This is one of those things that has stuck with me ever since I read it. It’s an account from a Colombian rider, Santiago Botero, in the Tour de France, about being overtaken by Lance Armstrong in a particularly tough mountain stage.
We all get so busy managing the day to day of our work, and the crises that come up. But the truth is, we need to find time for the long-term efforts , to think forward as to what initiatives we can start on now. It is tough to prioritise these when they won’t ease the present pain points, but they’re crucial to our development in the future.
It’s not just about the race, about that present moment. It’s about what you did to train, to prepare, to be ready for future challenges.
There I am all alone with my bike. I know of only two riders ahead of me as I near the end of the second climb on what most riders consider the third worst mountain stage in the Tour. I say ‘most riders’ because I do not fear mountains. After all, our country is nothing but mountains. I train year-round in the mountains. I am the national champion from a country that is nothing but mountains.
I trail only my teammate, Fernando Escartin, and a Swiss rider. Pantani, one of my rival climbers, and the Gringo Armstrong are in the Peleton about five minutes behind me. I am climbing on such a steep portion of the mountain that if I were to stop pedaling, I will fall backward. Even for a world class climber, this is a painful and slow process. I am in my upright position pedaling at a steady pace willing myself to finish this climb so I can conserve my energy for the final climb of the day.
The Kelme team leader radios to me that the Gringo has left the Peleton by himself and that they can no longer see him. I recall thinking “the Gringo cannot catch me by himself.”
A short while later, I hear the gears on another bicycle. Within seconds, the Gringo is next to me – riding in the seated position, smiling at me. He was only next to me for a few seconds and he said nothing – he only smiled and then proceeded up the mountain as if he were pedaling downhill.
For the next several minutes, I could only think of one thing – his smile. His smile told me everything. I kept thinking that surely he is in as much agony as me, perhaps he was standing and struggling up the mountain as I was and he only sat down to pass me and discourage me. He has to be playing games with me. Not possible.
The truth is that his smile said everything that his lips did not. His smile said to me, “I was training while you were sleeping, Santiago.” It also said, “I won this tour four months ago, while you were deciding what bike frame to use in the Tour.I trained harder than you did, Santiago. I don’t know if I am better than you, but I have outworked you and right now, you cannot do anything about it. Enjoy your ride, Santiago. See you in Paris.”
[Part 1 originally published in Colorado Biz on 01.18.11.
Blog post updated on 03.06.11 to include Part 2 of the article.]
The internet is a wonderfully measurable place. Businesses are able to use online data to drive strategy and measure return on investment. However, the wealth of data that makes the online world a prime space for analysis is also leading to consumer concerns over privacy. Facebook privacy controls, data capture, ad targeting and mobile applications have all been the subject of privacy discussions in the media.
A recent survey by USA Today and Gallup suggests that only 35% of respondents believe that “the invasion of privacy involved [in behaviorally targeted online ads] is worth it to allow free access to websites”, with younger respondents (40%) being more willing to accept this than older respondents (31%). However, while only 14% would allow all companies to target ads to them, another 47% would be willing to allow the advertisers they choose to target ads.
With so many concerns out there about data capture and privacy, what is a company to do to ensure their behavior and data practices are not called into question – or made front-page news?
What kind of data does your company use?
First, your company needs to differentiate between types of data capture, understand what you are leveraging, and the current climate around different types of data use.
Understanding the current landscape
Recently, the Federal Trade Commission released their draft report on Consumer Privacy. The FTC’s report distinguished first and third party data capture, with different views as to what consent and regulation should be required for each.
First party data includes web analysis done through tools such as Google Analytics, Webtrends and Adobe Omniture, for the purpose of improving consumers’ online experience and a company’s profitability online. First party data use also includes first-party marketing: a company recommending products or services based on a consumer’s previous purchases. The FTC recommended that this type of data capture not require specific consent, as these are considered commonly accepted business practices.
Third party data capture, however, is considered separately. This includes companies that deal in the buying and selling of information. For example, ad networks who buy and sell data to allow delivery of highly-targeted advertising. The FTC’s main concern regarding third party tracking is not banning the practice, but rather, allowing for informed consumer choice. While the FTC declined to declare opt-in or opt-out as the appropriate method for expressing consumer choice, the FTC did call for a Do Not Track mechanism, enforced through either legislation or industry self-regulation.
Legislative vs. Self-Regulatory approaches
The FTC’s recommendations open the door for potential legislation of online privacy and data capture. However, the Commerce Department has recently recommended self-regulation.
The Commerce Department disfavored prescriptive rules, noting the need for an approach that allows for rapid evolution and innovation, while enhancing trust. The Department called for voluntary but enforceable codes of conduct that promote transparency in data collection and use, and recommended enlisting the “expertise and knowledge of the private sector” in this regard.
While online data and privacy may seem new and uncharted territory, this is simply a new medium for similar challenges faced off-line. For example, consumer acceptance of tracking and targeted advertising in exchange for free online content is not too different to accepting grocery store data capture via loyalty cards in exchange for discounts. The difference is that online data capture is a newer, without a well-established procedure for privacy safeguards, and a lack of education about what the benefits or exchanges for tracking may be.
What is required in the industry is two-fold:
Finding the appropriate way (not necessarily legislatively) to establish and regulate those safeguards online; and
Educating consumers about the types of data capture and use, and potential benefits, to allow for informedconsent.
How can a company protect itself?
So how can a company protect itself, in light of the current uncertainty around online privacy?
Safeguard consumer privacy as if you are already legislated to.
This has two benefits: If enough companies voluntarily safeguard consumer privacy, legislation may not be needed, leaving flexibility for companies to find the right way to protect privacy within their own business model; and
If legislation does occur in the future, your company should not require major changes to your privacy model to be in line with the requirements.
Follow FTC recommendations and integrate privacy considerations into your company’s daily business practice, by:
Taking reasonable precautions to protect the safety and ensure the accuracy of data;
Only collecting data required for a specific, legitimate business need (rather than capturing data “in case” it can later be monetized); and
Ensuring your data retention periods are reasonable.
For any third-party data capture, make your practices transparent (this means not burying information behind legal jargon!) and educate your consumers. Advise what data is being captured, the benefits to the consumer, and provide an easy way to opt out. (A hint: if the only benefits are for your company, and not the consumer, you should expect a high opt-out rate.)
For companies in business overseas, keep in mind that privacy laws may differ between countries. For example, Europe’s privacy laws are already stricter than the United States, and will potentially receive further overhaul in 2011 to modernize the 1995 Data Protection Directive.
Prepare for the future
Online privacy is not likely to quiet down in the coming months. However, by being proactive and considering consumer privacy in your daily and long-term business strategy, your company can set itself up on the right side of proposed legislative or self-regulation.
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.)
So you have a content-based site, and you want to know whether your visitors’ time on your site was successful.
You have two options:
Attempt to measure this via their on-site behaviour; or
Ask them, via one of the many “voice of customer” solutions.
This post will deal only with #1.
Content sites can be challenging to measure the success of a visit, simply because there’s not necessarily one path. Rather, revenue is often generated via advertising, where page views = ad impressions = revenue.
If you are trying to measure the success of your content site, there are a few ways you can go about this.
Page Views per Visit: Seeing a large number of PVs/Visit could indicate a visitor has found information that is useful to them and has had a successful visit. However, a lost or confused visitor would also generate a large number of page views. How do you distinguish the two?
Time on Site: This too could indicate a successful visit. However, it could also indicate that someone is spending time searching for (and not finding) what they want.
So how could you better measure success?
Focus on valuable pages. A high number of page views to actual content suggests a more successful visit than a high number of page views that might include, say, site searches. Therefore, focus on PVs/Visit (or Time Spent) to a subset of pages. Thiscan be more valuable than site wide PVs/Visit or Time Spent.
But you can do better. First, you need to assess why your content site exists. What behaviour can a visitor perform that would indicate they successfully found what they were looking for?
For example, your site exists to provide information X – that’s the goal and purpose of your site. Therefore, a visitor seeing content X achieves that goal, and suggests they had a successful visit.
If your site exists for reasons X, Y and Z, a successful visit could be a one that saw one or more of of X, Y or Z.
Setting up goals or segments around these behaviours can help you measure over time whether your visitors are performing these behaviours. Can better navigation drive up the percentage of visitors successfully completing this task? Which tasks are more popular? Are you even doing a good job of communicating what your site exists for? (If very few actually complete that main task or tasks, I’d suggest probably not!)
A final note: the intention of measuring a successful visit to your site is to measure this success from the point of view of the visitor. Is your site doing a good job of providing what visitors want?
This “success” doesn’t necessarily tie to short-term revenue for a content site. After all, a successful visit might be one where the visitor comes in, finds what they’re looking for immediately, and leaves. However, that visitor might generate more ad impressions by getting completely lost on your site. Good for you … in the short term. But doesn’t mean they had a successful visit to your site, nor does it bode well for your long-term revenue.
Therefore, measurement of visit success should be analysed alongside measures of revenue success, while carefully weighing the long-term benefits of successful visits (and happy visitors) against the short-term revenue generated by “lots and lots of page views”.