Is your marketing crossing all channels?

Posted by Christopher S Penn on Jul 25, 2011 in Advertising, Marketing, Strategy | 1 comment

Over the weekend at WordCamp Boston, I had the opportunity to chat with and speak in front of many fellow content creators. One of the things that struck me most was how confined our promotional efforts are. SEO is treated as its own space, which people think about without considering social media. Social media is its own space, with no consideration given to advertising.

The reality is that all of the different ways of marketing anything – your blog, your products, your services – work together. They create a sort of marketing synergy that is greater than the sum of each individual channel. Nowhere is this more obvious than in the digital marketing space. Let’s say you’ve just written up a powerful blog post that you’re sure is the next great thought leadership piece. How do you promote it? Most people publish it, hope it gets indexed by Google, and maybe toss out a Tweet or a G+ update, then call it a day.

This is a mistake.

Why? Because not everyone receives your content in the same way. One commenter this weekend said they never read blogs but live in their inbox. Another person said they only see stuff on Twitter; everything else is information overload. A third person said they only read in Google Reader and nowhere else. If you’re just tossing things out without promoting across a variety of channels, I guarantee that you’re missing audience.

For example, a few years back, I had a daily podcast. It was doing fairly well, but then I added an RSS to email option and let people subscribe to it by email. Instantly, I had 20% more audience – that’s how many people found their way to my show but didn’t know how to use the existing RSS-based subscription methods. They knew email, though, and subscribed that way.

What’s powerful about this simple example is that not a single visitor ever asked for the option to subscribe by email. I was silently missing 20% of my audience every single day, assuming that I had captured the bulk of people who wanted the show, when in fact a fifth of the audience I wanted simply wasn’t subscribing. I never knew it until I offered an additional channel.

The lesson here is simple (if not easy): create as many channels as you can reasonably and practically sustain, in order to give people the option to get your stuff by the method they prefer best.

Are you crossing all the channels you have access to?

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How to market your WordPress blog

Posted by Christopher S Penn on Jul 23, 2011 in Advertising, Blogging, Conferences, Marketing | 1 comment

I’m delighted and excited to share some of my ideas, strategies, tips, tools, and methods for marketing your WordPress blog at Boston’s WordCamp event. As I anticipate a fair number of people and A/V conditions that are always less optimal than we’d like, I’m providing the mindmap for the session in advance here, so that if you’re attending (or even if you’re just curious), you can follow along on your own device and not have to rely on squinting at the screen.

Click the image for larger versions.

Would you like a high resolution version you can download and print out? Click here for the high-res PDF.

One cautionary note: without hearing the presentation that goes with the map, there’s a good chance some stuff won’t make sense. If you’d like to hear the full presentation, make sure you request the next marketing conference you attend to book me to speak and ask for this presentation to be a session at the event.

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Innovation has a low Klout score

Posted by Christopher S Penn on Jul 22, 2011 in Advertising, Awakening, Marketing, Metrics | 1 comment

Here’s a minor caution on any scoring mechanism. I mention Klout because it’s got mindshare, but it applies to anything which attempts to rate people by influence.

Innovation has a low Klout score.

You won’t spot the next hottest thing by Klout score. Like all scoring mechanisms of its kind, Klout scores are trailing indicators, which means that by the time the score is high enough for you to notice, it’s too late to get in on the ground floor of an opportunity. It’s just like a stock price in many ways – by the time the stock price is high enough to be really valuable and noticeable, it’s too late to buy in and reap the early adopter rewards.

The same is true for case studies. If you’re waiting for the definitive case study of how to be the market leader, then the market leader isn’t going to be you. The case study is a trailing indicator of success, not a leading indicator.

Trailing indicators are great – they tell you what has worked, they help you to refine processes and fix things that are broken in your current processes. These are invaluable attributes that make them an essential part of your marketing mix. Klout score, PageRank, stock price, AdAge 150 listing, web analytics data – all of these are very effective at telling you what has happened.

The problem is, if you’re looking for what is going to happen, what the clues are to the future, and how you can be ahead of the competition, none of these numbers will be of help. Here’s an obvious example: Spotify.

Suppose you are a music blogger who wanted to find the next trend in music marketing. On July 5 (assuming you hadn’t been following the news and were just trolling Klout scores), if you had been looking for influencers of a score of 75 or more as an indicator of future music trends, you would have missed Spotify. The only reason Spotify was even scored highly at all was that it had already launched in Europe and other parts of the world.

Imagine what’s out there right now that’s scoring in the low 20s and 30s on Klout: startups in near-stealth mode, new ventures, a brand new social service that is just beginning to get a bit of mindshare. The bottom line is, you won’t find them with Klout or any other rear-facing, trailing indicator – and the opportunity to get in early will pass you by.

Does that mean you should abandon trailing indicators? Of course not. But if you want to find the future, you have to instead be looking at trendspotters, listening and watching to people who are experimenting with new stuff all the time. The only way to find what’s innovative and new is to listen a lot, explore, and try new things.

Who knows? Perhaps you’ll discover the next big thing – and 6 months after it launches and you’re the industry expert on it, your Klout score might go up, too.

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How to analyze Google+ timestamp click data

Posted by Christopher S Penn on Jul 21, 2011 in Advertising, Marketing, Metrics | 3 comments

Yesterday I shared some interesting information about how Google+ was assigning a unique, UNIX timestamp (client-side) to every clicked link. More than a few people asked how to actually get that data, since it’s not obvious. Today, we’re going to dive deep down the rabbit hole and show you how to do it yourself, step by step. You’ll need Google Analytics, a text editor, and a spreadsheet program. You will also need to get your nerd on. Ready?

Caveat lector: this guide overwrites the User Defined variable inside Google Analytics. If you currently have custom data being recorded in User Defined, do not use this guide as it will overwrite your existing User Defined data!

First things first. You’ll notice that Google Analytics doesn’t record query strings. Google+ sends traffic by query string. Remember, this is how a link appears from Google+ to your site:

http://plus.google.com/url?sa=z&n=1310267970417&url=http%3A%2F%2Fwww.christopherspenn.com%2F2011%2F07%2Fhow-to-measure-google-plus-with-analytics%2F&usg=Fl5VGX6zftZiPhe6N1gENpM0EDQ.

This is how the same link, and all Google+ links, show up in Google Analytics:

Notice that all the tracking stops after the question mark in the referring URL? That’s where the good stuff is. So how do we get to it? Google Analytics provides an obscure way to record query strings that requires you to override its default behavior. Here’s how to set it up. First, go to your Google Analytics account’s settings. This is the main settings area for your account, not any one particular tab.

In your site’s settings, add a custom advanced filter:

Once you have the filter screen up, make a filter that looks like this:

Hit save, and your Google Analytics account will automatically begin collecting query data. Let it collect at least a day’s worth of data, more if you’re not especially active on Google+. Then go into your Google Analytics account and look at the User Defined data:

In order to find just Google+ data and not other query strings, you’ll need to apply a filter to the data. Use sa=z and you’ve got a list of what you’re looking for. If you want to isolate a specific URL that you shared on Google+, use that instead of the blanket sa=z variable; remember to URL encode it or you won’t get anything useful.

Next, set the rows displayed to 500 (the maximum Google Analytics will let you export from a single sub-report like this) and then hit your export button to your preferred data format:

Now you’ve got your CSV file that’s in a format which is terribly unhelpful. Open up your text editor, trim off the top section, replace commas or tabs with line breaks, and extract any line containing sa=z to a separate file. If you use BBEdit on the Mac or UltraEdit on the PC, this should be relatively trivial. What you should be left with is a pile of URLs that looks like this:

Once you’ve got this pile of URLs, you need to break each URL into pieces so you can export the G+ timestamps. To do this, in your text editor, execute a find and replace for the & and = characters, replacing them with commas. Then open the file in a spreadsheet package. You’ll end up with a nice, neat list of columns. Sort this by an individual post you want to measure, which should be column 6. Isolate the post, then sort by timestamps, ascending. Hit the charting button on the timestamp column and voila! You have a velocity chart for that post, because UNIX timestamps are sequential integers.

Remember that you’ll need to flip the axes to put the timestamps along the X axis; that will show you how tightly packed the middle of the chart is, where your posts have taken off.

Try this methodology out and see if it works for you, if it sheds any light. Those of you who are hardcore spreadsheet jockeys can even do comparisons of different posts to see how different kinds of content can have different sharing velocities. If you trim the last 3 digits off the G+ timestamp, you can also then transform it into standard spreadsheet datetime formats and assess what times of day and days of the week your content reaches velocity the fastest.

For example, if you notice that the inflection point on your posts tends to be around 11 AM local time, you have a better idea of when you might want to push out material that needs attention. I’m sure someone will eventually turn this sort of complex data analysis into an overly simple “When is the best time to Plus” blog post, so to avert this, I recommend that you do the data analysis for yourself. Everything you need has been provided for you already.

I hope this post gives you some additional ideas for data analysis using Google+ timestamps, as well as gives you some new things to learn with the tools you already have. You have everything you need already to do some amazing stuff. Go forth and do so.

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Google+ and Search Signals: Tinfoil Hat Edition

Posted by Christopher S Penn on Jul 20, 2011 in Advertising, Marketing, Metrics | 20 comments

I was recently examining Google+ and how it transparently redirects through plus.google.com as it sends readers to your website. One of the oddities I noticed was this:

http://plus.google.com/url?sa=z&n=1310267970417&url=http%3A%2F%2Fwww.christopherspenn.com%2F2011%2F07%2Fhow-to-measure-google-plus-with-analytics%2F&usg=Fl5VGX6zftZiPhe6N1gENpM0EDQ.

Take a look at how the URL starts. The second query string variable looks awfully familiar. If you’re not familiar with query string variables, they’re the key/value pairs in the URL that have an equal sign. For example, let’s break up that G+ URL into key/value pairs:

• http://plus.google.com/url?
• sa=z
• n=1310267970417
• url=http%3A%2F%2Fwww.christopherspenn.com%2F2011%2F07%2Fhow-to-measure-google-plus-with-analytics%2F
• usg=Fl5VGX6zftZiPhe6N1gENpM0EDQ.

URL is pretty obvious, that’s the URL to the post I shared about Google+ Analytics.

USG appears to be a hash of some kind, but none of the usual reverse hash hacking tools made sense of it, which means it’s probably just a unique identifier, such as which Google+ post the URL was linked from.

SA is their standard URL discriminator; Z appears to be the type assigned to Google+.

That leaves us with the mystery of N. In the example above, N is a 13 digit number, 1310267970417. At first glance, it doesn’t appear to be anything, but if you look closely, it resembles a UNIX timestamp. Feed it into a UNIX timestamp calculator, however, and it returns a senseless result:

Sat, 27 Sep 43490 13:06:57 GMT

However, I poked around a bit more and did a regular date-time to UNIX conversion. The day and time this post was written is: 1311151020, which is only 10 digits long. So what if we trimmed the mysterious G+ number down from the right to match the same number of digits as a current date UNIX timestamp? 1310267970 turns into:

Sun, 10 Jul 2011 03:19:30 GMT

Now isn’t that interesting? That’s closer to the time that I posted the article. Here’s where it gets funky. I went to that post and clicked through just now, as I was writing this. The N variable now reads: 1311165558. That’s just seconds ago.

Wed, 20 Jul 2011 12:39:18 GMT

Google+ is assigning a UNIX timestamp with an extra three digits – I’m guessing a sort of microtime – to every outbound click from G+ at the time of the click. Let me state that again: they’re uniquely timestamping every CLICK from G+ in the URL in realtime. Not just when a post was shared, not just when a post was reshared, but Every. Single. Click.

Here’s where we get into tinfoil hat territory. There’s no logical reason to be timestamping clicks for things like spam control or malware control. You can, and they do in other places, just shut down the destination URL or redirect it to a warning page.

So why would G+ be timestamping every outbound click? This is pure speculation, but the only reason I can think of is that you’d want to track velocity on a link’s popularity. You’d want to track not only how often was it shared or reshared, but how engaged were people with the link, and over what period of time. When I post a link on Google+, it seems that G+ is measuring when clicks occur relative to that content – how popular it is over any given period of time.

We’ve known for a while, we’ve read in many places, that Google is using social signals to influence search. What we have here may be the next iteration of that. Twitter’s data feed with Google came to an end, but they’ve beefed up their social base with G+, and if they’re timestamping every single click, that data can be used to assess the validity of content and the virality of it in a very tight, compact fashion that any data analysis tool can process. Further, by putting the timestamp data right in the URL, they may be making it easy for other Google properties like Google Analytics to process G+ data with a minimum of overhead.

How easy are they making it? Using my existing Google+ data, this is my Google+ analytics blog post mapped in Excel using the timestamps from G+:

Notice that with this explicit timestamping, I can measure exactly when the clicks to the article really started to take off, and then when they plateaued again. Google is paying attention to this data, so it’s probably a good idea for you to pay attention to it as well.

If you don’t know how to collect this data… well, stay tuned. Tomorrow I’ll show you.

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