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At Do The Green Thing, we spend a lot of time finding the best inspiring Green Things, and sharing them with you on our website, Facebook page, in our monthly emails and on Twitter. We love to hear what you think, and naturally, we're also keen to know if we're helping you to Do The Green Thing. We track the numbers for all our digital presences to see how many people we reach, and how interesting you find us. There are a lot of numbers to collect, and it's not always obvious what they mean, or whether they're useful. So we've been doing some work recently to come up with a simple system to collect data from all the different sources (our email software, Facebook, Twitter and so on), combine it, and give us some monthly indicators of how well we're doing. We've posted up a slideshow here that shows how our system works, what assumptions we're making, and what we get out of it. And we're sharing it for two reasons: 1. If you're involved in something a bit like Do The Green Thing, you might find it useful as a model for measuring your own success. You'll likely have to tailor it to fit your circumstances and objectives, but it might provide a useful starting point 2. We'd love to get your feedback on whether you think this is a good model, and how you would improve it. So please let us know what you think, and if you find it useful. Thanks.
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Green Thing social media metrics
15 December 2010
www.dothegreenthing.com
Introduction
• What is Green Thing? “Green Thing is a not-for-profit public service that
inspires people to lead a greener life. With the help of brilliant videos and
inspiring stories from creative people and community members around the
world, Green Thing focuses on seven things you can do - and enjoy doing.”
• Green Thing and social media. Most people who see Green Thing content do
so through online social networking tools: Facebook, Twitter, YouTube, email, etc.
• Social media measurement. We want to measure our impact through these
channels. How many people consider themselves ‘fans’ of Green Thing; how
many people engage with us; how much do they tell their friends about us?
• Feedback. We like feedback on how we’re doing. If you think we could measure
this stuff better, or you see a flaw in our reasoning, let us know. And if you’d like
to draw on this for your own social media measurement, go ahead. We’d love to
know if you find it useful. (Email me at [email protected])
What we’re trying to do
• Show the trends over time in key measures of our success: how
many fans we have, how engaged they are, how much influence we
have through the social web.
• Show the relative effectiveness of all the different social networking
tools we use.
• Be confident in our figures so we know we can rely on them to make
decisions, and they stand up to scrutiny.
What we’re not trying to do
• Campaign measurement. We run a lot of different campaigns,
sometimes several simultaneously. We have a different way of
measuring the success of campaigns, typically because we want to
answer different questions — and those questions vary so widely
across the campaigns.
• Insights for optimisation. We collect the raw data monthly. We’re
not using this for real-time review of campaign activity.
• CO2 saved. Our mission is to get as many people as possible Doing
the Green Thing, to prevent climate change. We have a system
(validated by experts) that helps us determine how effective we are
at changing behaviour and saving CO2. This is not that system.
What we’re measuring: the audience model
InfluenceFans
Direct
reach
Engagement
This diagram shows how we model
our audience.
The following slides show how the
parts fit together …
What we’re measuring: the audience model
Fans
‘Fan’ is a loose term – they’re
people who subscribe to our email
newsletters, like us on Facebook,
follow us on Twitter, or have
otherwise indicated that they like
hearing from us.
It gives us an idea of the potential
of our direct ‘first order’ reach.
What we’re measuring: the audience model
Fans
Direct
reach
Almost everyone we reach
directly is already a fan. But of
course we don’t reach all our fans.
For example, not everyone who
‘likes’ us on Facebook actually
visits our page.
But we’re not so interested in how
many people we reach; we’d rather
know how engaged they are …
What we’re measuring: the audience model
Fans
Direct
reach
Engagement
Of the people we do reach, only
some of them are engaged. i.e.
interested enough to do something:
click through to the website, hit the
‘Like’ button, or write a comment
on our Wall.
What we’re measuring: the audience model
InfluenceFans
Direct
reach
Engagement
With social media, many more
people can experience our content
than those we reach directly. This
can be through direct, personal
advocacy (e.g. blogging or re-
tweets), automated publishing
through networks (e.g. when
Facebook places stories in your
news feed), PR or paid media.
Influence is a measure of this
extended impact of our work. It’s
difficult to determine an absolute
figure, because we don’t always
know if someone has seen
something in their digital stream.
But we can track changes over
time.
What we’re measuring: types of activity
• Platforms. We experiment with a lot of social networking platforms to see
if they’ll work for us. We track all the significant ones: Facebook, Twitter,
email and our blog. We split out the data for each platform so we can see
how well we’re doing in each.
• Campaigns. Most of our content forms part of a campaign, e.g. Glove
Love or Buy Nothing. We often use one platform (like Twitter) to support
several campaigns at the same time. We collect data for all, but we
aggregate it for each platform. Campaign tracking is done separately.
• Ambient/continuous activity. As well work to support specific
campaigns, we also use these tools to share other content, news and links.
We collect data for this, but as with campaigns, we aggregate it all on the
platform level.
The end result is that we have a record of how well we’re doing on each
platform over time, with all campaign and ambient activity counted together.
How we’re doing it
1. We collect metrics for each platform monthly and put them in a
spreadsheet.
2. Each metric is assigned as a type of measure: fans, reach,
engagement or influence.
3. We apply a weighting where necessary to account for any
misleading raw data. (Currently no weightings are applied, but this
is kept in as an option.)
4. The spreadsheet does some maths to groups metrics by type (fan,
engagement, reach), aggregate data for each type on each
platform, and sum across each quarter. It then draws charts on a
‘dashboard’ worksheet to show the relative performance of
platforms, and trends over time.
How we’re doing it: the spreadsheet
1. All the social networks
we use are listed in
rows, split out by the
campaign activity
running in each. The
include different Twitter
accounts, Facebook
pages apps and groups
2. Each metric is classified
as a measure of fans,
reach engagement or
influence
3. Space for a weighting
factor if we want to use
it
4. All metrics collected
monthly
1 2 3 4
How we’re doing it: Email
• Our email delivery platform provides the standard metrics on
delivery and recipient behaviour:
Metric Type
Subscribers Fans
Emails opened Reach (direct)
Click throughs to website Engage
Forwards Influence
How we’re doing it: Facebook metrics
• We use Facebook insights for our page and for the apps we use for
specific campaigns
• We also have a legacy Facebook group — we don’t collect metrics
for thisFacebook page
Metric Type
Net new page likes Fans
Active users Reach (direct)
Like and comments Engage
User posts Engage
Stream impressions Influence
Sustainability's Next Top Model Competition
Metric Type
Net new application installs Fans
Active users Reach (direct)
Content created Engage
Saved Shop
Metric Type
Net new application installs Fans
Active users Reach (direct)
How we’re doing it: Twitter metrics
• We currently use several tools to collect Twitter metrics.
• The tools currently available don’t quite support the ideal model we
have in mind, shown here:
Metric Type
Followers Fans
Click-throughs Engage
Mentions Influence
Retweets Influence
Use of our hashtags Influence
Reach of retweets and mentions Influence}Currently not directly
measurable (though estimates are possible for individual tweets)
How we’re doing it: Twitter metrics (continued)
Twitter’s forthcoming in-house analytics product could fill in these
gaps. In the meantime, we use 3rd party tools to supplement the basic
metrics Twitter currently provides:
• Hootsuite: using trackable URLs, we can measure click-throughs to
our website
• Klout: provides some measure of our influence in Twitter
How we’re doing it: Blog
• Almost everything we produce ends up on
dothegreenthing.com/blog
• Google Analytics and Feedburner give us all the data we need and
more
• Some Green Thing content is syndicated elsewhere (e.g. on
weblogtheworld.com). At the moment, we’re not measuring this.Metric Type
RSS subscribers Fans
Visits Reach (direct and indirect)
Comments Engage
Referring sites Influence
How we’re doing it: 3rd party measures
We’re always trying out new tools to see how they can help us to
validate the data we collect directly from the tools we use (e.g.
Facebook Insights) and fill in the gaps in that data where necessary.
Currently, we collect data from:
• Klout to measure Twitter influence
• PostRank Analytics
Assumptions we’ve made in order to come up with a practical system
• All platforms are equivalent. e.g. Someone who likes our page on
Facebook is just as much of a ‘fan’ as someone who follows us on Twitter.
• No de-duping between platforms. We know that, for example, some of
our email subscribers also follow us on Twitter. As the platforms don’t talk to
each other, we have no systematic way of determining how many duplicates
we are counting. This is less important when reporting trends over time.
When we report absolute figures, we apply a de-duping factor based on our
best knowledge of how much we’re over-counting.
• Where we count reach, we’re counting ‘number of times we reach
people’, not ‘number of people reached’. The platforms we use don’t
consistently report uniques.
• We’re counting ‘engagements’, rather than ‘engaged people’. The
platforms we’re using don’t consistently report ‘number of people
interacting’, but rather ‘interactions’.
Problems, constraints and questions
This system is a work in progress. We welcome any thoughts on how it could be
improved. Some issues we’re thinking about:
• Does the model make sense? We want to be able to share these figures.
Are they meaningful to others? Does our categorisation stand up to scrutiny?
• Distinguishing direct, extended, and potential reach. We have no way of
telling if someone we reached on Facebook came there because they’re a fan
(i.e. direct), or if they followed a link from a blog (i.e. extended). And with
some tools, we can’t even be sure that we reached them at all. How many of
our Twitter followers actually see our tweets, for example?
• Twitter metrics. At the time of writing, Twitter’s official analytics service is
still in private alpha. The publicly available alternatives do not give us the data
we need. (They tend to focus on popularity or metrics for individual tweets.)
• De-duping. As mentioned above, should we use our weighting score to
account for over-counting? If so, how can we justify the weightings we apply?
Problems, constraints and questions (continued)
• How can we measure real, personal advocacy? At the moment, this
is difficult for three reasons:
1. Some advocacy metrics are not readily available (e.g. number of re-
tweets over a time period)
2. Some metrics fall into a grey area between engagement and
advocacy – to what extent is liking something on Facebook a form of
recommendation? Is it equivalent to a re-tweet?
3. Most social software has built in functions to propagate content
through the network. Facebook, for example, publishes content from
pages you like onto your wall. This helps us extend our reach, but we
can’t really count it as direct advocacy
• Dependence on shifting toolsets. We have no guarantee of sustained
access to consistent metrics (as we would with server logs for a website,
say). We know from experience that available metrics can be changed
and withdrawn by the 3rd party services we rely on (e.g. Facebook).
