Must we measure?
In November, Emer Coleman asked: Social media – Must we measure? In a fascinating post, Emer discusses how tricky it is to present the benefits of social media in traditional business cases. Emer argues that:
Making a business case to use these channels is like making a business case to read the newspaper; it suggests that there’s a decision to be made about whether to engage or not.
Both the post and all the comments are well worth reading. I’ve included a couple here:
At the moment, the argument for stats on social media is rather like measuring the success of a speech by seeing how loud the microphone is. What we need to do is work on getting the right people into the room (whether it be physical or virtual) and then talking to them in the right way – just like we do in the real world.
Emer’s reply to a comment by Ranjit Sidhu:
What social does add is the “softer”, human voice that compliments all of the quantitative work that government does. It helps us understand what might really matter to people rather than what we, as government, think matters to people. But these as I say will remain subjective opinions but the more collective voices we can hear the more likely we are to reach a more informed consensus.
So what *can* we measure?
I wasn’t looking for evidence to support a business case – I’ve given up on that – but was at least trying to find some metrics.
In response to Steph’s question, I had a go at a list which I’ve included below:
|Platform / type||Measurable (probably)||Additional indicators|
|Followers, re-tweets, mentions||Sentiment, specific feedback, requests|
|Likes, shares, followers||Comments, requests|
|You Tube||Likes, views, shares||Comments|
|Followers, repins, likes||Comments|
|Search||Mentions||How the search is phrased|
|Web site||Visits, views, likes||Comments|
|Flickr||Views, favourites||Comments, referrers|
|Open Data||Downloads, views||Re-use, apps developed (and their popularity)|
So, you can gather at least some ‘how manies’, ‘whens’, ‘likes’, ‘views’ etc, but so what?
- ‘Followers’: If we see follower growth, can that really be attributed to us?
- I looked at Facebook usage recently in Hampshire, and pretty much all age groups are showing growth, so we might do nothing and still see follower numbers increase*
- Many people have several Twitter profiles – I know one individual who has 12 – in theory you could be followed by one person, many times
- Bots: Aargh! They aren’t human, they’re generally spam, and they definitely aren’t of any value in metrics
- ‘Likes’ are probably a bit more helpful. Most people probably won’t say they like something when in fact they don’t
- ‘Favourite’ might be interpreted as ‘like’, but that’s not necessarily correct – it’s more of a bookmark, and could just as easily be used to remind the reader of something that annoys them
- ‘Re-tweets’ don’t necessarily mean approval – lots of people retweet as a way to share, but not endorse
- Appearance in Search and Blogs probably indicates a level of interest, but you need to look at the content and context to establish if that’s good or bad
- Downloads of open data is an interesting one. It probably doesn’t fit within the definition of social media, but I thought I’d mention it anyway
- In theory data could be downloaded just once and then be re-used, mashed-up, or whatever and become massively popular without the data publisher ever knowing what they’ve started.
- James Cattell got a great debate going about open data on the UK GovCamp discussion board by asking: “Why isn’t #opendata done yet?”
What does meaningful digital evaluation look like?
I’d love to know the answer!
I look forward to comparing notes with friends and colleagues at UK GovCamp on 19th January, and hopefully learning a bit more about a tricky subject.
Photo credits (with apologies)
Mountain Bluebird Wikimedia Commons: http://commons.wikimedia.org/wiki/File:Mountain_Bluebird.jpg