I also found it interesting to compare and contrast my Twitalyzer “Impact” score historically at different events. eMetrics SF 2012 led to my highest Impact score to date (but note that Followers is a consideration in Impact scores, so later conferences are likely to have a higher score.)
Definition of “Impact”:
Impact, as defined by Twitalyzer, is a combination of the following factors:
The number of followers a user has
The number of references and citations of the user
How often the user is retweeted
How often the user is retweeting other people
The relative frequency at which the user posts updates
Some of you may know that I tend to tweet a little at conferences. I don’t bother taking notes, but rather archive all the tweets for the conference hashtag (mine and others’) and use those as my conference notes. (A totally valid lifestyle choice, Jim Sterne! 🙂 )
Since I go the trouble of downloading a Twitter archive, I thought I’d share the archive from eMetrics NYC (held in October 2011), in case anyone would like to to read or analyse.
I was disappointed to not be able to join Keith, Jason and Olivier on the first two Measure “Mobcasts” – those darn international flights sure do get in the way! However, that doesn’t mean I won’t take the opportunity to put in my $0.22. (It would be my $0.02, but I was in Australia, and their dollar is worth more, so I figure I’ve got the exchange rate working for me.)
I wanted to add what are just a few (minor) “parting thoughts” after having an opportunity to hear the guys so deftly discuss their opinions on measuring social media influence. So here are mine …
1. Measuring Social Media “Influence” is Necessary
The reality is, while companies (and even individuals) would love to have an opportunity to engage with every voice that reaches out to them via social media, that kind of engagement isn’t necessarily scalable or realistic, and even if it was, there would still be a need to prioritize the order in which a company reaches out to people.
While that doesn’t mean, to Jason’s point, that anyone should be ignored because their Twitalyzer scores aren’t high enough, some kind of measure of where to start is realistically necessary, especially for companies with a large number of social interactions.
2. Social Media Influence Measurement Isn’t Perfect
I feel like part of where we get hung up is in thinking that if a measure isn’t perfect, it’s not useful. I agree with the guys that a measure of “influence” should be considered in context of other data, and I also agree that it’s probably more realistic to call it “potential influence.” After all, you never know whether someone who is considered to have social media influence is actually going to influence behavior of fans/followers/friends.
As we love to say in the analytics industry – you can’t manage what you don’t measure. However, the unfortunate reality is that you can’t measure everything that you would like to manage. (And our attempts to do so often end with “KPI” Dashboards that show fifty metrics instead of the one thing that executives want, because that measure isn’t truly possible at this stage.)
How could we measure true influence? Maybe: Person A engages with Person B, or shares a positive experience with everyone. Person B then goes, “Huh – I hadn’t thought of going to Restaurant X for dinner” and heads on over. Well, sadly we don’t have that insight. (Yet, or maybe ever.)
So what do we have? We have measures that look at, in the example of Twitter, how many contacts someone has, how often their tweets are shared or responded to, as a proxy for influence. Does that mean that the person following will “monkey see monkey do?” No. Is the measure perfect? No. Is the measure useless? No. Understood for what it is, it can be helpful. Blown out of proportion, of course it’s not. However, I know one thing – digital measurement is a constantly evolving industry. We will get better at this. But that doesn’t mean that we can’t do something with our “first draft”.
For anyone who is interested, my presentation from Social Media Masters is available for viewing on Slideshare:
Twitter Analytics: Michele Hinojosa, Red Door InteractiveTopics include: Twitter research for competitive intelligence, hashtag and network analysis, download, export and backup tools, Twitter account measurement using Twitalyzer and Klout and tracking Twitter links back to your website. Originally presented at Social Media Masters Twitter workshop in San Diego (2/11/2011)
For those of you who don’t know, Twitalyzer is one of my favourite Twitter measurement tools. Why? Well for one, they let you see the math. As someone in the digital measurement industry, I find it hard to put a lot of faith in a “secret sauce” approach to measurement. (“Just trust us, this is your score.” No thanks.)
I have been using Twitalyzer for months now, first through a free option, and now through a paid subscription. Why did I pay? Because it’s worth it. (And FYI, the individual subscription is cheaper than a cocktail. That was a very easy sell for me.)
So (Von Trapp style) … here are a few of my favourite things.
1. Customisable metrics report
Over the months, the number of metrics included in Twitalyzer reports has grown. Great, but for me, it’s approaches a “TMI” level. Therefore, I love that I can actually customise not only what order different metrics appear, but also whether they appear at all. If I decide something doesn’t help me manage my little corner of the Twitterverse, I can choose to hide it, and simplify the metrics report. To me, this is especially useful in simplifying the world of social media to those who may be newer. Choose the key metrics you need them to see, and perhaps add to those over time.
Now, to be honest, I’m looking forward to evolution of how you customise the metrics report (currently it’s a little more cumbersome than I’m sure it will be in the future) but the customisability alone wins big points with me. (FYI, it also transfers across accounts – so if you have a number of Twitter usernames connected to your Twitalyzer accounts, you don’t have to repeat the process every time.)
So what do I care about?
I’m still playing around with this, but here’s what I am currently showing on my Twitalyzer metrics report:
Impact: My impact is defined by how many followers I have, how many references there are to me, the frequency at which I’m uniquely retweeted and retweet others, and the frequency at which I post. (I call this one the Twitalyzer Ubermetric.)
Engagement: The ratio at which people reference me vs. those I reference.
Influence: Is the likelihood that a Twitter user will either retweet or reference me.
Retweeted: How often I am retweeted. I find this useful to help me understand what content of mine my network feels is worth sharing.
Signal: Whether my tweets contain a link, mentions or retweets another user or include a hashtag. Aka a way to measure how many of my tweets are of the “Ohhhh, my cat is so cute!” or “Yum, I just had pancakes” variety vs. something actually interesting. I’m sure in some networks, depending on your contacts, low signal isn’t a big deal. But I’m conscious of not shoving too much “status” type stuff out there. (I figure general “here’s what I’m up to” is what Facebook is for.)
Generosity: The percentage of time that I retweet others.
Clout: The likelihood that I’ll appear when searched for in Twitter. I won’t lie – this one still makes me go “Hmmm …”
Followers: Number of followers I have.
Lists: Number of lists I’m on. Often it’s a good idea to look at what the lists are (e.g. I’m on some lists of “People who RT-ed me” … probably not one that the list creator even reads!) but it’s definitely a “nice to watch.”
Velocity: The frequency at which I post.
Referenced: The number of times I’ve been mentioned on Twitter.
Potential Reach: The number of followers I have + the number of followers those who retweet me have. This attempts to estimate how far a tweet I send can be viewed.
Effective Reach: Takes my retweeting followers x my influence (the likelihood that I’ll be retweeted.) This attempts a more realistic estimate of how far a tweet I send could go.
Klout Score: Comes in through Klout. (The “secret sauce” tool.)
So why do I care about these metrics, and why don’t I care about others?
My reasons for Tweeting in the first place, and for tweeting about the topics I do, are fairly simple: to learn via reading what others post, to contribute to the discussion, and to build relationships in the community.
Measuring my signal ensures that I’m not posting junk that might alienate my Twitter contacts. (Sure, my cats are cute, but I’m pretty sure nobody cares.) Monitoring retweets, followers and lists is a good indication of whether what I’m posting is considered of any value by my contacts. Monitoring references to and by me, and my retweets of others, is a good indicator of whether I’m engaged with the community.
Basically, I’m choosing to focus on the things that relate to my goals in using Twitter, and as such I’ve currently hidden some metrics in Twitalyzer.
This is a small one, but when I first started using Twitalyzer, you could only see “Percentile” by clicking into a metric. Now they have incorporated it on the metrics view, visible at all times. I love this! The percentile basically tells me that my score is the same or better than X% of the Twitter users tracked by Twitalyzer. This can be helpful when you realise that a Impact score might seem low, yet still be in a fairly high percentile. (Aka it makes me feel better…!)
A nice future add-on would be a tailored percentile, based on a subset of Twitter (perhaps those you follow, or a list you’ve created.)
Data in a vacuum is meaningless. Twitalyzer lets me set goals for individual metrics, to ensure that I’m actually measuring something in context.
I love the ability to compare myself to other Twitter users on a variety of metrics. To me, this is another way to benchmark myself, and perhaps even help to set my goals. (What’s feasible? Well, what is X’s score? Okay, I’ll aim for something similar.)
However, I’d definitely love to see a future ability to pre-create a number of comparisons, rather than doing this individually each time I log in.
It’s pretty standard for a tool to tell you how you measure up. It’s less common for one to tell you how to go about moving the needle. Twitalyzer will actually give you recommendations of what is more and less important for you to do to positively affect your impact scores.
6. Network Explorer
Now, to me this is more informative than necessarily something you’re benchmarking against, but it’s still super cool. Basically the Network Explorer is a visual map of the people and topics you are connected to. (Because who doesn’t like to play Six Degrees of Awesome #Measure Folks?)
7. It’s about the community
So you follow these people on Twitter, or they follow you. So what?
Twitalyzer can help you understand:
When your network is online (e.g. time of day, day of week) and where they are located. (I definitely think there are some improvements that could be made in the presentation of regional information, but that’s an aside.)
This can be very helpful information if you’re trying to decide when the optimal times to post, say, a blog post are.
Who the most influential members of your network are, who your most influential “friends” are (based on your communication with some members of your network more than others), and who appears to to influence you.
Network Activity (Time of Day):
8. It’s about me
Curious about what dates or time of day you tweet? Are mentioned? Retweeted? Never fear, Twitalyzer is here:
But what about the content? What hashtags do you use? What communities and discussions do you tend to be a part of? What of your content has been retweeted lately? Which of your links were clicked? You can find all of that out.
There’s even the beginnings of sentiment analysis. Now, sentiment analysis is a toughie. (Especially if you have folks in your network who are, shall we say, sarcastic? Noooooo….) The reality is that there aren’t many great sentiment analysis solutions out there that don’t involve human assessment of sentiment. So to be honest, I tend to view all sentiment analysis (included Twitalyzer’s) as interesting, but not necessarily something to hang my hat on. That said, I do like the ability to play around with what words you consider to be negative and positive:
9. Integration with Google Analytics
I’m also looking forward to jumping more into the integration with Google Analytics – but that might turn out to be a topic for another time (entirely of itself.)
10. Export options
The ability to export data does not go unnoticed!
Last but not least … (definitely not least!)
11. Customer service
I’m not kidding you. Even before I was a paying customer, Jeff Katz at Twitalyzer was always enormously helpful, and though I’m a now only a meager paying customer (with my little individual account) he still goes above and beyond to help solve problems. He rocks.
And as a little FYI, if there’s something you can’t get working right in Twitalyer, take a hop over to Firefox or (shudder) IE. I’ve had very few issues using Twitalyzer in Chrome, but the rare issue I’ve had has been browser related. (Which I discovered because the aforementioned lovely gentleman Jeff Katz helped me out.)