Twitter Analytics: Presentation from Social Media Masters

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)

These are a few of my favourite things (about Twitalyzer)

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.

2. Percentile

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.)

3. Goals

Data in a vacuum is meaningless. Twitalyzer lets me set goals for individual metrics, to ensure that I’m actually measuring something in context.

4. Comparisons

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.

5. Recommendations

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.)

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A month of fun with ClickTale

As a self-confessed geek, when I hear about a new tool and there’s a free option I can play with, I naturally implement it right away. After hearing the Beyond Web Analytics podcast discussed ClickTale, I took the opportunity to implement it on my blog for a little “new analytics tool fun”.

After a month playing around with this tool, here are some of my impressions:

Unique value

It is not merely repeating with what your Google Analytics, Omniture, WebTrends, etc tracking tells you. There is a definitely unique value. Think of the standard web analytics tools as telling you visitor’s behaviour between pages (e.g. visitors go from page X to page Y, exit at page Z.) ClickTale tells you what they do within a page (how far down do they scroll? Do they start filling in your form? What do they click? Where does their mouse move?)

Recordings of a site visit

One of the original offerings of the ClickTale was simply recordings of your visitors’ behaviour on your site. You literally watch users scroll up and down, click a link, go to another page, etc. It’s like sitting over their shoulder, or user testing without the option to ask them why they did something. However, no one can possibly watch all the videos, especially on a large site. The real value of the tool is what ClickTale added next: the aggregation of all of those videos into heat maps.

Aggregated heat maps

You can view an aggregated heat map of:

  • Mouse moves
  • Clicks
  • Scroll reach
  • Attention (via mouse attention)

The scroll reach is pretty interesting, especially on a blog, since normally the main page is a six-mile-long history of previous blog posts, and it’s interesting to see how far down people scroll.

ClickTale uses mouse over attention to estimate eye tracking (due to the correlation between the two) but are pretty clear that they don’t intend this to be a perfect replacement of eye tracking, merely an affordable way to get close to that kind of information.

Example heat maps:

So as you’ll see, the value of the heat maps is:

  1. Not having to troll through multiple videos for insights. That’s just not possible with a site with millions of visitors.
  2. In-page information that definitely complements what is provided by your standard web analytics tool.

For a blog specifically, the heatmaps can also be a way to see what of your content people are reading. If a visitor clicks to read a specific post, obviously you know they took this action even in a standard web analytics tool. However, where they read a blog post on the main page, ClickTale can fill in the gaps of what they read via scrolling and attention. This is a great insight missing from a standard tool.

A concern for frequently updated sites (such as blogs) might be the impacts of a site changing throughout the day, via adding new posts. Never fear, that has been taken care of: you can choose which version of a page you want to view the heatmaps for, if there are multiple versions throughout a timeframe.

Some other nifty features:

Form analytics

I only saw a demo of this, as my site isn’t really form-heavy, but to be honest, this thing rocks. Who starts filling in a field then stops? Who has to refill in a form? How much time do they take to fill in each field? What is form engagement vs form submission? This information is much richer than a “X number saw the page that had the form on it, then Y% saw the thank you page.” It’s pretty awesome. Check out this demo of it on ClickTale’s site:

Page and Site Analytics

ClickTale will also tell you which of your pages are the:

  • Most engaging
  • Most clicked
  • Most errored
  • Least scrolling
  • Slowest loading

The engagement time is pretty sweet also. In a world of tabbed browsing, a visitors may come to your site, read your post, but not close the page. (“Tick, tick, tick” goes Google Analytics time on site.) I myself tend to have multiple browser tabs open with links I’ve clicked from Twitter. ClickTale measures the time they actually spend engaged with the page, via mouse moves etc. It’s a richer metric than time on site.


I’ve only mentioned some of the functionality of ClickTale that I enjoyed. There are also options to search, find and watch videos matching certain criteria (e.g. videos from visitors coming in through search, or seeing a certain page – great for watching playback of site errors.) There is also an option for Omniture integration, which I didn’t try (as my blog doesn’t use Omniture) but is nice knowing it’s there for enterprise use.

All in all, my conclusion: ClickTale doesn’t replace a standard web analytics tool (nor do they claim it does, or should) but it’s a great supplement to give you more in-depth information about what people do on a page. I believe a clear competitor for this product is TeaLeaf, which I have seen a demo of, but not been in a position to use. The main thing that sways me towards ClickTale, even on an enterprise basis, is the price tag. TeaLeaf definitely seems a more costly solution. Now, it’s completely possible that TeaLeaf’s price tag is justified by the functionality; I haven’t used it so I can’t speak to the differences. But unfortunately, the reason I haven’t used TeaLeaf is because I couldn’t get past the price tag …

The best part?

Very easy to implement: Two lines of code (I could implement it. ‘Nuff said.) And seriously – all of this with only two lines of code. No special click tracking or form tracking. It’s as easy as implementing Google Analytics.

FREE! They have a free version that you can use on small volume sites. Plenty for us web analytics geeks to play around with! Now, there’s some functionality you miss out on with the free version, but it’s plenty to get you into the tool and allow you to evaluate whether the insights may be worth a small investment.


I was fortunate enough to be given the opportunity to use ClickTale on my blog at an enterprise level access (thank you, ClickTale and Shmuli Goldberg!) Some of the features may only be available via paid subscriptions, and not in the free version, but the free version is definitely of value and worth checking out.

However, also keep in mind I used it on my blog, not on a larger corporate website. There may be some functionality that I’d like to have on a larger site that I didn’t notice was missing, just because of the size of the site I was looking at. I don’t claim this tool is the magic cure for any of your analytics ills, but it’s definitely worth looking at, to see if it might help answer some of the questions left open by your standard analytics tool.

Plus? It’s fun!