Alumni Associations Twitter Usage Report

Don't let the fact that I am not able to offer you a fully functioning version of this data with an attached, preloaded pivot table stop you. I would love to put a call out there for someone to do their magic with this data and give it back to us. I ventured into this project with a few basic questions I wanted to answer. I collected the data and set about to answer those questions. There is, without a doubt, a hundred other questions and answers that one could derive from this data, so have at it.

If you plan to do your own analysis and discover some answers to your own questions, you should know a few basics about the tool I used to collect this data. Twitalyzer is a website that runs the numbers you see represented in the data. Twitalyzer takes a snapshot of the past seven days of your use of twitter and runs the algorithm to arrive at a score in 5 different categories, influence, signal, generosity, velocity and clout.

A couple other things you should know...If you haven’t used twitter in the past seven days, it doesn’t matter how much influence or clout you had, Twitalyzer will give a zero return on data. This does NOT mean that your influence scores will reset, start over from zero, and need to build up again. Part of the Twitalyzer algorithm accounts for the number of followers you have, and previous profile scores that have been analyzed in the past. It is important to understand how some profiles might go from an influence score of 2.4 to zero and back to 2.2. The “no data” score is not technically a score of zero, even though it might seem that way in how you choose to present data. Twitalyzer basically answers the question, “what is your influence in twitter in the last seven days.” Where one can easily make the case that a profile that hasn’t been updated for the past week still retains some influence (based upon user accessibility to previous updates), Twitalyzer only shows trends limited to the previous tabulations that have been run on a given user name. In the basic report page, an ongoing tabulation of the scores is only presented in terms of averages… and not trends. If you would like to see the information presented in a line graph, over time, Twitalyzer will give you a look at that information in a couple of fun ways here.

Based upon this information, it seems inappropriate to present these numbers in a line graph, over time.

This raw Twitalyzer data should be seen as a snapshot average, tabulated five times, between the dates of May 27th and June 22nd , 2009.

If any one data collection time returned “no data” that time was not counted as a zero in the average, instead it was not included in the average.

So, lets get into the questions and answers about Alumni Associations.

I took time to select the top 40 twitter profiles (based on number of followers) by searching for user bios or user names that contained the words "alumni association." the remaining group of alumni association feeds came from a sampling of feeds that were interesting to me for one reason or another. For instance, the two profiles at the bottom of the list were selected because they were started within a couple of days of when my data collection began.

What does the average alumni association feed look like?
After collecting data over the course of a month, what was the aggregate growth seen in each time period?
The typical twitter profile for alumni associations started off with 454 followers and following 303 twitter users. Those numbers grew. By the end of the month, the typical alumni association profile was following 356 users while being followed by 559.

Lets average all the scores together for all 49 profiles that were traced over the course of the month.

The fact that alumni associations have an average influence score 0.4 give us plenty of comparisons to make among the ones that were analyzed. Should alumni associations be happy to be above average? Do their twitter feeds rank low in comparison to other similar industries? More on that later.
For now, here is several quick looks at how individual profiles compare.




















If you have been reading these posts from the beginning, you have heard me make the case that judging a profile based on the number of followers is a horrible way to measure success. It is still a statistic that most would be interested in. Here are a couple of ways to look at that statistic. There are a couple of ways to determine how engaging an alumni association is being with this social web tool. One quick way I did this was to look back through three pages of updates for each feed and see if they had a tendency to @reply any of their followers with conversation. If there were none, it is easy to conclude that a feed was dedicated to one-way communication. Those profiles that choose to engage with @replies saw slightly higher growth in followers than those who did not. While I personally hold to the insight that it is better to have 50 responsive followers than 1000 that ignore you, this data comparison can help one make several observations.

There also seems to be a relationship between high clout/influence scores with those profiles who make a practice of following a high percentage of users that are following them. This is seen, in twitter, as a more generous and engaging way to act as a user.

The question becomes, to the alumni association, if the simple act of following back the real people who are following your feed is worth the little bit of extra time it takes to do this. The influence scores say yes.

You can see that the majority of alumni associations fail to take time to enact a follow strategy that leads out and initiates a relationship with another user by following first. Those that do, and follow at least 90% of their following, have more than three times the influence and clout of those that follow fewer than 50%.

While I have several other observations to make about this data. This might be enough to get our conversation started for now. What do you think? Feel free to pull down the spreadsheet and run your own numbers? What does it tell us? What recommendations can we make?
More to come...

Alumni Associations = Twitter FAIL -- Part2

I have received some wonderful interaction (both online and off) from part one of this series and this research. This interaction has led to some adjustments I am considering and I'd like to hear what you think about some of these ideas.

Don't just lurk, feel free to chime in on the comments, I'm happy to hear ideas from friends I haven't met yet. One of those friends is Katie, who chimed in on the comments of the previous post. I even got to spend some time on the phone with Katie today. We had a good, invigorating conversation...I love when online introductions turn into offline interaction. (go to a tweetup some time, you'll really like it)

Anyway, a few things that have hit me as we are half way through this experimental analysis...

#1 - I HAVE BEEN HARSH

I need to come out and admit this right away. The title and opening paragraphs of my initial post on this topic were intentionally over the top.
It was my intent to pull readers, especially alumni association officers, all the way into the research. It is not my intention to publish a scathing diatribe about collective ignorance. I pledge to leave this kind of tactic in post one, and intentionally become affirming and offer help in the remaining posts on this topic. If the use of this tactic lured you in to reading, I'm happy for that. However, I don't want you to hide this report or it's findings from your VP or director because it felt like I had an agenda to make you look ignorant.

That being said, I am going to allow the numbers to be what they are, even if that means they are brutal.

There are a handful of Associations in the data that are doing remarkable with their feeds. Only a portion of this partial study has been published. I chose not to make any commentary on any individual feed, but there are some conclusions you can start to draw from looking at this limited data set.

#2 - BUILD A BETTER BASELINE

Baker alludes to this in his comment on the first posting. I had an offline conversation with him that expounded this idea. I initially chose to show a glimpse of two twitter power users, Beth Kanter and Chris Brogan, in the partial findings. I wanted to give a view of how their scores are coming out, not because I intended a comparison to show that Alumni Associations were awful. Instead, I wanted to give context to the scores generated by the twitter analytic tool I used. I would love to compare the AA feeds to the average or aggregate twitter user, but I don't know where to find a tool that can give those numbers. I could find or choose several random twitter users to establish this baseline, but I believe it might be more appropriate to compare AA analysis to a brand name or business organization. I think this point should be open for discussion. I'll be happy to take suggestions of who or how to establish an appropriate comparative baseline in the comments of this post.

#3 - ESTABLISH A CONTROL GROUP

This idea came from the conversation I had with Katie. Her concern was that AA behavior and tweet habits might be affected based on the partial release of the findings. Feed managers like her will react to this release by awareness that I'm watching. This would result in skewed results for the second half of the data.

Scientifically, this is true.

Practically, I @replied to about 35 of the AA profiles that I was examining with a link to the blog post. I have heard from 6. I think a control group might naturally emerge from among those who hardly read their @replies.

Katie's suggestion also means recruiting a few feeds that were not in the study to take us up on the findings and recommendations we make once the study is over. Let's see if our recommendations are effective. That turns this into a much project for me. (A second project, in fact)

Either way, I'd love your thoughts on this point that Katie brings up.

#4 - WHY TWITTER?

Bill asked me this in an offline conversation. I think the foundation of this question is wondering if I am suggesting that twitter is the thing Alumni Associations should be involved with.

No.

I like the idea of doing a similar analysis of facebook and Linkedin. Katie pointed me to Alumni Futures. This is written by Cal Tech's, Andy Shaindlin. His colleague, Elizabeth Allen, has written in several places about Linkedin best practices. Facebook recommendations are all over the place. I guess I just needed to start some place with twitter. I do think that objectives and strategy are important. I think those should be determined before AA's dive into any one of these technologies.

#5 - YOUR METRICS ARE INTERESTING, BUT DON'T REPRESENT OUR STRATEGY

I have heard several variations of this comment, and I think it is fair to bring up. I used some language in the opening paragraphs of the first post that would lead some to believe that I think a certain way about most of the AA twitter profiles that have been opened. That they are being managed without thought or examination of objectives or strategy. Though that may be the case for many of these feeds, I don't think it's true of all of them. Some of this analysis will come out in the final report and recommendations I'll put together.

That being said, I do believe there is well-intentioned, but faulty, strategy that exists among these feeds. I would like to refrain from talking about this too much prior to the data being collected completely. I am eager to engage in this as a constructive conversation. I think I have some practical suggestions that Alumni Associations can apply that will create both efficiency in the amount of time they spend while increase the engagement level of their alum followers.

If you have any metrics that measure effectiveness of your twitter strategy that are not represented in the tools I selected, I would love to know either the metric you want counted or a tool I might use to capture those numbers.

#6 - WHAT IS THE PLAN?

My plan is to collect data three more times over the next two weeks. This will give us a look at the numbers over a month-long period of time. I plan to invite suggestions into the process along the way so the results are both beneficial and encouraging to the Alumni Association community. Feel free to leave your suggestions.