CoolData blog

16 August 2011

Phonathon pledges and time on the call: Another look

Filed under: Annual Giving, John Sammis, Peter Wylie, Phonathon — Tags: , , — kevinmacdonell @ 11:54 am

by Peter B. Wylie, John Sammis, and Kevin MacDonell

(Download a printer-friendly PDF version here: Time on call and pledges P2)

Back in January of this year, the three of us posted a paper based on calling data from one higher education institution (Time on the call and how much the alum pledges). You can go back and take a look at the paper, but its essence is the strong relationship we saw between time spent on a call to an alum, and whether or not that alum made a pledge and how big the pledge was.

We weren’t bowled over by these findings, but we were certainly intrigued by them. In this paper we’ve got some more data to show you — data that provides “corroborative testimony” for that relationship between calling time and pledging. And we’ve got something a little bit extra for you, too.

We’ll start by tipping our hand just a little. We looked at calling time (in seconds) only for those alums with whom contact was made, and the result of the last call was labeled either “NO PLEDGE” or “SPECIFIED PLEDGE.”

Tables 1 – 3 show the calling time in seconds for the three schools (X,Y, and Z) that we looked at. Notice that we divided the alums called at each school into ten groups (called deciles) of approximately equal size.

Table 1: Median Talk Time, Minimum Talk Time, and Maximum Talk Time by Decile for All Alums in School X Who Either Made a Specified Pledge or No Pledge

Table 2: Median Talk Time, Minimum Talk Time, and Maximum Talk Time by Decile for All Alums in School Y Who Either Made a Specified Pledge or No Pledge

Table 3: Median Talk Time, Minimum Talk Time, and Maximum Talk Time by Decile for All Alums in School Z Who Either Made a Specified Pledge or No Pledge

These three tables convey a lot of information that we think is worth looking through carefully. On the other hand, sometimes it’s just easier to look at a quick summary. And that’s what you’ll see in Table 4 and Figure 4; both show the median talk time (in minutes, not seconds) by decile for the three schools.

Table 4: Median Talk Time (in Minutes) by Decile for All Three Schools

There’s not much difference among the schools in terms of how much time their callers spent on the phone with alums. Schools X and Y look very similar; School Z callers appear to have been just a bit “chattier.”

Now let’s look at the pledge money that was received from alums in the three schools by our time on the call deciles. It’s laid out for you in Tables 5-7 and Figures 5-7.

Table 5: Total Pledge Dollars and Mean Pledge Dollars by Talk Time Decile for All Alums in School X Who Either Made a Specified Pledge or No Pledge

Table 6: Total Pledge Dollars and Mean Pledge Dollars by Talk Time Decile for All Alums in School Y Who Either Made a Specified Pledge or No Pledge

Table 7: Total Pledge Dollars and Mean Pledge Dollars by Talk Time Decile for All Alums in School Z Who Either Made a Specified Pledge or No Pledge

These data are not tough to summarize. There is an obvious and strong relationship between time spent on the call with alums and how much the alums pledged. If someone pressed us for specifics, we’d say, “Look at the total pledge money received for deciles 1-3 (the bottom 30%) versus deciles 8-10 (the top 30%) for each school.”

Here they are:

  • School X: $6,850 versus $164,485 (24 times as much)
  • School Y: $25,032 versus $93,355 (3.7 times as much)
  • School Z:  $3,554 versus $220,860 (62 times as much)

So far we’ve confirmed some of the findings from our January paper. But what about the extra we promised?

You’ll recall that the alums we looked at in this study were ones who had (on the last call made to them) either agreed to make a pledge, or who had told the caller they would not make a pledge.

Take a look at Tables 8-10 and Figures 8-10. They show the percentage of alums at each decile who chose either option.

Table 8: Percentage of No Pledges versus Specified Pledges by Talk Time Decile for School X

Table 9: Percentage of No Pledges versus Specified Pledges by Talk Time Decile for School Y

Table 10: Percentage of No Pledges versus Specified Pledges by Talk Time Decile for School Z

As is often the case with data analysis, we sort of happened upon what you’ve just seen in these table and charts. We were looking at outcomes that were related to call length. We didn’t plan to look only at alums who either said they’d give a pledge or, “Nope, can’t help you out.” The thought just occurred to us as we were looking at lots of different possibilities. But look at what popped out. It almost appears as if we fudged the data. But we didn’t.

Some Concluding Thoughts

Here are three:

  1. We’ve now looked at call time data from four quite different higher education institutions. At this  point, it would take a mountain of evidence from other schools to dissuade us from this notion: “The longer student callers talk to the alums they are soliciting, the more likely those callers are to obtain bigger and bigger pledges.”
  2. We are far from ready to tell call center managers: “Tell your callers to try to keep the alum on the phone as long as they can. If they do that, both your pledge rates and pledge amounts will go up dramatically.” It would be nice if things were that simple, but, of course, they are not. Some alums are quite willing to give a healthy pledge, and the last thing they want to do is yak on and on with a kid who went to a place they graduated from when people used rotary phones. Some callers are naturally chatty and engaging, as are some alums. Others are not. Humans beings are complicated creatures and they vary enormously. One size fits all advice is almost always unhelpful for dealing with them.
  3. That said, we do think this relationship between time on the call and pledge rate/pledge amount is worth a lot more investigation. A good example. Not long ago, Kevin (a call center manager himself) said:

“I’m always interested in identifying ways to predict which of those people who’ve never given us anything before will finally make a pledge. I’m going to start looking at the talk time of lifetime non-givers from last year who ended up making a pledge this year. I bet the talk time for those who converted will be a lot longer than for those who didn’t.”

Great idea. Let’s hear some more from you all.

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6 Comments »

  1. I applied the methodology of the study to our data and found virtually identical results. However, I don’t believe a caller is generating affinity through keeping someone on the phone longer, I believe “time-on-call” is a surrogate variable for affinity. In other words, I don’t believe, if a caller manages to keep an alum on the phone longer, he increases the affinity the alum feels for the institution, but I do believe an alum who feels stronger affinity for the institution is willing to stay on the phone longer with one of our students.

    In many ways I think time-on-call is a supperior measure of affinity to those measures we purchase from data-mining companies. I found little to no correlation between our purchased affinity scores and time-on-phone. Many of the purchased scores are simply a measure of how much information we have been able to gather on an alum, while time-on-phone requires an actual choice of the alum. When choosing, for example, which prospects to visit to make a mid-level ask, I would trust the time-on-phone data as a measure of affinity more than I would a purchased score. One confounding issue here is, time-on-phone doesn’t stay consistent from year to year, so it’s difficult to create a stable affinity score from longituinal time-on-phone data.

    Comment by Allen Lunde — 16 August 2011 @ 6:57 pm

    • Allen: Well put. We’ve pretty much left it to readers to draw their own conclusions, preferably after digging into their own data, as you have just done. Like you, though, I am a bit skeptical that we can “generate affinity” via a single phone call. So yes, I agree with you when you say that time-on-call is a measure of the level of affinity that an alum already feels for alma mater. Alas, in Annual Giving we so often place emphasis on fine differences in approach. Do they make much of an impact? Over a long time, an accumulation of engagement strategies done properly might bring mildly-engaged alumni closer to us. But taglines, branded annual funds, subtle differences in envelope sizes and whatnot? I just don’t know — I haven’t seen the evidence. Measurable affinity indicators such as time on the call can give us real indicators about which alumni might, for example, consider increasing their annual gift, or be open to talking about planned giving — perhaps if we spent a little less time speculating on what font would work best in our appeal letter, and more time listening to what our alumni are telling us (via historical contact data), we might really get focused on the people who would respond if asked. Regarding your last point, about the difficulty of creating a stable affinity score from time-on-phone data: What I do is total up talk-time from several years of data. This allows the variable to extend to more alumni than one year’s worth of data would. And whaddya know: I’ve found talk time is predictive of major giving. Now that’s exciting.

      Comment by kevinmacdonell — 22 August 2011 @ 6:56 pm

  2. This is good data to back up a gut level supposition: good/friendly engagement indicated by longer talk time indicates a stronger propensity to give/pledge. But the next step may be to look at individual caller success in relation to average call time. For instance, are the most successful callers typically spending more time engaged with alumni or do they employ better persuasive techniques and actually spend less time talking vs more average callers who by virtue of a friendly phone conversation are able to win a pledge? Of course this is a bit more in depth than the simple time stats. That data could be an indicator as to which students need more coaching and which can serve as examples and mentors.

    Comment by Keith C. Kerber — 17 August 2011 @ 3:16 pm

    • Keith: If the time and the data are available for getting that deep into caller performance, then go for it! For me though (and keep in mind this is just my opinion), the time would be better spent on trying to figure out what a long phone call might tell you about how an alum feels about alma mater. For example, I plan to do some analysis to show that, on average, a long phone call in a past year that resulted in a “No Pledge” beats a short phone call with the same result for being predictive of conversion. (My models already show that cumulative talk time over several years, regardless of call result, is predictive of major giving.)

      Your comment echoes other responses to the blog post that I’ve read elsewhere (on LinkedIn) in that it focuses on the nuts and bolts of running a program, making adjustments here and there to the message and other aspects that are under the control of the fundraising institution, in hopes that ALL alumni will be just a tiny bit more inclined to consider giving. If we listen to alumni (via the data), we’ll have a much better sense of who’s standing up in front giving us their attention and just waiting to be addressed, who’s more standoffish but might possibly be swayed, and who’s just not worth talking to even if they haven’t specifically told us to pound sand.

      As I gear up once more to hire 25+ callers, like you I’m concerned about knowing which students need more coaching and which ones I can call on to train their peers. Call time is one indicator I use (there are big differences in average call length from caller to caller), but how much of this difference is due to the varying nature of the calling pools that are assigned? It’s not an equal playing field, as you know. I could do the analysis, but really, being able to tell the difference doesn’t take that much number crunching — there are simpler, more obvious ways to help callers succeed to the best of their abilities.

      Comment by kevinmacdonell — 22 August 2011 @ 7:22 pm

      • Thanks Kevin for sharing your insights. Do you have a blog post regarding the cumulative talk time and it’s correlation to major giving? Would love to include that in caller training as well as for shoring up the case for phonathon operations over the long haul. We are still a manual phonathon so I don’t have the data collection capabiltiy for measuring that at Thunderbird. I always tell my callers to think of phonathon as an invitation to a “long-lost cousin” (alumnus) to attend this year’s family reunion. Even if they say “no” for several consecutive years, I want the alumnus to feel like he/she will always be welcome and, in fact, that they will be missed this and every year that they don’t show up. Thanks again for sharing your data and insights.

        Comment by Keith C. Kerber — 23 August 2011 @ 2:50 am

  3. Keith: And thanks for your input. To answer your question, I haven’t yet written about the connection between phonathon contacts and major giving. I should, because probably few people ever make the connection. Yes, callers do often speak with very high-capacity donors, and yes their work either provides us with (at least) indicators of affinity such as talk time, or it has a direct influence on the success of future contact. I created and tested a couple of major-gift models using different methods, and cumulative phonathon talk-time (2007 to 2010) was a significant predictor in both of them. Other phone-related variables, such as number of attempts, number of ‘no pledge’ on the phone, number of failures to pick up the phone, etc. also crept into the models as significant.

    Comment by kevinmacdonell — 23 August 2011 @ 12:23 pm


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