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Green Thing social media metrics 15December 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 andrew@dothegreenthing.com)
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 foroptimisation. 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 This diagram shows how we model our audience.  The following slides show how the parts fit together … Influence Fans Direct reach Engagement
What we’re measuring: the audience model ‘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. Fans
What we’re measuring: the audience model 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 … Fans Direct reach
What we’re measuring: the audience model Fans 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. Direct reach Engagement
What we’re measuring: the audience model 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. Influence Fans Direct reach Engagement
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 We collect metrics for each platform monthly and put them in a spreadsheet. Each metric is assigned as a type of measure: fans, reach, engagement or influence. 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.) 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  2  3  4 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  Each metric is classified as a measure of fans, reach engagement or influence Space for a weighting factor if we want to use it All metrics collected monthly
How we’re doing it: Email Our email delivery platform provides the standard metrics on delivery and recipient behaviour:
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 this
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: } 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.
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:  Some advocacy metrics are not readily available (e.g. number of re-tweets over a time period) 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? 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).
Thank you andrew@dothegreenthing.com

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Do The Green Thing Social Media Metrics

  • 1. Green Thing social media metrics 15December 2010 www.dothegreenthing.com
  • 2. 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 andrew@dothegreenthing.com)
  • 3. 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.
  • 4. 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 foroptimisation. 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.
  • 5. What we’re measuring: the audience model This diagram shows how we model our audience. The following slides show how the parts fit together … Influence Fans Direct reach Engagement
  • 6. What we’re measuring: the audience model ‘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. Fans
  • 7. What we’re measuring: the audience model 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 … Fans Direct reach
  • 8. What we’re measuring: the audience model Fans 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. Direct reach Engagement
  • 9. What we’re measuring: the audience model 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. Influence Fans Direct reach Engagement
  • 10. 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.
  • 11. How we’re doing it We collect metrics for each platform monthly and put them in a spreadsheet. Each metric is assigned as a type of measure: fans, reach, engagement or influence. 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.) 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.
  • 12. How we’re doing it: the spreadsheet 1 2 3 4 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 Each metric is classified as a measure of fans, reach engagement or influence Space for a weighting factor if we want to use it All metrics collected monthly
  • 13. How we’re doing it: Email Our email delivery platform provides the standard metrics on delivery and recipient behaviour:
  • 14. 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 this
  • 15. 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: } Currently not directly measurable (though estimates are possible for individual tweets)
  • 16. 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
  • 17. 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.
  • 18. 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
  • 19. 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’.
  • 20. 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?
  • 21. Problems, constraints and questions (continued) How can we measure real, personal advocacy? At the moment, this is difficult for three reasons: Some advocacy metrics are not readily available (e.g. number of re-tweets over a time period) 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? 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).