Category Archives: analytics

Measuring non-profit contribution: @JaimeStein ‘s impact on #Climb4Cord

Jaime Stein represents a new breed of non-profit campaign contributors – one whose efforts can be easily hidden by traditional fundraising measurements.

A 2013 Case Study in Non-profit fundraising [or should we call it contribution raising?]

@JaimeStein is deeply involved in #Climb4Cord; a fundraising event where a select group of executives climb Mount Kilimanjaro to raise funds for the Canadian Blood Services ambitious project to raise funds for a national public umbilical cord blood bank.  This event just happened in August 2013 and the whole team raised an impressive $350K.

By traditional measurement, Jaime was listed as the third top fundraiser (last time I checked)  – a wonderful achievement given the aggressive goals and fundraising achievements of his colleagues in #ClimbforCord.  [let’s give pause to recognize all of them who signed up to climb the side of a massive mountain and committed to raising >$1K]

Climb4Cord

I first became aware of @JaimeStein ‘s efforts – as he announced his 6 – 8 month long training program and invited friends to sign up in a Google Calendar for one of his weekly training hikes in Toronto #KiliHikeTO.    I had the pleasure of walking with @JaimeStein on April 11  <- his blog captures this.

I count Jaime among the new breed of social wunderkind – who are as active outside of their emploi as they are inside it.  Folks who expertly leverage social media or technology partnership to advance their personal ambitions  ( like the impressive @sneiditee @hessiejones @mmonaa @helenandrolia @natandmarie or @greenwooddavis ).  Among his many efforts, Jaime participated in #BeerHikeTO evenings with friends, secured awareness, commitment and generous donation from ING Direct and worked with good folks from Roadpost to secure satellite technology ( DeLorme inReach satellite communicators) to test and send progress of his trek back through social media channels.  [Jaime’s blog post on the very cool technology here].   He no doubt contributed to the over 3100 mentions on twitter, 27 blog posts and over 192 news articles covering the climb.  [sysomos for #climb4cord, #beerhikeTO, #kilihikeTO in the last 12 months].  The folks tweet sharing Jaime’s climb messages included some great Canadian twitspokespeople – the @CEO_INGDIRECT, @DaveoHoots, @CTVCanadaAM, Erica @YummyMummyClub.

Jaime created tremendous awareness and consideration for #Climb4Cord – of course, he was the lead for social media efforts for the climb – but still contributions well beyond revenue.  I think someone like Jaime is needed on every major non-profit fundraising (contribution) drive.  The trick will be to identify the ‘influencer’ properly (recommended reading of @DannyBrown @SamFiorella ‘sInfluence Marketing book as a great start)

But in reviewing the donation website, I was stuck that Jaime’s other efforts were not affecting his ‘rank’ as a fundraiser – and yet – by blogging, running Twitter events, inviting Canadians to joining his personal training – he was likely creating far more impact than revenue.    Most fundraising goals are clearly expressed in dollars — and yet, for a non-profit that also relies on generating awareness of a new cord blood bank and encouraging personal cord  (and blood) donations, non-revenue metrics must be valued as much as generating revenue.   I’m certain Jaime’s efforts are not lost on Canadian Blood Services – they have come across influence marketing in its truest form.  Jaime is personally connected to the cause and happens to be a brilliant marketer (in social and otherwise).  It may just be the website and measurement had not yet caught up to fundraiser like Jaime.   Yet, I am left wondering if there are other non-profits who have yet to measure efforts like Jaime’s  – who is ushering in new levels campaign contribution.

Let me know your thoughts.

@LDillonSchalk

The curve of your #FACEbook; 4 common #facebook #insight curves demystified

By now, I’ve looked at many, many Facebook insights curves working with various brand pages and I’ve come to notice a pattern in what I see.  Here is an explanation of four common Facebook insight curves or charts.  Understanding these patterns will help with understanding the success of Facebook pages.  This is likely of most interest to community managers or analytic geeks.

First a quick recap of the main units of measure on these charts.

  • People Talking About This or “TAT” includes all engagement metrics that Facebook allows – liking a post, sharing it, commenting, presumably any liking per comment and *liking a page*.  I don’t think it is the best measurement of engagement but it is what Facebook allows us to see.
  • New likes per week – indicates any new liking activity for your page.   Why Facebook adds “per week” on this unit and not the other, I don’t know.

Consider that these units of measure are presented as though they are daily activity – but they are NOT.  Each point on the graph represents a rolling 7 day week of data.  So that means the Sept 20th data is actually 7 days of activity ending on Sept. 20th (so Sept. 13 – Sept 20th).  Then Sept 21th is represented by data from Sept 14 – 21.  This is frustrating because true daily activity is muted somewhat.  I’m not sure why Facebook does this nor can I find articles on why using 7 day rolling data would be advantageous over using daily data.  If you have an opinion – please enlighten me!

Also consider that the TAT number contains any liking of a page – which is what the ‘new likes per week’ is all about.  So we are comparing two curves, one containing the other curve within it so we have to deduce that the visual gap between the two curves represents the “success” of the content.

Of course, a liked post can be generated by cheap, low involvement engagement e.g. what is your favorite colour vs. answering a consumer inquiry.  I see tons of ‘cheating’ questions – to the tune of “like this if you put socks on in the morning” – and community managers report that as successful content because facebook monkeys click “like” on the post but it does nothing for building deeper connections with a brand page.  [rant]   So despite charts, there will always be a need for further analysis into the context of the engagement.

Onto the curves.

The Newbie Chart

This is the chart to an unidentified, brand new facebook page.  Our natural cues to its newbie status would be the start of content & number of facebook likes on the actual page (not depicted here).   In looking at this Facebook insights curve,  you see new like and ‘talking about this’ [TAT]  following together.  This is because for every new like, Facebook also records it within their  “TAT”number.  So the TAT number is driven almost entirely by new likes.    Then the community manager took a break – and with a young page, every thing – liking the page & engagement crashes.  But then content reappears which looks like it appeals to the existing fan base.   We see the curves diverge.

The Contest Driven Chart

Contests are the easiest way to ‘cheat’ at Facebook fan (like) growth.  So many many do it and wonder why their community isn’t reflecting the people brands care about.  At the same time, it is a tactic – a reasonable fast one to gain critical mass.  Critical mass allows brands to get into a decent social graph – reaching friends of friends – otherwise the brand is in a room talking to itself.   With a contest under belt,  its a crowded party but possibly in the wrong bar, with the wrong crowd.

So focus on the right half of this chart – we see two bumps with the gray ‘new likes’ line following the TAT line.  This is reflective of new people entering a contest.  It could also be a curve that reflects good content that encourages people to also like a page, but since we know the contest is going on, then know the curve.   At the same time  – there is a bit distance between the curves which indicates that the content either resonated with contest goers (it did, its the Swiffer ‘my man cleans’ t-shirt, Oct. 15) or that the contest asked visitors to do some kind of monkey task (it did, Swiffer’s advertising ‘show us the love or at least like us’).

The ad supported chart

Up, down, up, down… likely in concert with two waves of facebook advertising spend.   To me, the first bump suggests the first ad worked harder or was supported by some kind of like incentive.  The curve drops when the stimulus is removed, and re-appears with ad support (confirmed as I’ve seen the ads).    I don’t see this as a healthy facebook curve at all.  It is artificial – because it is not sustainable without advertising.

The ‘my content went viral’ chart

This is Red Bull’s facebook page – after its sponsorship of Felix Baumgartner’s jump from the stratosphere.   A brilliant capture of content from a brand, in my opinion.  Here we see the facebook curve coming off an ad spend, then the big bump on the right is the release of photos related to Felix.  The content is heavily shared – and although this is a rolling seven day picture, it seems to have been shared over time – given the evidence of new little spikes in the curve top.   As for new likes per week – there is traction.

What is interesting is that this chart represents a community of 32 million.  So the “new likes” are not what is driving the content here – it is the content being shared among the existing fan base – or so I expect.

Another ‘my content went viral’ chart

UK Bodyform’s very interesting video response to a disillusioned man was well received.  For a little community – the content got a lot of eyeballs.  It did not translate well into likes – although there are a few new likes at the right.  It may be that this community did not have a lot of content prior to the video – so the community saw this as a one time contribution, albeit awesome, but not enough to like the page.  That said – this is a page for feminine protection which wouldn’t get much public liking anyways.

I hope this helps with your perspectives on facebook insight charts and your measurement of facebook pages.  Drop me a comment if there is a curve pattern that I could include.