Category Archives: Twitter #Measure

#eMetrics Boston: Twitterific!

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A few fun facts about eMetrics Boston on Twitter:

  • During the conference timeframe, there were 2,726 tweets from 499 users, averaging 5.5 tweets per user. (For comparison, eMetrics San Francisco saw 3,241 tweets during the conference from 622 users, but it was also a more heavily attended conference.)
  • The top 20 contributors to the #eMetrics hashtag were:

MicheleJKiss 295  (don’t judge me)
BloggerKrista 189
measurefuture 138
june_li 112
eswayne 76
andrewjanis 75
rdo 67
RachaelGerson 66
deniseburns 65
jimsterne 47
Stuart_Wood 45
AnyaPrimavera 43
LdsWebAnalytics 43
codydbailey 40
iwanttobesocial 40
SashaVerbitsky 39
tgwilson 39
Wilson_Lopez 39
johnlovett 35
emetrics 33
JoseAnalytics 33

The tweet that reached the furthest (thanks TweetReach!) with over 430,000 impressions was:

(And in case you’re curious, the second highest also mentioned Gilligan.)

And in case you’re curious what we were talking about:

Thank you to the lovely and clever people at TweetReach for the spiffy data!

eMetrics Tweet Activity

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Tweet stats:

3,241 total tweets during the conference time
59 tweets per hour
38% of conference tweets were retweets
622 unique contributors to the #eMetrics hashtag

Top tweet topics:

Top tweeters:

Most Retweeted Tweets

This year, eMetrics had a competition for the most retweeted tweet. The winner received a blue bird (and fame and glory, of course.) The competition was judged by the lovely folks at TweetReach and announced on the last day of the event.

In order, the most retweeted tweets were:

 

Twitalyzer “Impact” Score

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

Related post: Top Takeaways from eMetrics SF 2012

TakeFive with TweetReach interview

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[Originally published on the TweetReach blog]

Welcome back to TakeFive with TweetReach, our ongoing interview series with notable members of the social media analytics and measurement community. This week we’re thrilled to welcome Michele Kiss Hinojosa, a self-confessed analytics geek and Director of Digital Analytics at Red Door Interactive.

TweetReach: Welcome Michele! Let’s start with talking about how you got started with social analytics. What got you interested in measuring social?

Michele: I first got into digital measurement through web and advertising analytics at Kelley Blue Book. As I started expanding my horizons and wanting to learn more about the digital analytics industry, I started joining in conversations in social media — the Yahoo Web Analytics group, Linked In, Quora, but especially Twitter. For me, social analytics started mostly as a curiosity, just playing around with different solutions and analysing social traffic to my little blog, or analysing the social media behaviour of the online web analytics community through the #measurehashtag.

Now, at Red Door Interactive, my team of Digital Analysts and I get to help clients understand the impact of conversations they’re having with customers, including on the website, in social media or through a variety of acquisition channels.

TweetReach: What metrics are most important for your job and your company? What should we be measuring? Beyond that, is there anything we shouldn’t be measuring? Are there any “bad” metrics?

Michele: I don’t think there are “bad” metrics per se, just less useful ones. There is an evolution as companies grow from a simple like/follower approach to looking more at business impact. This isn’t really surprising, given a lot of companies also embark on social “because we should”, but without strategy or goals for doing so. Ideally, companies should embark on social initiatives with clear goals (e.g., decrease call center volume, drive sales, drive traffic to the website, save on other marketing budgets, etc) and understand what, in a perfect world, you would want to measure. From there, figure out if you can. Do you have the right toolsets? The necessary data integration? If not, come up with something that gets you close, or gives you directional insight while you build out the rest. I’m not saying wait until everything is perfect before you do anything, but make sure you know where you want to get before you start working towards it.

TweetReach: What are your recommendations for someone just getting started with social analytics? What should they do first? What are some important considerations?

Michele: For an analyst thinking about diving into social media, they need to first get involved in social media themselves. I don’t think you can measure what you don’t understand, and getting involved in a variety of social channels is key to understanding them. (And no, just having a Facebook account doesn’t count.) Each channel is different and the goals of being involved are different. I try new social channels all the time. They may prove to not be “my kind of thing” (and no one can possibly keep up with all of them and hold down a job, too!) but at least play around and see what they offer, how the channels differ and how they might be used for different goals or different businesses.

There are key books I would recommend reading – John Lovett’s “Social Media Metrics Secrets”, Jim Sterne’s “Social Media Metrics” and Olivier Blanchard’s “Social Media ROI” (and converse with these guys on Twitter! They are great guys and are always up for a good conversation.) Not to mention a myriad of blogs out there.

From there, start doing it, even if you just start by analysing your own accounts. Better yet, find a local business or non-profit to help (so you can attempt to tie to actual business metrics.) You’ll learn more from doing (and, let’s be honest, making mistakes) than you ever will from a book.

But it’s important to keep in mind social media is just one marketing channel. It’s great to have an interest in social analytics, but like other areas, it needs to be kept in context of the overall business and marketing efforts.

TweetReach: Let’s talk about consistency in measurement. There are a tremendous number of tools and approaches used to measure social media performance, which can produce results that are difficult to compare. Do you see the industry evolving towards a more standardized set of metrics or do you think we’ll continue to see a lot of variety and experimentation?

Michele: I’m going to give the very on-the-fence answer: Both. While social analytics often starts as just “likes” and “followers” for companies, pretty soon executives (and hopefully, good analysts!) are trying to tie this to actual business value, and look at social media in the context of other marketing initiatives. Profit or revenue driven are standardised and can apply across all channels, including social. However, let’s be honest: sometimes that’s hard to measure! It involves tying together different data sources, understanding attribution, and trying to measure what may sometimes be unmeasurable. (Do I know that you bought my product after you saw your best friend’s Facebook post raving about it? Maybe not.) But while the answers won’t be perfect, companies have to try to get as close as they can.

On the other hand, new social channels crop up every day, and while these too need to be tied to profit, they’ll also have their own in-network metrics that marketers and analysts will keep track of, and use to understand behaviour. (After all, somewhere there’s a 12-year-old in his garage creating something that will blow Zuckerberg off the map.)

Ultimately, social needs to be tied to business objectives like any other initiative, but the methods we use to do this will get more sophisticated, and I think there’s a lot more experimentation still to come.

TweetReach: We’re hearing a lot about influence right now; everyone wants to measure influence and target influencers. What are your thoughts on measuring influence in social media? What’s the best way to determine who is influential for a particular campaign or initiative?

Michele: Influence is a great example of where social analytics has room to grow. What businesses care about is who influences sales (or leads, or referrals, or whatever your business objectives.) Social tools are measuring “influence” on retweets, or Facebook likes, or video views. I can understand why businesses want to understand who their influencers are, but I think we need to keep in mind the limitations of a lot of current measures of influence — they’re likely not measuring influencers of the business metric they actually care about. That’s when it will be truly useful.

At the same time, I worry about the uses that current influence metrics are put to. I can see a use in using influence to prioritise, for example, response to requests. (For the same reason that food critics get the best cut of meat, those with online influence can have a big impact if they have a negative experience, and I can understand companies wanting to provide excellent service.) But I hope it’s not used as a metric of “you’re not worthy of my time.” Simply put, I can see using influence to determine who to respond to first, but not who to respond to at all.

I also worry about the use of influence in areas such as recruiting. I hope companies make their decisions off more than one number, and look at a candidate or potential consultant’s actual track record, results and skills.

I think these concerns just speak to the overall reality with a lot of social media metrics today — they can be useful in context, but as one standalone metric, we may sometimes attach too much significance, without enough consideration, analysis and scrutiny.

TweetReach: Thanks, Michele!

Getting into Twitter for Digital Analytics

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[Originally published by IQ Workforce]

Perhaps you’ve been working in digital measurement for a few years, or maybe you’re new. You keep hearing about Twitter and wondering whether you should jump on the bandwagon. Well, you’ve come to the right place.

Why should I join Twitter?

  1. To learn: Step outside the sandbox of your own company, your own analytics solution, and your own challenges. Your eyes will be opened and you’ll start thinking about the bigger picture, and bring your what you learn back to your organisation.
  2. To engage with others: It’s a fantastic opportunity to meet and build relationships with others in the industry. You can debate, discuss challenges, throw ideas around and form connections that may benefit you in the future.
  3. Get help and help others: The web analytics community on Twitter is an amazingly generous group of people. Take @usujason or @VABeachKevin, who respond to fellow analysts’ Omniture questions on a daily basis. Oh – did I mention neither of them even work for Omniture?! Having a problem with Google Analytics? Throw it out. Others may have tackled this already and can give great advice.

So how do you get started?

  1. Create a Twitter account. You can sign up at http://twitter.com/
  2. Advice for choosing a username:
    • Twitter can be a great opportunity to create your “personal brand.” Using your name, or something close to it, is a good idea. Using your name also helps when it comes time to meet people in person, as they’ll recognize your name from your twitter username.
    • Try to keep your username separate from your current place of employment. (E.g. @TomSmith instead of @TomAtCompanyX.) If you change companies in the future, it’s easier to not have to change your Twitter username. (Obviously though, if you are using Twitter on behalf of your company, this will be different.)
    • Keep it short. Tweets are limited to 140 characters, so the longer your username, the harder it is for people to retweet you. (I can’t really throw stones here, as my username is pretty long, but at least try to keep it on the shorter side.)
  1. Set your Twitter photo (because being a Twitter new user “egg” is totally uncool.) Try to pick one that will help others identify you, should they meet you in person. That means no blurry artsy photos, or pictures taken from a mile away. It can be helpful to keep a consistent photo across networks (e.g. Twitter and Linked In) and try not to change it too often. Remember, Twitter isn’t Facebook – people don’t know you personally, so changing your photo often will often mean they suddenly don’t recognize you.
  2. Create a bio: This will tell people a little about you so they can decide whether to follow you – so make it informative.

Now for some Twitter basics:

  • Retweet: Reposting another user’s tweet, either as-is or with your own comments, indicated by using “RT” or “via.” For example, a retweet with comment might look like this: “Great article! RT @useryouareretweeting: I like this article: http://www.somearticle.com”  Keep in mind that while a retweet isn’t technically an endorsement, but it can be construed as one, so add your commentary if you are retweeting something you don’t necessarily agree with.
  • Mention: A mention involves you referencing another Twitter user. Mentions can go back and forth as you have a conversation with someone on Twitter.
  • Hashtag: Twitter users will preface a term with a # symbol to allow easy searching for tweets on the same topic. For example, “@user: I love #knitting”

Next, you’ll want to find people to follow.

A good place to start is by finding the main hashtag used by a community. For web analytics, this is the #measure hashtag. Start reading the #measure hashtag, and follow users whose content you find interesting.

You may also want to look at the hashtags for vendors you use. #Omniture (or #OMTR) is a popular one for Adobe Omniture users, but you can also check out #webtrends, #coremetrics, etc. In fact, following the vendors themselves can often be a good place to get started – most typically have a corporate Twitter account and post industry news.

Do I have to follow someone if they follow me?

No! Twitter is not reciprocal like Facebook. Just because you follow someone doesn’t mean they have to follow you, and vice versa. This makes it easy – follow someone if you want to read what they have to say. Don’t follow them if you don’t. It’s really that simple.

Keep in mind, one of the benefits of a mutual follow is that you can send each other Direct Messages (DMs.) These are 140 character messages that are “private” between you and the person sending it. However, while these messages don’t show up in a Twitter stream, applications can access DMs, so to be safe, don’t include anything truly private in them.

Start posting

There are lots of Twitter users who just lurk (read but don’t post) but to get the most out of it, start posting. Throw in your viewpoint into a discussion (if they’re happening on Twitter, they’re not private, and no one will complain that you’re butting in!) or post links to interesting content you think others would enjoy.

You can also ask questions. You would be surprised who participates in the #measure discussion and is willing to take the time to answer. You can ask questions about the analytics tool you’re using (e.g. “How do I do XYZ in #Omniture?”) or even just a general “Has anyone seen any research on XYZ?” The #measure community is an amazingly generous community who really do help each other, so start asking – and answering others.

From Twitter.com to Clients to Apps

You can choose to use Twitter via the main twitter.com site. However, many choose to use a Twitter client such as HootSuite or Tweetdeck to allow them to customize their layout. For example, you may want to be able to view your home feed (the tweets of everyone you follow) plus a list, plus a search, all side by side. Check out some of the different Twitter clients and see what strikes your fancy. You may even bounce back and forth between different clients.

There are also great apps for your smartphone or tablet. On the iPad or iPhone, my favorite is Echofon, but there is also the official Twitter app, HootSuite or Tweetdeck. On Android, I primarily use TweetCaster, but you have HootSuite, TweetDeck and many other options too. Play around with a few to see which works best for you. Most have a free version with ads. Once you find one you like, you can pay a few bucks for the premium version for ad-free tweeting.

Create lists

Once you start following users, you may choose to start creating Twitter lists. A list is a group of Twitter users that you group together. That way, you can read just content from your list, rather than from everyone you are following. For example, maybe you would have a “Web Analytics” list vs. “Social Media” vs “Email Marketing.”

I have a list called “Favs” – I follow a lot of people, but these are my “core people”, so if I’m busy and don’t have a chance to read what everyone I’m following is posting, at least I will keep up with my must-read folks. Feel free to check it out: http://twitter.com/#!/michelehinojosa/favs

“But I don’t have time!”

We’re all busy, and in the case of web analysts, normally overloaded. After all, it’s hard to hire good people so most companies are strapped for resources.

My advice if you’re “too busy”:

  1. Start small. Just follow 5-20 key people. It’s not hard to keep up with a small number.
  2. Check in regularly, for short periods of time, to break it up. It’s easier to find five minutes at a few times than an hour block of time.
  3. Mark posted articles to read later, when you have more time.
  4. Use Twitter to actually help you do your job. If you’re struggling with something, seek out help from the community. (Make sure you are abiding by your company’s social media and non-disclosure policies, of course.)
  5. Smartphones can help, by turning time you’d be wasting in a doctor’s office or waiting for a friend into valuable catch-up-on-Twitter time.

So what are you waiting for?

 

A heartfelt thank you

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On Tuesday, 15 March 2011 the WAA held the inaugural Awards Gala. (For the record, it’s pronounced gah-la. Not gay-la.) It was a wonderful event – a chance to spend time with the lovely people in this industry, and make new friends. The Gala was, in my opinion, a hugely successful experience – I can’t wait to attend the next one.

As a part of the Gala, the WAA handed out the very first Awards of Excellence. The categories were:

Client/Practitioner of the Year
Most Influential Agency/Vendor
Most Influential Industry Contributor
Web Analytics Rising Star
Innovator/Technology of the Year

I myself was so incredibly humbled just to be nominated for the award of Web Analytics Rising Star, let alone become a finalist. Those two alone seemed to good to be true.

Imagine my shock to win …

So, from the bottom of my heart,  thank you.

Thank you first and foremost to the kind soul who even thought of nominating me. Thank you for the WAA members who kindly voted for me to be a finalist. And thank you to the Awards judges, who made such a difficult choice from an amazing list of finalists, who are all so deserving.

I have been working in web analytics for a few years, but really only got involved with the community last May. I have loved every minute I’ve spent getting involved with the WAA, the Analysis Exchange and #measure. I learned more in six months than I had in years prior.

So all I can say is thank you. I really, truly love this community of amazingly smart people. Thank you for welcoming me so generously into it. Thank you for letting me learn with you and from you. Thank you for the time we’ve spent discussing, debating and encouraging each other.

Congratulations to the award nominees, the award finalists and the award recipients. You are what makes this community such an amazing thing to be a part of. I am humbled and grateful for the award, but more thankful still to be a part of such a wonderful community.

WAA Award

Twitter Analytics: Presentation from Social Media Masters

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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)

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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.)

Like this post? Related content:

The Web Analytics Community

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Like many web analysts, I pretty much “fell” into this field. Coming from Law and Psychology degrees, it certainly wasn’t a clear path. At the time, I happened to be an assistant, and the web analytics team happened to need “temporary” help. Five years later, here I am: incredibly grateful to have fallen into a field that is fascinating, in high demand, and full of smart, engaged people.

Here’s a great example: the Analysis Exchange. This program brings together “students” of web analytics, mentors to support them, and non-profit organisations needing analytics assistance. (Note: I say “student” because you don’t need to be an actual student.) There are currently 1,000 members, and no open projects. As many needs as there are out there, the analytics community is rushing to fill them.

The fascinating thing about the Analysis Exchange is the skill level of some (probably most!) of the “students”. My first project (and currently only project – see above, no open projects!) went a little like this: Wow, my student is smart. I hope there’s even anything I can help him with! (He later said there was. I hope he wasn’t humouring me…!)

In fact, as Analysis Exchange mentor Jason Thompson commented on Twitter recently, many of the people we look up to in the analytics community are offering their services as students! When I myself first signed up, I was torn between student and mentor. Yes, I currently manage a team of analysts. However, would I be knowledgeable enough in a completely different setting and business model? Not to mention,  any good analyst can always use more hands-on experience! So I won’t lie – going in as a student definitely crossed my mind. The basis for my eventual decision to be a mentor was that I wanted to leave the full-on student experience for those interested in web analytics, who may not have access to data or real life examples.

So here’s how our community works. You have a group of people who are in high demand, flat-out at their “real jobs”, with a real life outside of work. Despite this, they volunteer their time for 1) their own continued education and development and 2) to assist others in their growth. Most of these people never really think they’re ready to be a mentor, because no one considers themselves to be an “expert”. We think there’s always more to know, more to learn.

Web Analytics is developing fast. But with these people in our community, there is no worry that we won’t keep up. In fact, we’ll keep pushing, and moving our field even further forward.

PS. You know you’re addicted to Twitter when you have to consciously write “the web analytics community” rather than the “#measure community”.