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In Uncategorized on September 2, 2011 at 8:40 pm

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If you can’t measure it, you can’t manage it – some links to free social media metric tools

In Business Education, DCU Business School, Digital Marketing, MBS in Marketing, MSc in Business Management, MSc in E-commerce, Uncategorized on April 21, 2011 at 11:33 am

“In physical science the first essential step in the direction of learning any subject is to find principles of numerical reckoning and practicable methods for measuring some quality connected with it. I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of Science, whatever the matter may be.”[PLA, vol. 1, “Electrical Units of Measurement”, 1883-05-03]

As the semester at DCU Business School comes to an end, I find myself with marginally more time and have decided to refocus again on sharing some nuggets in the long form. This particular article will be a work in progress and so I apologise in advance for the “list” nature of this and that it will be expanded and polished over time. NOTE: I have excluded the big three search engines as a tool because you should be using these anyhow.

As Lord Kelvin said, to measure is to know. There is an ongoing debate on whether you can calculate the ROI on social media – I don’t particularly understand the perspective that you can’t – if there is an action, it can be measured. Once you accept it can be measured, then the next question might be whether it is feasible (economically, technically, ethically etc) to do so. Then once you have some measurements, how do you interpret this data. This blog discusses some free tools that you may be able to derive some value from.

A good starting point is David Berkowitz’ (@dberkowitz) list on “100 Ways to Measure Social Media”. David has also made his presentation to the PMA available. I like this presentation (the list is embedded) as he contextualises his thinking.

My interest and focus is increasingly around understanding how business re-orient from the demo-graph to the social graph and understanding network theories is essential. I like Dan Halgin and Stephen Bogatti’s paper on Network Theorizing.If you accept this re-orientation, you need to rethink your marketing and customer engagement strategy dramatically – in many respects it requires getting to know your customers on a much more deeper level and finding a point on the social graph that you can intersect or levers for influence. This is not really something new. Historically, this is how we always did business – people would ask friends, families, neighbours, authority figures for recommendations on people based on their centrality within a community, their social activity and their connectivity or network. Today, we have many different types of network – in the real world and the virtual and what it means to be connected to someone means different things in each network or does it? Is your Twitter network the same as your Facebook one or your LinkedIn one or your FourSquare Friends or your Contacts list on your phone or even your Christmas Card list ? How much influence do you have on these networks? What does it mean when your “friends” don’t “like” you? Being a “friend” used to be hard but now it is just complicated.

Visualizing your social network or the social network of your target customer is a good first step. There used to be some neat free tools around like Agna and now LinkedIn is looking at this, in a relatively basic way, using InMaps. Wikipedia have a good page on Social Network Analysis software. Understanding the network topography is only a start. Who are these people?  Who has influence? Well, there emerging popular players in the social media universe are Klout (Klout have an app – sociofluence but some influence interpretation reports seem inconsistent) and Peer Index. I like both for different reasons. Klout is easy to use and can be used to craft and refine your personal and institutional brand. They have made a pretty good stab at categorising social media users (and in this context Facebook and Twitter users initially) and provide a lot of data points that can be used for marketing purposes. I like Peer Index because it allows you to create peer groups and compare them against activity, authority and audience and therefore allows quick visualization of influence. When looking at these profiles, I look at the score and see what’s driving them. If it is very facebook driven, you might ask whether the person’s user’s influence is driven by personal social activity. Another piece of data to help establish they type of influence the target has, is their topic analysis – does it reflect personal casual interests or personal professional interests. Both can be useful for marketing purposes but may be interpreted differently for employment purposes. There are a couple of other similar tools like Grader (Grader offer tools to rank you on blogs, twitter, facebook, foursquare etc etc) and Twitalyzer. While there seems to be some correlation between Klout and Peer IndexGrader  is often a mystery to me and I don’t really understand the utility of the foursquare grader. Another snapshot tool is Twitter Search and OpenBook – the former allows you search all twitter feeds and the latter all facebook accounts with public settings -you may get an insight in to what people are really saying about you. This is best used with keyword analysis via Google.

Sentiment Analysis seems to the be one of buzzword bingo winners of recent times. I’m a big fan of the sector and have tried Radian6, Scout Labs and others but these are expensive for a small to medium sized business. I believe people feel have a more positive sentiment to positive people and indeed the people you want to be associated and are more likely to help you are generally those of a positive outlook. However, people who are unhappy or negative often have a problem that you may be able to solve and they also represent opportunities. Twitrratr is a quick snapshot of the twitter sentiment surrounding a brand, product, person or topic based on analysis of positive and negative words (links to words sourced from Jim Sterne).

Some other twitter tools which may be useful to look at are Tweetreach and Twunfollow. The free Tweetreach  tools give you a snapshot of the last 50 tweets of  user and provides you with analysis of reach (by users and impressions), tweet type and the contributors to reach. While many people focus on the size of their audience, few monitor who is unfollowing them. Unfollows may be interpreted as failed attempts to engage – these people have decided to follow you because of a message and then decided to unfollow you, why? Understanding the unfollow motivation may provide an insight in to your messaging style and how you might refine communication. For free, Twunfollow provides you with a 7-day analysis and trending graph for both follower and follower growth and then lists unfollows, follows and deleted followers (eg they may have been deleted by themselves or for spamming). Each unfollow entry includes how long they had been following you from. My students have recently been messing around with Twalue and Twength (although I may have first (re)tweeted this. Twalue puts a monetary value on your twitter account and twength measures your average twitter length. The former isn’t really useful without comparative data and then I think the way the valuation is done could be perceived negatively. The latter may have value in that long tweets may not be retweeted or when retweeted are truncated and therefore the message is impaired. So Twength may be useful for refining a factor that impacts on amplification.

A note on blogs – blogging platforms come with a variety of good analytical tools.  These are largely covered in David Berkowitz’ list but it is worthwhile looking at Jason Stamper’s  Blog Value Index and Avinash Kaushik’s Blog Metrics: Six Recommendations For Measuring Your Success.

One observation which may be useful is that success on one social network does not necessarily translate to other social networks – a blogger may not transition to microblogs and have the same impact. Similarly, the number of followers does not equate to influence.

Other reading? I liked Jim Sterne‘s book, Social Media Metrics and his blog. Why? It had lots of stuff I had seen elsewhere but bundled them together nicely in to a customer lifecycle structure. It was also a fast and easy read! I also really like Gary Arndt’s blog post on Klout vs PeerIndex, mostly because he has engaged the executives from Klout and Peer Index via comments and there are some great insights in these comments.

Please feel free to leave comments and suggest some sites I may have forgotten or need to check out.