni engagement. But if we’re realistic, we have to admit they tend to view engagement as mainly a step in the direction of one day becoming a donor. So let’s take a look at how number of website visits is related to alumni giving at this school.
We’ve created two sets of tables and figures to allow you to get a clear look at all this:
- Table 6 and Figures 10 to 12 show the relationship between the number of website visits and giving over the past two fiscal years.
- Table 7 and Figures 13-15 show the relationship between the number of website visits and lifetime giving of $10,000 or more.
Browse through all this material. After you’ve done that, we’ll tell you what we see.
Table 6: Percentage of Alums by Number of Website Visits for All Deciles Who Have Given Anything in the Last Two Fiscal Years
Table 7: Percentage of Alums by Number of Website Visits for All Deciles Who Have Given $10,000 or More Lifetime
Clearly, there is a lot of information contained in these tables and charts. But if we stand back from all that we see, the picture becomes clear. Regardless of how long alums have been out of school, those who have visited the website versus those who have not are better recent givers, and they are better major givers.
For example, let’s focus on alums who graduated before 1958 (Decile 1). Those who have visited the website at least 8 times are almost twice as likely to have given in the last two fiscal years as those who have never visited the site (75% versus 41.6%). If we look at giving of $10,000 or more lifetime for this same Decile, the difference is even more striking: 42.9% versus 12.5%.
Let’s jump down to Decile 10, the “youngsters” who graduated between 2006 and 2010. Understandably, almost none of these alums have given $10,000 or more lifetime. But look at Figure 12. For this group the relationship between number of website visits and giving over the last two fiscal years is striking:
- 27.8% for those with 0 website visits gave during this period.
- 35.1% for those with 1 visit gave during this period.
- 38.1% for those with 2-3 visits gave during this period.
- 43.1% for those with 4-7 visits gave during this period.
- 50.9% for those with 8 or more visits gave during this period.
Where to Go from Here
Clearly, there is a strong relationship between this simple web metric (number of website visits) and alumni engagement and alumni giving at this particular school. If that’s the case, it’s reasonable to assume that the same sort of relationship holds true for other schools. If you agree with that assumption, then we think it’s more than worth your while to take a look at similar data at your own institution.
At this point you might decide:
“Look guys, this is all very interesting, but we simply don’t have the time, resources, nor staff to do that. Maybe sometime in the future, when things are less hectic around here, we’ll take your advice. But not now.”
As much as we love this sort of analysis, we totally get a decision like that. We may be specialists, but we talk to enough people in advancement every week to realize you have a lot more on your minds than data mining and predictive modeling.
On the other hand, you might conclude that what we’ve done here is something you’d like to try to replicate, or improve on. If so, here’s what we’d recommend:
- Find out what kind of online data is available to you.
- Ask your technical folks to get those data into analyzable form for you.
- Do some simple analyses with the data.
- Share the results with colleagues you think would find it interesting.
1. Find Out What Kind of Data Is Available
Depending on how your shop is set up, this may take some persistence and digging. If it were us, we’d be trying to find out:
- Has an alum ever opened an email that we’ve sent them? (In a lot of schools they don’t have to be a member of the online community for you to ascertain that.)
- Have they ever opened an e-newsletter?
- Have they ever clicked through to your website from an e-mail or e-newsletter?
- Can you get counts for number of openings and number of click-throughs?
In all probability, you’ll be dealing with a vendor (either directly or through your IT folks) to get answers to these questions. Expect some pushback. A dialogue that goes like this would not be unusual:
YOU: Can I get the number of e-mails and e-newsletters that each of our alums has opened since the school has been sending out that kind of stuff?
VENDOR: We can certainly give you the number of e-mails and number of e-newsletters that were opened on each date that one was sent out.
YOU: That’s great, but that’s not what I’m looking for. I need to know, on a record-by-record basis, which alums opened the e-communication, and I need a total count for each alum for their total number of openings.
VENDOR: That’ll take some doing.
YOU: But you can do it?
VENDOR: I suppose.
2. Ask Your Technical Folks to Get The Data Into Analyzable Form.
What does “analyzable form” mean? To us that just means getting the data into spreadsheet format (probably Excel) where the first field will probably be the unique ID number you use to keep track of all the alums (and other constituents) in your fundraising database. For starters, we’d recommend something very simple. For example:
- Field A: Unique ID number
- Field B: Total amount of lifetime hard credit (for many alums, this value will be zero)
- Field C: Total amount of hard credit for the last two fiscal years
- Field D: Total number of e-mails or e-newsletters opened
- Field E: Total number of click-throughs to your website from these e-mails and e-newsletters
- Field F: Preferred class year of the alum
In our opinion, this kind of file should be very simple to build. In our experience, however, that is often not the case. (Why? How much time you got?)
Our frustrations with this sort of problem notwithstanding, keep pushing for the file. Be polite. Be diplomatic. And, above all, be persistent.
3. Do Some Simple Analyses with The Data.
There are any number of ways to analyze your data. Our bias would be to have you import the Excel file into a stats software package, and then do the analysis. (You can do it in Excel, but it’s a lot harder than if you use something like SPSS or Data Desk [our preference]).
If you can’t do this yourself, we’d recommend that you find someone on your team or on your campus to do it for you. The right person, when you ask them if they can roughly replicate the tables and charts included in this paper, will say something like, “Sure,” “No problem,” “Piece of cake,” etc. If they don’t, keep looking.
4. Share The Results With Colleagues You Think Would Find It Interesting.
Sharing your results with colleagues should be stimulating and enjoyable. You know the folks you work with and have probably already got some in mind. But here are a few suggestions:
- Look for people who think data driven decision making is important in higher education advancement.
- Avoid people who are inclined to tell you why something can’t be done. Include people who enjoy finding ways around obstacles.
- It’s okay to have one devil’s advocate in the group. More than one? That can be kind of frustrating.
- If you can, get a vice president to join you. Folks at that level can help move things forward more easily than people at the director level, especially when it comes to “motivating” vendors to do things for you that they’d rather not do.
When you can, let us know how things go.