A little more than a week ago I could not sleep. I was about to ask the analytics community for money at what has proven to be a tough time for many, and I was about to make a statement about the values that our company holds. It’s a little nerve-wracking I admit.

I shouldn’t have worried in retrospect.

Jason Thompson of 33 Sticks and I set out to raise $40,000 for Black Girls CODE by agreeing to match up to $20,000 in donations. We gave ourselves two weeks to raise the money and meet our goal.

It took three days.

I just want to say I am personally HUGELY GRATEFUL for the support we have received from the digital measurement community in this campaign.  Nearly 100 individual donations large and small have pushed us past our goal and now we are well on our way to raising over $50,000.

We still welcome your donations, instructions to do that are pasted below, but again, from the bottom of my heart … thank you all. Thank you for thinking beyond your own lives and considering the lives of others. Thank you for recognizing that racism is present even if we personally do not see it. Thank you for sharing our desire to have a more diverse, more equitable, and more balanced technology landscape over time.

You are all awesome.

If you’d like to make a donation as part of the Demystified/33 Sticks campaign for Black Girls CODE:

1. Decide how much you can contribute, knowing that Jason and I are matching you dollar for dollar
2. Go to donorbox.org/support-black-girls-code and make your donation
3. When you get your email confirmation of the donation, which is also your tax donation receipt, forward that to either blm@analyticsdemystified.com or blm@33sticks.com. If you want to redact the email and remove your personal info that is totally fine, we just need to know how much you donated!
4. Track our collective progress online at https://tinyurl.com/demystified-33sticks

I have white privilege.

I was born into it, and throughout my life I have been given opportunities simply because I am white. I don’t want to say I have taken advantage of that, but I honestly don’t know that I haven’t … because I don’t know what it’s like to not be white and live in a system that treats otherwise qualified, talented, hard working individuals differently because of the color of their skin.

I didn’t ask for it, but it’s there, and so watching the scenes unfold across the media in the wake of George Floyd’s killing makes me feel ashamed of the system that has given me so much. And I am frustrated that in a day and age that has seen so many amazing technological advancements, we have not as a society managed to further the causes of equality, humanity, and compassion.

I’d like to start to help fix that.

If you have followed my career — from my founding of the Web Analytics Forum, to my publishing Web Analytics Demystified and The Big Book of Key Performance Indicators, to my co-founding of Web Analytics Wednesdays, or the creation and fostering of the Analysis Exchange — you will see that I have tried to be there for the digital analytics community. My efforts have not always been wholly altruistic, I admit that, but in the end I like to believe that I have had some positive impact on our industry as a whole.

Today I want to ask the analytics community to help me give back.

On behalf of Analytics Demystified, I am donating to Black Girls CODE, a 501(c)(3) non-profit that is working to increase the number of women of color in the digital space by empowering girls of color ages 7 to 17 to become innovators in STEM fields, leaders in their communities, and builders of their own futures through exposure to computer science and technology. I chose Black Girls CODE as a recipient because their efforts speak directly to me as a technologist, a business leader, and as a father.

But I am not alone in my efforts.

Jason Thompson, the CEO and co-founder of 33 Sticks, has generously agreed to match my donation to Black Girls CODE.  While technically Jason and I compete, I reached out to him because I respect his work ethic and his continual efforts to remind us all that it’s not what we do but how we do it that matters. He is one of the “good guys” in digital measurement, and I knew before I even asked him that he would help if he could.

And Jason and I … would like your help.

We are asking each of you reading this who work in the analytics industry and who have comparatively good lives to join us in donating to Black Girls CODE. And to encourage your donations, Jason and I will match up to a total of $20,000 USD in donations over the next 14 days.

Our goal is to work with you, the global digital measurement community, to raise $40,000 USD for Black Girls CODE to help them bring more diverse voices into technology. By expanding the range of experiences shaping our industry, Jason and I have little doubt that digital analytics, and by extension, the technology community, will be better for it.

To help us, and to take advantage of our matching efforts is super simple:

1. Decide how much you can contribute, knowing that Jason and I are matching you dollar for dollar
2. Go to donorbox.org/support-black-girls-code and make your donation
3. When you get your email confirmation of the donation, which is also your tax donation receipt, forward that to either blm@analyticsdemystified.com or blm@33sticks.com. If you want to redact the email and remove your personal info that is totally fine, we just need to know how much you donated!
4. Track our collective progress online at https://tinyurl.com/demystified-33sticks

No donation is too small!  If you can give $5 it’s like giving $10! If you can give $50 it’s like giving $100!! Jason and I are confident that if we are able to rally the digital analytics community to raise $40,000 for Black Girls CODE, that together we can have a positive and meaningful impact on their efforts to make our little corner of the world a more diverse, a more inclusive, and an overall better place.

I welcome any questions you might have about this effort, and on behalf of everyone at Analytics Demystified I sincerely hope that all is well for you and yours during these uncertain times.

P.S. Please feel free to share this post with anyone and everyone you think may want to contribute. 

I am extremely excited to be joining the talented team of Analytics Demystified partners.  I am truly humbled to be working alongside some of the brightest industry veterans Digital Analytics has to offer, and I am looking forward to adding my expertise to the already broad offering of services that we provide. My focus will be on the technical and implementation related projects, however I will also assist with any analysis needs that my clients have, as well.

While joining the partner team is a new role for me, I have been working with Analytics Demystified for the past three years as a contractor through Team Demystified.  Prior to this, I was Principal Consultant and Director of Global Consulting Services at Localytics, a mobile analytics company.  My 10+ years of experience in Digital Analytics, as a consultant, vendor and practitioner, puts me in a great position to help our clients reach their maximum potential with their analytics investments.

On a personal note, I currently live in the Portland, Oregon area with my girlfriend and energetic Golden Retriever pup.  I’m a native Oregonian and therefore love the outdoors (anything from hiking to camping to snowboarding and fishing).  I’m also a big craft beer enthusiast (as is anyone from the Portland area) and can be found crafting my own concoctions during the weekends.

I can be reached via email at tim.patten(AT)analyticsdemystified.com, via Measure Slack, or Twitter (@timpatten).  

This post was inspired by a recent conversation on Measure Slack, where Andrew Richardson posed the question:

One discussed shift is the desire businesses have to understand a customer along their entire journey (online/offline/marketing touch points/across devices/etc,) These discussions led to my comment, regarding the cross-device challenge:

In this post, I hope to expand on these thoughts.

Now, on with the post…

Regardless of the business model, organisations commonly express a desire to be able to track the “holistic customer journey”, tackle the “cross device challenge” or “get a 360 degree customer view.” (Congrats! You just won Buzzword Bingo!) This is a complex challenge and even starting “simple” (for example, by trying to first tie behavior across devices) encounters hurdles.

It is common to treat cross-device identification as if it were a technology problem: we just don’t have the easy, magical, perfect tools to do this with ease. However, I would argue that the most common barrier is a user behavior problem. (Or, most accurately, a user benefit problem.)

To be able to successfully tie user behavior across devices, the user needs to self-identify (typically via login.) Technology can get around this but attempts to do so are reliant upon a lot of assumptions, a less-than-explicit opt-in, or downright “creepy” methods (“zombie cookies”, anyone?)

The businesses that successfully track multi-device behavior either:

1. Have a business model that requires login to use core functionality (for example, Facebook, Netflix or Bank of America), or

2. Provide such benefit to logging in that it’s a no-brainer for the user (for example, Amazon, Zappos or Twitter.)

(Spoiler alert: Not every business is Amazon or Netflix.)

A click-bait content site, on the other hand, is unlikely to be successful tying together multi-device behavior, as there’s no real benefit to logging in. Users see a page view or two, but then they leave, with no real loyalty to the site.

Instead of focusing on the technology and how to implement cross-device tracking without opt-in, I would recommend business stakeholders ask themselves two questions:

1. What are we offering that would make it attractive for a user to identify him/herself?
2. How can we make it easy for users to do so?

Starting from a position of “What can we offer our customer?” instead of “What stealthy technology can we use?” sets your business up for a relationship of trust with the consumer – a critical component to a long-term relationship.  

Some business models will be able to provide a solid benefit in exchange for self-identification. Those businesses will be best served by expanding on those benefits, and making the ease-of-use the best they can.

Other businesses may struggle, because, despite their best efforts to manufacture one, the benefit simply isn’t there. So, what if you are one of those businesses that struggles to offer enough incentive for self-identification? What should you do?

Unless you have a well defined strategy for exactly how you will act on your cross-device user view, and how that strategy will drive actual revenue, I would recommend focusing your analytics efforts on a project with more tangible returns, and revisiting cross-device at a later date. It is tempting to chase the holy grail of the “360 view”, but its value doesn’t lie in the “interesting insights” or in getting a true de-duped user count. It lies in the actions you’ll take, based on knowing I’m the same user, moving from screen to screen. Like all projects, it should be undertaken to drive the business, so start from how you’ll act on this data.

What are your thoughts? Share in the comments! 

Not on Measure Slack? Come join us! join.measure.chat 

[Originally published at Inc.com]

It doesn’t matter if you are a small startup, or a large organization, these six tips will help you succeed with digital analytics, whether it be for your website, mobile app, marketing or social media data.

1. Nail the basics, before you try to get fancy

At Analytics Demystified, many organizations come to us with lofty near-term goals. For example, wanting to implement comprehensive, cross-device tracking of their customers, that they can link to their personalized marketing data and point of sale system…. But they can’t even get basic digital analytics tracking correctly implemented on their website.

For example, a large travel company we worked with had aspirations of doing deep segmentation and customized content… but couldn’t get simple Order and Revenue tracking correct. Or, a global B2B company who wanted an integrated data warehouse, from anonymous website visit through to lead through to customer… but couldn’t even get accurate counts of the number of lead forms submitted on their site.

The corporate advantage from analytics absolutely comes from being able to get an integrated view of your customer. However, you have to nail the basics before you try to get fancy. The fundamentals are fundamental for a reason. If you don’t have a solid foundation, with accurate data collected across all your systems, your integrated data will be flawed, leading to poor decision making. Accept that your organization will take time to crawl, walk, then run.

2. Perfect is the enemy of progress

While you build your solid foundation and move towards more advanced analytics, don’t get discouraged because you can only do some of the things you want. There are still plenty of gains to be made from careful analysis of your web analytics data, or your email or social or mobile app data, before they are fully integrated with your other systems and CRM.

Just because you’re not at your dreamed end-state doesn’t mean you can’t gain valuable insight along the way.

3. There is no “right” and “wrong” way. There’s only “appropriate for your business.”

Recently I attended a webinar, where the speaker was asked “What is the best report in Google Analytics?” He proceeded to name a specific report and why he felt it was so valuable.

My first thought? “Wrong! The best report is the one that answers the business question.” There is no “right” answer, no “one” report. Solid analytics comes from using data to answer a business question. So what reports you should be using, what data you should be collecting and what analysis you should be doing depends on your business requirements. There is no “one size fits all” approach, and “best practices” may not be best for your business at all.

4. People. Not Technology.

Spending on people matters far more than buying shiny new tools. (But every vendor selling you on “shiny” will argue otherwise!) You can do far more with a smart team, and free or inexpensive tools, than with all the bells and whistles, but no team to use them properly.

Unfortunately, we commonly work with large enterprise organizations with little or even no analytics resources. (For example, a large, Fortune 100 company with twenty individual brands and no internal resources devoted to analytics!) Your chance of gaining anything valuable from analytics … without analysts? Slim to none.

Why is this so common? Unfortunately, in most organizations, it is easier to get budget for technology than additional headcount. It’s easier to get budget for agencies and consultants, than headcount! As consultants, we at Analytics Demystified certainly benefit from this. But ultimately, we see the greatest success from our clients when they invest in their internal resources, and we therefore arm clients with justification to build out their internal team.)

When does it become about the technology…? When your awesome team are breaking the limits of what can be done with inexpensive solutions.

5. The grass is not greener

Is your analytics not helping you? Is your data a mess, the subject of deep distrust, and your implementation a disaster?

“I know! The problem is Adobe Analytics / Google Analytics / [Insert Vendor Name here]! If we change to [Some Other Vendor] things will be perfect.”

At Analytics Demystified, we have seen countless clients with a poor analytics implementations of Adobe Analytics, who jump ship to Google Analytics (or vice versa) under the assumption that the problem is the vendor. (Normally, we see those clients again a few years later when they repeat the process and switch again…)

It’s easy to think that the grass is greener, and that a vendor switch will cure all your ills. However, what actually solves problems in a vendor switch is not the new vendor per se, but rather, the time you spend redesigning, tidying and correcting your implementation while you are in the process of implementing the new vendor.

A vendor switch is not a good fix, because in a year or two, your shiny panacea will be in as much disarray as its predecessor. After all, you still have the same technical resources, the same back-end systems, and the same processes (or lack thereof!) that led to the mess in the first place. You just will have wasted a lot of time and money… and will probably switch tools again and repeat the cycle.

Rather than starting from scratch with a new solution, go back to the foundation with what you have. Revisit and reimplement your current tools, and see if you can make them work before trading them out. And this time, address the systemic issues that brought you to this place, rather than being swayed by fancy demos.

6. “You can’t manage what you don’t measure.” But, don’t bother measuring if you’re not willing to manage it!

“I want to track every single link and button our site! This is critical. How else will we know what people did?”

Before requesting in-depth tracking of the minutiae of your website or your app, stop and ask yourself: “What action will I take based on this data?” And even more importantly: “How will that action affect the bottom line?”

A “let’s just track everything” approach can be indicative of a lazier approach to analytics, where stakeholders aren’t willing to separate what’s important from what’s nice to know. And while it can seem easier to track everything (“just in case we need it”) there is a high opportunity cost to doing so: your analysts are likely to spend more providing tracking instructions, QAing and monitoring data, and less of the valuable work: analysis!

That’s not to say more in-depth data can’t be valuable. A client of mine has multiple links to their trial signup flow. One in the global navigation, one in the body of the site, and one at the bottom of the page. They wanted to be able to differentiate trials coming from each button. Was this tracking worth implementing? Absolutely! Why? Because they actually use this data to optimize the placement of each button, the color and call to action, the number of buttons on the page (and more) via A/B and Multivariate testing.

If you want to track clicks to every button on your site, you had better be ready to move, or remove, calls to action based on their performance. You’d better be ready to look at the data frequently and put it to good use. After all, if you aren’t ready or willing to make a change based on what the data tells you, why bother having it at all? Data should enable decision making, not be merely informational.

What do you think?

What has been critical for your organization to draw value from your digital analytics? Leave your thoughts in the comments!

What Happens When You Combine Analytics and Pregnancy?

Those of who know me might have noticed I have been suspiciously quiet. (Let’s be honest, that’s not the norm for me!) I wanted to explain a little about where I’ve been, and how I manage to make everything in my life about analytics.

If it wasn’t obvious from some of my previous posts and presentations, I have an interest in “quantified self” – essentially, tracking and applying analytics to every day life. So, when my partner and I were expecting a baby, of course I had to turn this in to an opportunity to analyze what happens to physical activity levels during pregnancy.

As background: I’m a pretty active person. I teach Les Mills group fitness classes (4-5 classes/week) and work out 6-7 days a week. Because I was so active before pregnancy, I was able to keep doing everything I had been doing, all the way up until the day I went in to labor. However, even with a focus on continued activity, I found there was still a “slow down” that happens in pregnancy.

I tracked my steps and “active time” (which includes any exercise, even if it’s not “steps based” – for example, this would include activities like swimming or yoga, that aren’t easily measured by “steps”) throughout pregnancy, as well as during the postpartum period. This gave me data I could use to examine the changes to activity levels at different stages of pregnancy, and after birth.

What I found

Here is what I found…

1. Pregnancy definitely decreased my average daily step count, with the heaviest “hit” to my steps occurring in the third trimester.
   • I went from 13,700 steps per day to 8,600 during pregnancy (a -37% drop.)
   • The first trimester wasn’t a huge change. I was still taking 11,000 steps a day! (A -19% drop.) However, I was pretty lucky. I had an easy first trimester with no nausea. A lot of women are actually very inactive during the first trimester due to exhaustion and morning sickness.
   • The second trimester I dropped to 9,000 steps per day. (Given the recommendation is 10,000 steps per day, 9,000 seemed pretty respectable for pregnancy, if you ask me!)
   • The third trimester was my lowest, with 6,100 steps/day. If you look at the charts, you may notice a large drop around Week 35-37. That actually coincides with my partner heading out of town, to Adobe Summit. I was intentionally laying low to avoid going in to labor while he was gone! (I considered excluding this data as outlier, but decided to keep it in since it is accurate data.)
2. However, the biggest drop was actually in the “post-partum” period immediately after birth, where I only took an average 6,000 steps/day (a -56% drop compared to before pregnancy.) For those who don’t know, you’re not supposed to do much of anything in the six weeks after birth. (It’s really boring.)
   • The first five weeks after birth drove most of this, with only 3,400 steps/day.
   • After six weeks I was able to return to teaching and a lot more activity, and am averaging back up at 8,600 (and continuing to trend up!)
3. Pregnancy also decreased my “active time”, but not as significantly as my steps. Essentially, I was still staying active, but sometimes non-ambulatory activities like swimming, yoga, weight training etc were taking priority over activities like running (which I gave up towards the end of the second trimester.)
   • While my steps decreased -37% in pregnancy, my active time only decreased -26%. So, I was keeping active, just in other ways.
   • During the first trimester I was still managing an average of 2 hours of active time per day!
   • This dropped to 1.7 hours in the second trimester, and 1.5 hours in the third.
   • Similar to steps, the biggest drop was in the post-partum period, where I averaged only 1.2 hours of active time per day (a -48% drop.) The lowest of this was during Weeks 1-5 (only 0.7 hours/day), with 6 weeks post-partum seeing an increase in activity again – up to 1.8 hours/day and climbing!

In case you’re into charts:

How I tracked this

For years now I have used Jawbone UP products to record my step, activity and sleep data. I have IFTTT connected, which automatically sends my UP data to a Google Spreadsheet. That’s the data I used for this analysis.

Why no sleep analysis, you might wonder? Two reasons:

1. The way Jawbone exports the sleep data is really unfriendly for analysis and would require so much data cleanup, I simply don’t have the time. (You’ve probably heard: babies can be time consuming!)
2. Let’s be honest: Seeing how little sleep I’m getting, or how fragmented it is, would be a totally bummer. My partner is pretty awesome about sharing night duty 50/50, so I choose to not look to closely at my sleep, since I know it’s actually pretty darn good for a new parent!

What’s next?

Yes, there is actually such a thing as a Quantified Baby. My partner and I use the Baby Tracker app to record our son’s sleep, feeds, medication etc, which gives us amazing little charts we can use to detect patterns and respond accordingly. For example, choosing an appropriate bed time based on the data of his sleep cycles. There’s probably not a post coming out of that, but yes, the tracking does continue on!

Thanks for tuning in!

I undertook this analysis mainly because I found it interesting (and I’m a nerd, and it’s what I do.) Pregnancy was such a unique experience, I wanted some way to quantify and understand the changes that take place. Most people probably won’t be too interested, but if you have any questions or want to discuss, please don’t hesitate to leave me a note in the comments!

Last week my inbox blew up all the sudden with email from LinkedIn with subjects like “congrats” and “well done, old man!” At first I assumed this was just more of the same SPAM I seem to get from that platform … but upon further inspection I realized that LinkedIn had told folks that it has been nine years since I quit my cushy job at Visual Sciences, threw caution to the wind, and founded (Web) Analytics Demystified!

Nine years!

It is positively mystifying to me how much the Demystifiers and I have accomplished in this relatively short amount of time. Seven Senior Partners with seven books between us, hundreds of marquee clients, thousands of blog posts helping to shape the industry, and millions of miles flown in an effort to help amazing individuals and organizations make the most from their investment in digital analytics and optimization. We have watched giants fall, competitors fold, and thought leaders simply stop thinking … while simply doing what we do best: demystifying analytics.

It’s not to say we haven’t transformed our business, far from it.

If you look back at my writing from nine years ago you can see that we have gone from being almost exclusively strategic to being a full-service shop. Engagements that start strategically with Adam and John quickly expand into tactics with Brian, Kevin, and Josh and ultimately insights with Tim and Michele. Clients are now able to leverage the experience of the Senior Partners on an ongoing basis, allowing the best in the industry to make their own people better.

What’s more, with the addition of Team Demystified we are more deeply embedded than ever and fully invested in our client’s success and able to deliver implementation support and insights on a truly full-time basis. This decision, in retrospect, may turn out to be one of the best I have ever made given that it has allowed Demystified to grow in a scalable and sustainable way, creating amazing opportunities for some of the best young talent in the analytics field. If you’re interested in learning more about joining Team Demystified or adding Team members to your analytics staff please email me directly.

Another change some of you may have noticed is that I personally don’t do any consulting anymore.

Two years ago I made the decision to take more of a behind-the-scenes management role, growing Team Demystified and making sure that the Senior Partners were given the support they needed to deliver client value commensurate with our reputation. At that point I established a single key performance indicator for the entire business and set everyone working towards it: client satisfaction.

No great surprise but this turns out to be the one KPI that matters in a consulting business.

Everything we have today is a direct result of going as far as necessary for each client … and then one step further. It has led to a lot of early mornings, late nights, and worked weekends, but at the end of the day we know that our business is only as good as our reputation. What’s more, since it is common knowledge that we are often the most expensive option in analytics consulting — increasingly by a factor of two to three as other shops seem to be in a race towards the bottom — the onus stays on us to do the job right the first time, every time, for every client.

That’s not to say we have kept every client we have ever taken on.

One of the big “ah ha” moments for me in the past two years has been that our KPI is also a function of the client being willing and able to be satisfied. We have had to essentially fire almost a half-dozen clients — and trust me, as a business owner this is painful — when we found them unwilling or unable to actually follow the advice we gave. That said we now have much better qualification filters for new clients in an effort to make sure that before we let them hire us for our transformation expertise … that they actually want (and are able) to be transformed.

Sigh. I guess web analytics is still hard …

Having started in the late ’90s at Webtrends I have personally watched this industry grow from almost nothing to the point where the best digital leaders wouldn’t even consider making a decision without analytics data to back them up. Together the Demystified Partners and I have watched the vendor landscape mature to the logical two-horse race we see today, and that has allowed us to focus our efforts to provide the best possible service. And at the end of the day I am grateful for the experience, my amazing Partners, our incredible Team members, and of course, our clients.

The title of this post is really two questions:

• Is on-demand radio the next big channel?
• Is using “on-demand radio” instead of “podcast” in the title really just a sleezy linkbait move?

I’ll answer the second question first: “Maybe.”

Now, moving on to the first question. This post is in two parts: the first part is digital marketing prognostication, which isn’t tied directly to analytics. The second part is what the first part could mean for analysts.

The Second Life of Podcasts

No, I’m not referring to SecondLife (which, BTW, is still around and, apparently, still has life in it). I’m referring to the fact that podcasts just turned ten, and there are a lot of signs that they might be one of the “next big things” in digital. Earlier this year, when I wrote a post announcing the launch of the Digital Analytics Power Hour podcast, I listed three examples as to how  it seemed like podcasts were making a comeback:

• Slate published an article on how, while podcasting is a wildly imperfect technology, its 10-year birthday was a good point to reflect on the promise of the medium
• Serial took the world by storm, which prompted Fortune to muse on the growth of the format
• Alex Blumberg started a for-profit company — Gimlet Media — whose sole product will be podcasts (with the excellent Startup and Reply All podcasts both up and running), and he quickly hit his initial funding goal

The fact that I felt like podcasts were experiencing a resurgence should have been a death knell for the medium — predicting the future of technology has never been my forte (I distinctly remember proclaiming with certainty that SaaS-based CRM would never work when Salesforce.com launched! I said the same thing about SaaS-based web analytics!).

But, this past week brought another bullet for my list: The Slate Group launched Panoply, a podcast network where they’re partnering with Big Names In Media (think Huffington Post, The New York Times Magazine, HBO, Popular Science…) to produce high quality podcasts. Slate feels like they bring their experience (producers) and the technology (studio setups, audio mixing chops)to produce high quality podcasts. Many of the organizations who are joining the platform have a strong background in journalism, print, and digital publishing, but don’t necessarily have podcasting expertise. This seems like big news.

Here’s my list of why it makes sense to me that professionally-produced podcasts are poised for dramatic growth:

• On-demand TV has definitely gone mainstream with Hulu, Netflix, and Amazon Instant Video — while it’s odd to think that “radio” would lag behind “television” when it comes to innovation, TV seemed to be what had more advertiser focus (I don’t have a source to back that up), and the fact that it was video reasonably made it more attractive to startups/innovators; but, now that consumers are watching their television shows when and where (not just on a TV!) they want, it seems like they’re primed to forego the commercial-laden, live stream of traditional radio
• According to Andy Bowers (the long-time executive producer of all of Slate’s podcasts, and the main guy overseeing Panoply), the cost-per-user to reach a podcast listener with an ad is higher than even a Super Bowl ad; admittedly, it’s still a much smaller audience, but advertisers are starting to go in for podcasts, so media producers are picking up on that and looking to fill the space with advertising-worthy content
  
• Why are advertisers keen on the space? For now, at least, it’s a fairly captive audience. I’ll be the first to admit that I hit the “jump 15/30 seconds ahead” button when I hit the ads on many of the podcasts I listen to (although I also happily have paid to be a Slate+ member to avoid the ads on their podcasts), it’s still hard to miss the repetition of messages there. I wound up as a Carbonite subscriber for several years, and I became aware of them solely through podcast advertising. MailChimp is a perpetual advertiser, and these days, Cone, the “thinking music player,” seems to be betting on the medium.
• Not only are podcast listeners a reasonably captive audience, they can generally be reached on a consistent basis (like appointment TV viewing of days past), and, I suspect, are starting to fall into a pretty dreamy demographic for a lot of advertisers
• What’s in it for consumers? We’re getting more and more accustomed to a constant bombardment by media that has been algorithm-tailored or explicitly controlled by us to deliver information we want to see or read. Yet, when we get into the car or step out to mow the lawn (or shovel the driveway!), our vision is off-limits as a sense. The radio is the easiest stimulus to access that is an auditory-only experience…and that experience can often be pretty lousy. Podcasts give the consumer a much more self-tailored experience.

I get it. Being a podcast junkie myself, I have some inherent bias. But, the launch of Gimlet Media and Panoply has me thinking that it’s not just me.

So, What This Could Mean for Analysts

This, unfortunately, is going to be brief…and not particularly optimistic. The kicker with podcasts is that they are, fundamentally, powered with pretty crude technology:

• The podcaster creates an audio file and is responsible for hosting it somewhere (iTunes does not actually host podcasts — they maintain a library of pointers to the podcast audio files that are hosted wherever the podcaster has put them; Soundcloud actually hosts and delivers podcasts…but I agree with this skeptic about Soundcloud as a good platform for that)
• The podcaster updates an RSS feed — that’s right…RSS — that includes some basic meta data about the episode, including a link to the audio file
• Podcast hosting services get that updated feed and pass it through to the podcast platforms that their users use (the iTunes podcast app, Stitcher, TuneIn, etc.)
• The user’s local device gets that updated feed and downloads the audio file
• The user may or may not ever listen to the file, but it’s just an audio file — there is no universal mechanism to provide any data back to the podcaster about the number of times the podcast was actually listened to, much less how much of the podcast was listened to
• There is no universal concept of a “subscriber.” That’s something that is actually managed by the podcasting application. As such, any count of “subscribers” is, inherently, just an estimate

This explanation is just a way of saying, “This is why most podcasting advertisers harken back to direct mail by providing an ‘enter the offer code XYZ when you go to the site to get a special discount’ call-to-action.” There simply is not good data available as to the actual reach of any given podcast at any point in time.

I’m sure this is part of the reason that, occasionally, someone proposes that a fundamentally new technology should be introduced for podcasts. So far, though, that hasn’t happened. Yet, publishers are charging ahead with new content, anyway.

As analysts, we’re going to stuck with, essentially, three imperfect measurement tools:

• Download-counting — this isn’t bad, but it’s analogous to counting “hits” on the web (or, really, page views — it’s not quite as bad as the days of “hits” of any and all assets on a web page); it gives us a general sense of scale of the reach of the content, and it can provide some basic level of “who” based on the details included in the header of the request for the content.
• Offer redemptions — as I noted above, if the advertiser has a good CTA they can use where the listener will be incentivized to implicitly tell the advertiser “what prompted me to buy,” then there is a pretty strong link from a podcast listen to a purchase; unfortunately, the number of organizations where there would make any sense, while large, is by no means universal.
• Asking — several podcasts I listen to periodically embed a CTA in an occasional episode to go fill out a survey. I’m a fan of the voice of the customer, so I’m totally cool with that. But it requires reaching a sufficient volume of listeners to where a meaningful set of data can be collected that way. And, of course, there is a major self-selection bias risk — the listeners who are most likely to take the time to go to a link and fill out a survey are their most loyal listeners, rather than a representative sample of all of their listeners.

I predict this will be an interesting space to watch over the next few years. As a rabid podcast listener, I’m excited about the possibilities for the medium. As an analyst, I’m afraid I’ll be feeling deja vu when marketers first get serious about wanting to measure the impact of their investments in the medium.

What do you think?

Photo Credit: Patrick Breitenbach (Flickr)

Next month’s ACCELERATE conference in Atlanta on September 18th will be the fifth — FIFTH!!! — one. I wish I could say I’d attended every one, but, sadly, I missed Boston due to a recent job change at the time. I was there in San Francisco in 2010, I made a day trip to Chicago in 2011, and I personally scheduled fantastic weather for Columbus in 2013.

This will be my second ACCELERATE as a partner at Analytics Demystified, and I’m really looking forward to it, so I thought I’d take a run at 5 tips for making the conference as fruitful and memorable as possible — the most non-subtle of homages to the “10 Tips in 20 Minutes” format of the event.

Tip 1: Register!

Obviously, you can’t really help make the event fantastic if you’re not there. It’s $99, for Pete’s sake! Did you know that the first ACCELERATE was actually free? What Eric, John, and Adam learned with that was that “free” meant people would register without even checking their calendars for availability. So, they went the “nominal fee” route to ensure registrants had the teensiest bit of skin in the game. You can actually read more about the philosophy behind the event pricing here — it goes to what makes the conference different from other analytics conferences! For fun, I’ve actually finagled a nominal discount on that nominal fee. Use the promo code “gilligan” when you register and you’ll get a little discount. It was going to be an amount that matches the last two digits of the year I graduated from high school…but then we got crazy and decided to make it match the year I finished second grade.

Tip 2: Set a Conversion Rate Target

We’ve got 10 speakers each providing 10 tips. You can check out the speakers and topics here (scroll down after clicking through the link). That’s 100 tips! We’re not brazen enough to claim that every one of those tips is going to knock your socks off. The fact that you’re getting out there and reading blog posts and attending industry events means you’re already in the mode of learning from your peers. That’s great! Take a look at the topics that we’ll be covering. How many tips are you aiming to pick up that you can take back and apply immediately when you get back to the office? Set a target. Leave a comment here with what it is. Tweet it with the #ACCELERATE hashtag. Then, let me know how you did!

Tip 3: Identify Your Biggest Analytics Challenge

Between the speakers, the Demystified team, and the several hundred of your peers who will be attending, you have a great resource to tap into during the breaks at the conference. Whether you seek out a specific person who you know will be there, or whether you will just be mingling with a random mix of people, tee up in your head the thing you’re struggling with the most. Toss it out for discussion and see if you can track down a bonus tip or two that is specific to your circumstance. You’re allowed to count any tips you pick up that way as conversions, too!

Tip 4: Be Social

Dust off your Twitter account and get ready to help us capture the essence of the event and the most popular takeaways. We’ll be tracking the tweets that use the #ACCELERATE, and so will many of the attendees. Tweet the tips that you find the most useful (this is also an easy way for you to tally up your conversion rate after the event — just review your own feed). Tweet your additions/enhancements to the tips. Tweet when you disagree with a tip or a tweet, or when you have an amusing, related anecdote. It’s not about volume, and it’s not a competition. Well…maybe it is a little about competition. There is definitely a bit of cachet that goes with being the author of one of the most retweeted tweets of the event. Either Michele Kiss or I will certainly tweet out the most RT’d tweets of the day at the end of the event.

Tip 5: Be Sociable

This is the countervailing tip to Tip 4. This is a one-day conference. Set your out-of-office message that you are out for the day. One. DAY! Email can wait for the flight back. Set a goal to know not only the names of everyone at your table, but where they work, what they do, and what their biggest challenges are (see Tip 3). Introduce yourself to the person in front of or behind you in line at lunch. Sidle up to a small group and join the conversation.

I’m looking forward to what I know is going to be another great event. I hope to see you there!

Update 5/23/2014: This post should now be unnecessary and no longer accurate as of the May 2014 Adobe Analytics release. See this post by Ben Gaines for details on the segmentation feature updates released then.

Update 3/27/2014: Following the Sneaks session at the 2014 Adobe Summit in Salt Lake City, this post is going to have a very short half-life. Segments are getting much more shareable! I’ll get this updated once I’ve got my hands on the update and can speak to it accurately.

In honor of Adobe Summit 2014 coming up next week, I’ve got an Adobe-related tactical post!

Over the past year, I’ve run into situations multiple times where I wanted an Adobe Analytics segment to be available in multiple Adobe Analytics platforms. It turns out…that’s not as easy as it sounds. I actually went multiple rounds with Client Care once trying to get it figured out. And, I’ve found “the answer” on more than one occasion, only to later realize that that answer was a bit misguided.

To be fair, there is actually a tall order for Adobe here: three fairly distinct data reporting/analysis/extraction platforms (Reports & Analytics, Data Warehouse, and Ad Hoc Analysis), and an ideal state where all three can be used for segment creation such that any of the other two can then use that segment! Some analysts are (inexplicably) still clinging to Reports & Analytics (SiteCatalyst) as their primary analysis platform, which is a little silly, given the increased speed and flexibility of Ad Hoc Analysis (Discover). But, I get that the Discover interface has a steeper learning curve, so Reports & Analytics is probably not going anywhere any time soon (although…who knows what will be announced next week? I don’t!).

Anyway, I finally sat down a few weeks ago and created a grid of all the different places a segment could be created, and then where that segment would be available. I ran that past a few people and got some feedback. It’s not going to be a surprise to anyone who is interested in this post that Adam Greco was the biggest contributor of that feedback.

Here are the main highlights (unpleasant ones, unfortunately) from this investigation:

• Segments created in the Reports & Analytics (SiteCatalyst) Admin Console are not available in Ad Hoc Analysis (Discover)
• Segments created in Ad Hoc Analysis (Discover), even if saved in a Shared Folder, are not available in Data Warehouse

A Google spreadsheet with more detail (the grid shown below) is located at http://bit.ly/segmentSharing or by clicking on the image below:

This grid represents a work in progress, but Adobe has done a great job in the last year or two trying to get parity between the different tools and I expect that it will keep getting better. It may yet have some inaccuracies (although one of my Adobe heroes has blessed it since I initially published it), so, if you spot any, please let me know and I’ll do some further testing and validation!

My presentation from the Digital Analytics Association San Francisco Symposium is now available on SlideShare:

What the ‘Quantified Self’ movement and really, really personal data means for marketing, analytics and privacy?

At the intersection of fitness, analytics and social media, a new trend of “self-quantification” is emerging. Devices and applications like Jawbone UP, Fitbit, Runkeeper, Foursquare and more make it possible for individuals to collect tremendous detail about their lives, creating a wealth of incredibly personal data. What does this intersection of “”big data”” and very small, very personal data teach us about the practice of analytics? And what cautions must marketers heed with respect to targeting and privacy in trying to seize upon this trend?

View on Slideshare.

I’m closing in on six full years since I moved from Austin to Columbus. Because I’m a native Texan, I’ll never truly “go native” in Columbus (there’s a Natural Law of Hillbilliness that dictates that), but, with ACCELERATE 2013 rapidly approaching, it seemed like a good time to rattle off why the town is a great place to be for digital analytics.

The town itself, like me, has long-struggled with a bit of an inferiority complex:

• On more than one occasion, a long-time local has pointed out to me that, when talking to people from other large cities, the city name itself suffices: LA, Houston, San Francisco, New York, Chicago, Cleveland, Cincinnati. But, Columbus residents always feel like they have to provide a little more detail: “Columbus, Ohio” (it’s true!).
• A first-time visitor to the town recently flew in from Austin and assumed he was just flying over an “actual Ohio city” as he descended into Columbus: “It’s a real city! Bigger than I expected!”

So, with my tongue occasionally inserted into my cheek as I type, below are five reasons that Columbus is actually a great town for digital analytics!

#1: Birthplace of Presidents…and Digital Analytics?

Virginia is the “Mother of Presidents,” in that 8 U.S. Presidents were born there. That makes sense — it was a hotbed of colonial activism. 4 of the first 5 presidents, actually, were from Virginia. After that, though things tapered off a bit for the state. Ohio, though, wasn’t even a colony, and, yet, is the birthplace of 7 presidents. Not bad!

On the digital analytics front, did you know that:

• Eric Peterson was born in Ohio, just like those 7 presidents (well, presumably, not “just like,” as some of them were born when medical techniques were more primitive).
• Avinash Kaushik got his MBA at The Ohio State University, so he spent some seriously formative business years in the town
• Jim Sterne put his wife through law school selling lots of software to GE and Wright Patterson AFB in Ohio.

Super-compelling anecdotes like this can’t be sheer coincidences, can they? (Don’t answer that.)

#2: Big Brands with <groan>Big Data</groan>

A number of major brands were founded in Columbus (and stayed), relocated to Columbus as they grew, or have a major presence here. Those companies have a wealth of consumer and digital data…and they rely on sharp analysts to help them put that data to profitable use.

Some logos you might recognize of brands that were founded and continue to be based here (or have been headquartered here long enough that they might as well have been):

That doesn’t include the fact that JPMorgan Chase has a massive presence in Columbus, as does Abbott Labs. And Thirty-One Gifts is now based here and growing like a weed. And P&G is just down the road…

You get the idea.

#3: Same Right Size as Austin… but Definitely Cooler

Austin and Columbus are just about the same size. They’re both easily in the top 20 cities in the U.S. by population. Everyone thinks of Austin as being a cool town — hipsters abound, keepin’ it weird, and so on. And it is a cool town. It just turns out that Columbus is cooler:

At the same time, the frigidness of Columbus in the winter tends to be exaggerated. Notice in the chart above that the temperature didn’t drop below freezing and just stay there for a long period of time. Columbus is in central Ohio, which means it’s far enough from Lake Erie that the “lake effect” that dumps snow early and often on cities like Cleveland and Detroit actually tapers out before getting down to Columbus.

Climate-wise, it’s actually pretty mild.

And, no, this doesn’t really directly have anything to do with digital analytics…but it did include a chart with real data (courtesy of NOAA)!

#4: When Big Blue Does <groan…again>Big Data</groan…again> They Do It In Columbus

IBM. Ever heard of ’em? Well, let me tell you a little story: when they decided to open a client center devoted to advanced analytics, they looked high, then they looked low, then someone said, “Why don’t you look in Ohio?” In the end, they landed in Columbus. The combination of talent, brands, and local government support made it a no-brainer (whether or not it being cooler than Austin may or may not have factored in).

#5: Our Analysts Like to Hang Out and Drink Beer

Digital analysts in Columbus get together about once a month to hang out, eat good food, drink good beer (except for Liz Smalls — she drinks Budweiser), and swap tips and ideas at Web Analytics Wednesday. We’ve had over 50 WAWs in Columbus in the last 5 years, and those will keep on keeping on!

So, what are you waiting for?

Seriously. What are you waiting for? Sign up now for ACCELERATE 2013 so you can check out a bit of this analytically awesome spot!

Ask a career coach how to land your dream job and they’ll tell you: 1) figure out what your dream job is, and 2) develop a plan to get there.* I never consciously did either one, but I realized several years ago that I have the most fun when I’m helping companies figure out how to “do” digital analytics effectively.  I even caught myself with a pretty tight description of what that looked like in my ideal form: it looked like what Eric, John, and Adam (just the three of them at the time) were doing over at Analytics Demystified. The fact that I got to know them personally, both at conferences and through social media, as well as the rest of the stellar crew of talent they’ve added since then, did nothing but reinforce my beliefs.

And now…I’ll be joining that team in a couple of weeks! As someone that Eric Peterson once referred to as “The Grandmaster of Grump,” I’ve been dealing with an unfamiliar emotion: giddiness. I’m looking forward to joining a fantastic and talented team, including having them all in my adopted home town of Columbus in a few months for ACCELERATE!

* I’ve never actually had a career coach. I tried to read What Color Is Your Parachute?  years ago and didn’t make it past the second chapter.

This week I was one of 3,500 people from 26 countries to attend IBM’s Global Smarter Commerce Summit in Nashville Tennessee. While I also enjoy attending more specialised, analytics-focused conferences, I find events like Smarter Commerce a fantastic opportunity to take a step back and look at the big picture.

After all, IBM is in the process of building out an enormous picture. In the marketing and analytics space alone, acquisitions like Coremetrics, Unica, SPSS, Tealeaf, DemandTech and Netezza are being brought together for integrated marketing and business success, not to mention integration with the entire spectrum of IBM products.

The interesting thing to me is always the themes that emerge from events like these. For those who did not have an opportunity to attend, let me recap a few.

Big Data … use

I know what you’re thinking – “big data, haven’t heard of that before…</sarcasm>” But what I found interesting about the discussion of big data at Smarter Commerce was that the discussion has evolved. No ifs, ands or buts about it – big data isn’t just coming, it’s already here and already being used. It’s no longer being touted as “the next big thing” or useful in and of itself. Rather, the conversation is moving to the application of insights from this data. Data is the way in which we can get to know our customers, and to delight customers we must first know them. (-Best Buy) (And for some enjoyable irony: consider the fact that we are using massive volumes of data to treat people as more than a number. (-Jay Baer))

Companies are not the only ones to be leveraging larger data sets. The power has moved from the boardroom to the living room (-Porter Gale) and this new era of the informed customer has consumers looking at more data than ever. In 2010, consumers used an average of 5.3 sources of information to make a decision. One short year later, that was already at 10.4. Why? Because the more information that is available, the more information is considered necessary for consumers to feel they have conducted a thorough review. (-Jay Baer)

Marketing as a Service

What data and technology allow us to do is to provide “Youtility”: Marketing so helpful that people would pay for it. (-Jay Baer) After all, we all know what bad marketing looks like. But good marketing is seamless – you don’t even know it’s happening. (-John Lovett.) What enables that is integrated efforts across channels, with the right message to the right person at the right time in the right way. It comes at the intersection of data and action across channels.

Omnichannel

Not only are there a plethora of channels within digital, there is the physical side of the world to consider. (Look out your window – it’s still there!) It’s not enough for companies to think of physical or digital – it’s about digital and physical. (-Jay Baer) For the consumer, the physical and digital experiences are not separate, and companies need to exploit the convergence of these. (-Paul Papas)

The reality is, the world is forever changed by the rapid adoption of digital technology. Digital has created a new consumer and a new mindset. However, this is an opportunity! In retail, digital is often viewed as the enemy, or the downfall of the physical. (Think of concerns such as showrooming and the impact on mobile on price competition.) However, while mobile is often rumoured to be the “death” of physical stores, mobile is in fact an asset – it is a bridge between the physical and digital worlds. (-Philip McKoy, Target)

Opportunity in Chaos

Companies have two choices in our new hyper-connected world: They can be fearful of change, or embrace it and re-invent their approach. Companies that take smart risks in the new world will thrive. (-Philip McKoy, Target)

And much as this is a new world, this isn’t truly new, nor the first time this has happened! Massive brands like IBM, Disney, CNN, Apple, Fed Ex and more were formed by seizing opportunities during difficult economic times. (-Jeremy Gutsche) Industries have been re-invented over and over again throughout history.

In the end, it is about seizing upon the opportunities our changing world provides, and focusing on the customer. As Sir Terry Leahy, former CEO of Tesco, said, “When I learned to follow the customer, I stopped having to look for growth.”

Brave New World

Events like Smarter Commerce are great previews of the future of marketing and technology. Craig Hayman spoke of the evolution of computing technology, from tabulating to programmable to cognitive. Cognitive technology like IBM’s Watson is in itself an evolutionary step: cognitive technology learns, so it gains value over time rather than becoming quickly outdated. (-Craig Hayman.) Innovations like Watson, Jaguar/LandRover’s virtual vehicle experience or IBM’s augmented location services are just a hint of the amazing things to come, and I for one am excited.

I am super-excited to join the incredibly talented team of Demystified partners! My background is in development, and in full disclosure I considered beginning my initial post with “Hello analytics world!”, until better judgment prevailed. Needless to day, I’m thrilled to be joining the brightest minds in digital analytics, and looking forward to adding my skillset to the wide range of services we offer our clients.

I was most recently a member of the front-end development team at Salesforce.com, where I managed all technical aspects of their web analytics, optimization, and advertising efforts. Initially with our own Adam Greco, and later with another group of rockstars, we rebuilt our implementations from the ground up in a way that that allowed the entire online marketing organization to have an “apples-to-apples” view of what each individual team was doing. Prior to that, I worked in the Omniture Consulting group with some of the brightest individuals and most successful companies in the industry today.

My focus at Demystified will be in tag management, implementation, and in custom development. I enjoy turning broken implementations into world-class ones, leveraging vendor APIs in unique ways, and enabling clients to maximize the significant investment they make in their online presence. And I couldn’t be more thrilled to work side-by-side with Adam, Kevin, and Brian again – and with Eric, John, and Michelle for the first time.

I’m the second Demystified partner in Utah, where I live with my wife and 3 young kids – a boy and 2 girls. Our youngest was born the week I started at Demystified – which made for a pretty crazy week! I enjoy playing basketball and following almost every sport (none of which I’m very good at), camping, and spending time with family. We enjoy making homemade pizza, which I learned when I spent a few years living in Italy. I enjoy all things Italian – in fact, I chose my Twitter handle (@joshovest) because “Ovest” is “West” in Italian, and all the common variations of my name were taken when I signed up.

Please feel free to reach out to me via email (josh@analyticsdemystified.com) or follow me on Twitter (@joshovest), especially if you have any technical questions about your analytics. I look forward to engaging with all of you in the analytics community very soon.

Google recently launched a new television commercial that advertised their Chrome browser as a solution for your computer, tablet, and mobile device. For marketers and digital analytics pros of all types, this solution has real potential. Not because of the convenience of the solution, but because it potentially solves our problem of identifying visitors to our websites and mobile apps as they traverse from work computer, to mobile to tablet…throughout the day.

First check out the video:

Here’s why this solution has potential for consumers…

Errr…what’s my password again? In an increasingly password-protected web, users will find this unified browsing service valuable. How many times have you scratched your head and asked yourself…”What’s my password?” This unified browser resolves that issue with Chrome’s saved password feature. For those of you not using OS keychains or another solution for recalling your passwords, this is a sure-fire way to minimize the dreaded password reset.

Faster than a speeding search engine. Google’s search (while Bing is giving it a good run) is getting smarter. The Chrome “Omnibox” (you know it…it’s the address bar) will automatically predict what you’re typing (if you let it), which virtually tells you that Google is smarter than you are. Not only does this help get to the right stuff more quickly, but it also recalls where you’ve been previously. But if you’re not into that sort of thing, “Google only records a random two percent of this information received from all users and the information is anonymized within 24 hours. However, if you use Chrome Instant, your data can be kept up to two weeks before it’s deleted.”

Remember my Tabs? No, I’m not talking about the “Totally Artificial Beverage” soft drink (for those of us old enough to remember Tab cola), which was the predecessor to today’s ubiquitous Diet Coke. I’m talking about the tabbed browsing experience. Since most of us bounce between devices as a matter of habit, the ability to bookmark a tab on one device and pick up another to find the same page is becoming increasingly valuable. No more searching for that web page you found right before your boss walked into your cubicle. Simply tap the bookmark star and you’ve got it remembered on all of your Chrome-synched devices.

Here’s why this is a web analysts’ dream…

For us web analytics wonks, having Google Chrome Now Everywhere could help us solve the problem of identifying visitors across devices and sessions when they don’t log in. I cannot count the number of conferences, expert panels, and lobby bar conversations where I’ve heard the question asked: “How can we identify anonymous users across devices?” Well, Google could now potentially solve this problem for a subset of devoted Chrome users…if they choose to make this data available. That’s a big if…

Despite the fact that Google also announced Universal Analytics today, Google would have to make this cross-device data available to us #measure folks. Wouldn’t that be AWESOME? But who knows if they’ll open the kimono on this really valuable data? Perhaps, Google may be holistically trying to help marketers by someday tying products like Chrome and Google Analytics into a common perspective… But perhaps that’s just too progressive for the privacy pundits. I don’t know.

While no digital analytics solution is 100% accurate in its ability to understand user behaviors due to cookie deletion rates, missing data, and anonymous browsing. Chrome’s omni-device presence would certainly help identify with precision those users who opt in to use this solution because of the benefits that it offers. I’ve been saying this for years, but it’s all about the value exchange. And the value derived from having Chrome remember all of your passwords, favorite pages, and preferences is well worth it for many. Don’t be surprised if Safari, Firefox and others start riding GOOG’s coat tails on this one…

What about you? Do you think this will change #measure?

Summary: real-time marketing stat, tag management throwdown challenge, keynote livestream info, short people (tweeter and target), Adobe announcements.

Wait a Minute: Top 5 by WHAT?

Presumably, most people reading this are analysts, so there will be questions about the data itself. I kept it simple:

• Data source: TweetReach by UnionMetrics  (bonus: they just rolled out the beta of their new tracker design!)
• Filter: includes the #AdobeSummit hashtag (so, no Unsummit, and no direct inclusion of the myriad Adobe accounts — although many were, obviously, tweeting with the hashtag)
• Criteria for “Top”: this is simply based on the number of retweets as recorded by TweetReach. I like this as a measure because it captures “tweets that got traction.” Obviously, users who have a gazillion followers (@charleneli, @Adobe) have an advantage here, because there are more first-level opportunities to garner a retweet…but they’ve got a gazillion followers for a reason, so I’m fine with that). In the case of ties, well, I just included 6 instead of 5 and that takes care of that.

Now, on to the tweets!

Real-Time Marketing Stat

Charlene Li will be presenting in one of the general sessions today (and I’ll be on hand to grab people afterwards for some quick thoughts via video interview). In addition to this being a true social media thought leader, the specific stat is pretty interesting. It makes logical sense…but it also requires operational processes to back it up. I’m looking forward to hearing her thoughts in more depth later today!

Tag Management Throwdown Challenge

Click through on the image above (or here) to get to the actual tweet and retweet it yourself, if you’re intrigued.

Evan, I’m sure, has never been described as meek and unopinionated. On any topic. Ever. Lucky for the world of digital analytics, he’s also damn sharp, and he’s a vendor calling for a head-to-head comparison.  Doesn’t every practitioner wish there was more “head-to-head” and “face-to-face” when it comes to vendors (not just tag management — web analytics, voice of the customer, testing, etc.). This won’t happen (logistically, it’s tough to do a meaningful head-to-head…and most vendors don’t really want to see that happen)…but it’s fun to dream!

Later (much later) last night at the Gibson Girl bar, Evan shared that he’s got an “Attribution Management Manifesto.” As yet unpublished…and a topic for another post. But, I’m looking forward to seeing that! 

Keynote Livestream Info

Fun stuff. I’m looking forward to seeing it in person!

Short People (Tweeter and Target)

My fellow Summit Insider — not a WNBA prospect in her own right — captured Kevin Willeitner’s first exposure to Liz Smalls.

(Note: I will almost certainly get in trouble for my description of that tweet from both @MicheleJKiss and — just because — @KristaSeiden).

Adobe Announcements

If I were less of an analyst and more of a UX/experience guy…I might have something clever to say about CQ 5.6. Alas! I am not.

Engagement scoring has been around in the web analytics industry for a long time. The idea behind this kind of score is to give visitors points based on actions they perform that are positive for the business. If a visitor does something important (like viewing certain content) then you give a few points. If a visitor does something very important (like contributing content) you might give them a lot of points. In the end, the goal is to come up with a final number that summarizes just how valuable that visitor has interacted with your site. The most valuable visitors should then be examined and compared with visitors at lower tiers to better understand how the groups differ and how you might encourage visitors to move to a higher score which provides more value to your business.

The rising trend of gamification introduces an interesting twist on engagement scoring. Gamification is the way that you make your site, intranet, or portal more engaging by using elements borrowed from games such as points, achievements, and missions. These intrinsic rewards encourage deep engagement without increasing the cost of the campaign. Previously, engagement scoring was a passive indicator that was often arbitrarily assigned. Now, however, it is a score that visitors to your site see and are interested in improving. As marketers, we can now not only observe engagement but actually be involved with the engagement as it is unfolding.

Introducing the Badgeville to SiteCatalyst Integration

To measure this new type of engagement Analytics Demystified and Badgeville have teamed up to bring you a new integration between Badgeville and SiteCatalyst. This is a Genesis integration that will help you bring your Badgeville gamification data directly into SiteCatalyst. You will then have the ability to see your Badgeville data in the context of your larger SiteCatalyst dataset. Additionally, you can use the powerful features of SiteCatalyst and other Adobe Marketing Cloud tools to analyze the data and even export the augmented data to other systems.

This is the first version of the integration which gives you a solid foundation in understanding the engagement of your visitors or “players” and how they are interacting with your gamified site. The integration currently offers the following reports:

• Badgeville Player ID: The unique ID for each player. The web behavior associated with these IDs can be tied to your Badgeville and CRM information to create a rich and personalized dataset.
• Badgeville Total Points: The lifetime value in points for a player. This report will give you the total sum of points a player has earned in its lifetime which is helpful in understanding the level of experience a visitor has had with your site.
• Badgeville Total Point Groupings: This is similar to Total Points but combines many unique point levels into larger groupings which analysts will find easier to analyze and compare.
• Badgeville Incremental Points: This is the number of marginal points awarded to the player from page to page as they interact with the site and play the game. This is a great indicator of the current level of activity and what is happening now on your site.
• Badgeville Behaviors: As visitors perform actions on your site this will tell you just what it is they are doing (view a video, post a comment, read an article, etc) and how many times they are doing it.

We have created quite a bit of information around these reports which are in the Badgeville Integration Guide (see the Getting Started section below) and how you can use the data. One of the examples that you might find interesting is looking at the Badgeville Total Point Groupings and include other data points that may or may not be part of your game design. Here is an example of how players are combined into general point groupings for analysis. Below we see that the group of 1200-1299 points is amazingly active with the 4th highest number of Video Views. This is apparently a group that has had a history of being very engaged with the site and is still consuming a lot of video content.

All of the other groups at the top of this report are much “younger” groups as far as their total point value. Somehow, though, the 1200-1299 group is behaving very differently and you wouldn’t have even known that was happening before. You can now dig deeper to understand just why that group is so special and if you might be able to adjust your campaign to help improve the performance of the other groups.

On a negative note, we see that the video views per visit for the 400-499 group is lower than what we see in the other groups (red arrow). With this information you might be able to modify your game design by introducing a level or status to help bump that group to a higher Video Views/Visit number.

How to Get Started

If you are a SiteCatalyst and Badgeville customer you can get started with this integration right away. To enable the integration and to access all of the documentation log into SiteCatalyst and navigate to Genesis:

Once you are in Genesis, select Add Integration on the left. Then switch over to the Labs section of Genesis by modifying the dropdown as shown below. Labs is where Genesis places integrations that don’t have any professional services built in. This allows the integration to be completely free if you choose to rely solely on the documentation. If you would like expert assistance, you can contact me (kevin@analyticsdemystified.com).

Once you see the Badgeville icon you can drag the integration over to the Adobe Marketing Cloud on the right to start the configuration process. You will see a popup with instructions that contains links to access the integration documentation. This documentation thoroughly outlines all steps and technical considerations you will want to keep in mind with this integration. Additionally, the document provides many examples to get you started in analyzing the data.

Keep in mind that, as with any Genesis integration, you should thoroughly QA before committing anything to production.

Final Thoughts

I hope that you enjoy this integration and are able to quickly implement it on your site. There is documentation available to help you if you decide to do the integration on your own; however, if you would like assistance putting the integration in place please contact me (kevin@analyticsdemystified.com). I created the integration so you might find me useful in helping you set it up. We have consulting packages available should you need assistance.

There were other attributes and metrics that we considered including in this integration that will be saved for the next version. As you work with the integration please provide feedback to the Badgeville support team. This will then help to mold future enhancements to the integration.

I noted in my last post that I’m an Adobe Summit greenhorn. But, that doesn’t mean that I’m a conference neophyte. Over the past few years, I’ve gone to an increasing number of conferences…and I get a lot out of them! As my fellow Summit Insider, Michele Kiss, put it:

Conferences are definitely like Christmas for nerdy digital analysts – a chance to step outside of your work cocoon, get  a new perspective on your current challenges, meet and mingle and generally talk shop.

We can break that description down into three buckets of “value” from conferences:

• Session content — People who like to gripe about conferences if they don’t get rich, actionable content out of every session they attend. It’s almost a sport to deride the sessions as being high on fluff and short on meat. I think that’s aiming too high for a range of reasons. But, I definitely always pick up a few nuggets or a nuanced perspective from the session content itself (sometimes, I vigorously disagree with the presenter…but that forces me to think about the topic nonetheless, which is valuable)
• Technology and Tools — no analyst uses more than 1% of all of the digital analytics tools on the market. But, conferences are a great way to get a broader perspective of what is out there and not fall into the trap of “when all you have a hammer, everything looks like a nail.” Web analytics, click tracking, voice of the customer, A/B and multivariate testing, attribution management, real-time content targeting, search optimization, display ad optimization, marketing automation,… the list goes on and on. The broader our perspective of the universe of technologies, the more likely we will use the right type of tool for the job when a new analytics challenge presents itself.
• Relationships — conferences are one big community of people who speak the same language and deal with many of the same challenges. It’s energizing to talk with like-minded people, certainly. But, every new relationship I make is a resource I have the potential to reach out to in the future — for help (“Hey…do you know anything about…?”), to help (“I know you’re interesting in X, and I just came across…”), and, honestly, for friendship.
  

I’ve actually been doing some pre-work on that last one thanks to my last post, Twitter, and a few side comments on phone calls and side notes in emails. If you’re working on your own list, check out this Twitter list that and Nick Barron is maintaining (Just @ him with a request to be added if you’re interested).

For me, I now have two distinct lists of people I’m planning to connect with in Salt Lake City:

List 1 — Names

My first list is people who I know will be there for one reason or another, and we’ve agreed we want to hook up:

• Michele Kiss — I still kick myself that I could have met Michele at eMetrics in Washington, D.C. several years ago, but I didn’t actually meet her until the following spring in San Francisco. I’ve since hung out with her numerous times — in person and digitally — and I still haven’t convinced her that the letter “z” is not evil.
• Aaron Maass — I borderline stalked Aaron for years, but I didn’t actually have a conversation with him (and that was a fleeting one), until a WAW in Philly last fall
• Guy Fish — he was a client at one point in time, which meant I met him in person once and then got to know him much better through phone calls and Twitter
• Sergio Maldonado — I had a fantastic conversation with Sergio at an eMetrics that actually led me to write a whole post on Digital Insight Management (which I still think analysts aren’t thinking about and owning enough)
• Matt Coen — the guy who taught me more about Sitecatalyst than I wanted to know than anyone else before or since
• Noe Garcia — the guy on this list I go back the farthest with (well over a decade)…although I didn’t meet him in person until 5 years ago. I am 90% sure that Noe is the first person who told me to accept that web analytics data is not (and never will be) pristine.
• Michael Shear — we’ve been in the guts of Sitecatalyst together…and, yet, have never met in person
• Jessica Vasbinder — one of those people who got some analytics responsibilities dropped in her lap…and embraced the challenge!
• Gregory Ng — a guy I met very briefly in person…but whom, in the years since, I’ve become convinced never sleeps.
• The Columbus Crew (WAW folk — not the MLS team) — Sasha Verbitsky, Liz Smalls, and Robb Winkle
• The Satellite crew — Evan, Michael, Rudi, and whomever else is around
• Adobe people — Ben Gaines (of course!), Jarin Stevens, Paul Kronenberger, and Josh Teare; and, if I can track them down, Carmen Sutter and Laurie Wetzel

List 2 — Which I Can’t Write Out Just Yet

The second list is all the people I know I will meet or reconnect with…but I can’t possibly know who they are, specifically, until I get there! The conference offers a world of opportunities to mix and mingle and meet new people, and I certainly plan to do that every chance I get!

Are you making a list?

This is a question that we have had many clients ask recently. You can imagine, with the heavy usage of JavaScript in web analytics, the thought of a decreased acceptance of JavaScript would be a terrible thing. The reason this question keeps popping up is due to the following SiteCatalyst report which gives the breakdown of visitors that have JavaScript enabled or disabled. You can see in this example that the percentage of visitors that come with JavaScript disable is about 17%. You can find this report under Visitor Profile>Technology>JavaScript.

Well, not to worry! Your JavaScript implementation isn’t worthless even if you have a high amount listed here as disabled. This is just a reporting oddity. For some reason SiteCatalyst is counting all mobile visits as not accepting JavaScript. Obviously that is not correct. If you segment out mobile visits you can get a more accurate view for non-mobile devices. Here is an example of a segment you can use to get to non mobile.

With the segment applied you should see the percentage disabled drop to about 1% or less. Take comfort in knowing that non-mobile devices still love JavaScript.

But what about mobile devices? How are we going to tell what the acceptance rate is like in case we need to take a different implementation approach for mobile? Well, until this report changes, I would suggest looking at the devices in your mobile reports and compare them to the JavaScript information in DeivceAtlas. DeviceAtlas has a Device Data repository and they allow you to search for a particular device that you might be interested in. Once you look up the device you can check out the JavaScript section of the report for details on what is accepted. Here you can see that the iPhone 5 does accept JavaScript.

Now keep in mind that JavaScript settings are really an aspect of the phone’s browser and not the actual phone. A user can always modify their individual settings but this Device Atlas information gives you an idea of what the defaults are.

So, in the end, don’t worry about the JavaScript report in SiteCatalyst. JavaScript isn’t always the right thing to use with an implementation but in general it is still a very valid approach.

I am both thrilled and humbled to announce I have joined the Analytics Demystified team as the newest partner, adding dedicated analyst services to enhance Demystified’s offerings to clients. I will be helping Demystified clients use analysis to proactively identify business opportunities, as well as developing the right skill sets and teams to generate insights internally. I truly love exploring data and finding hidden opportunities, as well as sharing my knowledge and developing others. I enjoy discussing, writing and speaking about digital marketing and analytics, including contributing to industry journals, podcasts and speaking at conferences.

Prior to Demystified, I worked as a client-side and agency practitioner across a variety of verticals, including automotive, telecommunications and technology, ecommerce, travel, restaurant and entertainment, and home building. I have had an opportunity to work in web, mobile, marketing and social analytics using market-leading solutions.

I am an avid contributor to the digital analytics community via my work with the Digital Analytics Association (I am currently the Co-Chair of the Membership Committee), the Analysis Exchange, where I help mentor budding analysts to provide (free!) consulting to non-profit organisations and of course, Twitter, where you can follow me at @michelejkiss.

On a personal note, I am originally an Aussie (though you wouldn’t know it from speaking to me – the accent is, sadly, long gone, though my stubborn adherence to Australian spelling has persisted), now living in Boston, MA. I am an avid technology and gadget fan, mainly of the Apple variety, and love to explore new digital trends. I am also a certified Les Mills instructor, so you might find me in the gym from time to time!

You can contact me on michele.kiss@analyticsdemystified.com or reach me via Twitter on @michelejkiss.

I’m a Nate Silver fan. Make no mistake. His book is at the top of my holiday reading list. I have been an avid follower of both his predictive models and his musings for the past 4.5 years. And, when my sister picked me up at the Austin airport on Tuesday evening and we headed to an election watch party, we wound up in a rather heated discussion as to the degree to which the results of the Presidential election were in doubt (I claimed that, as of Tuesday at 7:30 PM Central…they weren’t).

By late Tuesday night, analysts everywhere — despite their political affiliation — rejoiced. Tuesday night was a clear victory for math. The visualization below by the folk at Simply Statistics isn’t the prettiest thing in the world, but it shows how Silver’s predictions compared to the actual vote %:

That’s all well and good. As I said, a victory for math. The Simply Statistics post made an accurate statement when they wrote:

While the pundits were claiming the race was a “dead heat”, the day before the election Nate gave Obama a 90% chance of winning. Several pundits attacked Nate (some attacks were personal) for his predictions and demonstrated their ignorance of Statistics.

But, somehow, this “Silver vs. pundits” thing has taken an interpretive turn off course, as this is now being hailed as being the death knell for the punditry profession:

Hold the phone there, Leroy!

From Google, a pundit is:

An expert in a particular subject or field who is frequently called on to give opinions about it to the public

Pundits do a lot more than simply predict election outcomes. Political pundits, certainly, weigh in on how elections might turn out. But, they also weigh in on interpreting the electorate’s behavior, explaining and debating economic/foreign/healthcare policy, and proposing and defending various political strategies and tactics.

Nate Silver’s intent is to predict the outcome of the election based on the data available at the point of the prediction. One of Silver’s main, front page visualizations actually illustrates how his predictions changed over time:

The closer to the election, the more the probabilities drifted towards 100%/0%. This makes sense (and gets us to the main point of this post). There are two — and only two — underlying factors in the accuracy of the prediction at any point in time:

1. The mindset/preference of all voters at that point of time — this is measured, quite accurately, by the slew of polls conducted throughout the election cycle
2. The amount of time between that point and time and the election — the opportunity for “something to happen” that changes the mindset/preference of voters

Either one of these factors can drive the confidence (dangerous word to use here — that’s not in strict statistical significance meaning of the word) of the prediction up.

Pundits — who, often, also double as partisan strategists — actually weigh in on the interpretation of both of these factors:

• The polls represent facts…but the facts have to be interpreted. And, that interpretation is with an eye to action. Which is…
• What can “we” (strategist hat) or “they” (pundit hat) do to cause “something to happen” between now and the election to change voter mindset?

Michael Gerson weighed in on this with an op-ed piece that, while I don’t agree with his main conclusion, I think makes this point very eloquently:

The most interesting and important thing about politics is not the measurement of opinion but the formation of opinion. Public opinion is the product — the outcome — of politics; it is not the substance of politics.

Now, let’s pivot from political predictive analytics to marketers and marketing analytics. If a CMO goes to the CEO on Day 1 of a new quarter and says, “Our data is showing that we’re losing market share, but we’ve been working on a major new campaign that is launching next week, and we think we will turn the corner by the end of the quarter,” then he is making a reasonable claim. If, however, that same statement is made on Day 89 of the quarter…it is clearly poppycock.

Analytics — and predictive analytics in particular — are based on historical and “now” data. Analysts can and should be presenting “the truth” as to how things stand. They should be identifying specific problem spots so that, in collaboration with marketers, they can look to do something that will “make something happen” that drives more favorable results.

“Analytics vs. Punditry” is a false debate, as is “Analytics vs. Strategy.”

After months of writing, editing and re-editing, The Adobe SiteCatalyst Handbook: An Insider’s Guide is now available!

I have received many questions about the date it is available and formats. The book is available in both hardcopy and digitally from the Pearson publishing site using the preceding link. The book is also available on Amazon.com and in the iTunes Bookstore. You can check out the table of contents on the Pearson site as well as on these other sites.

To hear more about the making of the book, you can listen to Rudi and I discuss it on this podcast. If you have any questions, please leave them here as a comment. Thanks and enjoy the book!

I am wildly excited by the opportunity to join the Demystified team. I look forward to contributing my own expertise to the deep knowledge of Eric, John, Adam, and Brian to provide even greater value to our clients. I work with clients to evolve their web analytics program and to build their digital solutions through system integrations. I enjoy measurement evaluations, solution design, implementation management, data quality evaluations, basic and advanced user trainings, testing, analysis feedback sessions, all things Excel, tool development, and executive presentations and communications.

Previously I worked at Adobe (through the Omniture acquisition) as Principal Consultant for Digital Analytics and Optimization. I had the pleasure of working with a lot of great people and technology. I certainly did not leave Adobe due to any level of dissatisfaction. I truly had a dream job at Adobe. Then Analytics Demystified came along and I saw it as a wonderful opportunity to advance my career and to continue doing what I love–helping companies use data and systems to provide impactful business results. It is almost as if I am now in a dream within a dream (Inception anyone?). I would like to give special thanks to the managers I worked with at Adobe along the way including Matt Belkin,Cameron Barnes, Josh Dahmer, Dave Kirschner, and James Hodges for the great opportunities they provided to me. Also a thanks to my many friends on the Adobe Consulting Services team that I worked with for many years.

Of the many successes I had at Adobe, the most…unique…was to win the 2011 Halloween costume contest. If you are at all familiar with the way that Adobe does Halloween in Utah then you know that there is an amazing amount of competition for this prize. I mostly mention this because it is funny, but I also think it is indicative of the creativity and quality of work I provide.

On a personal note, I am a husband to a beautiful wife and father to three beautiful little girls. I live in Utah.  I enjoy outdoors activities such as rock climbing, canyoneering, backpacking, and snowboarding. I’m also trying to get better at surfing but that has been difficult to do given my land-locked state. I volunteer as an Assistant Scout Master to help boys in the neighborhood get cool merit badges and build character.

If you need help with your digital solutions feel free to reach out to me by email (kevin AT analyticsdemystified.com) and you can follow me on Twitter (@willeitner). I look forward to working with all of you in the digital marketing community.

This was originally published as the President’s Message in the August DAA Newsletter.

I’ve been spending a lot of time recently working with data. For some clients I’m helping to assemble data from multiple sources across their enterprise to answer business questions like how does clickstream behavior impact revenue. For other clients, I’m strategizing about using aggregate data to create new opportunities that provide added insights and actionable steps toward increasing profitability. And for fun, I’m slicing through data to gain greater understanding of events I’ve missed or simply things that I’m curious about.

This last effort is what got me typing today. As I sorted through Tweets and scoured the web for information about the recent DAA Symposium in San Francisco, I was heads down looking at data. I wanted to accomplish two very specific objectives: 1) to validate a new calculated metric that I’m working on, and 2) to simply find out how the event was and what type of knowledge was being shared.

So I turned to five different tools to try to find the answers that would satisfy my curiosity.

My research quickly yielded data that showed how many Tweets with @DAAorg and #SanFranDAA were flying; who the top contributors were; and in some cases how many impressions were created by these messages across the Web. As I researched more, I became more and more focused on the numbers and sought to find the story within the data that would tell me more. As I dug deeper, my tracking spreadsheet started to grow and I began to see that across the five tools, each had significant gaps in the data that they provided. While most were able to reveal the total volume of mentions for my specific keywords, there was a great deal of variation in what they found. Further, the data produced by these tools was often lacking metrics that I wanted to perform my calculations. But what really struck me was the fact that amid all this data I was looking at, very few of these tools told me anything about the content of what was being said. Sure, I could scroll through the individual Tweets and see the content, there were also lists of top keywords showing me what was mentioned most, and even in a few cases there were word clouds that highlighted commonly mentioned terms and their relationship to my search query. But through all of this data I still didn’t know what really happened at the DAA Symposium in San Francisco. I needed someone who was there to fill in this essential piece of information.

But I was still determined to produce something from my exercise in curiosity, so I sent out a Tweet with a quantitative perspective on what I had discovered. Almost immediately, I received a response that asked… “@johnlovett @DAAorg so what’s the qualitative story?” I too had this question in my mind and with the help of this one innocuous Tweet; I realized that every data exercise can benefit from both the quantitative and qualitative sides of the story. Either one alone is woefully insufficient. By digging into the data, there were things that I could see that helped me to understand what happened at the event, and I was even able to gain a better understanding of the awareness created by the event using my calculated metric. However, what I failed to capture in looking solely at the data alone was the qualitative message. Through all the Tweets and data I analyzed, I learned some very interesting things, but the results of my analysis were hollow without a first hand narrative to accompany them.

While this may be painfully obvious to many, all too often I see organizations lose sight of this fact. They expect digital analysts to amass data and crunch numbers to uncover revelations about the business. But in many cases, these analysts don’t have the benefit of understanding the strategy behind the numbers or the context of a story that they data can support. This makes their jobs incredibly more difficult and ultimately it leaves their analysis with a hollow void that is begging for a narrative. In my experience, I’ve found that this narrative comes from collaboration between analysts and business stakeholders who take both sides (the quantitative and the qualitative) to showcase results in a manner that is not only meaningful, but also leaves a lasting impression.

So the next time you’re itching to deliver that beautiful analysis you just created…or if you’re listening to an eager analyst share new data…ask yourself if the perspective you’re hearing considers both the quantitative and qualitative sides of the story. If not, ask for more.

What do you think?

Sincerely,
John Lovett DAA President

PS! Here’s links to blog posts from Krista Seiden’s (BloggerChica) and @AllaedinEzzedin’s Thanks!

I am extremely excited to be joining Adam, Eric, and John here at Analytics Demystified.  While at Offermatica, Omniture and then Adobe I witnessed first hand the value this firm brings to clients and I am incredibly proud to be working with them.

A bit about me

I’m originally from Chicago but moved to San Francisco not long after finishing Graduate School in 2004.  Soon after arriving I met the fine folks at Offermatica and started my optimization career servicing clients large and small and across every industry.  It was during these years I found out how to best help organizations scale their optimization programs and, more importantly, how to get the most value out of their optimization platform.

In the years that followed at Omniture and then at Adobe, I spent most of my time continuing to help clients build best of breed optimization teams and practices.

These practices included auditing implementation, training, campaign road mapping, and the ever important process of analysis and communicating results to other parts of the organization.

During those years I also architected solutions for clients that allowed them to get more value out of their personalization and optimization platforms by integrating those platforms with their Analytics, Demand Generation tools, tag management systems, Email service providers and with other tools that share data internally and externally.  I am a strong believer that optimization and personalization should span across all marketing efforts and not just on the website; and integrating internal and external tools enables this.

Going forward

At Analytics Demystified, my hope is to continue helping clients in this manner as I see the incredible value it brings them.  I want to show them how to get the most out of their optimization and personalization tools.  While my background has been heavily focused around the Adobe technologies such Test&Target, Test&Target1:1, and Recommendations, I am already branching out and applying my skill set to other vendor tools.

I really look forward to sharing my insights here on this blog and I hope to hear from all of you here as well.  If I can be of any help to your business or you would like to chat, do not hesitate to let me know.   I can be reached via this page or by email at brian.hawkins@analyticsdemystified.com.

Adam, John, and I are incredibly excited to announce that industry veteran Brian Hawkins is joining Analytics Demystified to help us expand our offerings around testing, optimization, and personalization of all forms of digital communication. Brian is the most widely recognized expert in the field when it comes to Enterprise-class optimization and personalization technology, integration, and strategy. He comes to us from Offermatica by way of Omniture and Adobe, and we are delighted to build on our support for Adobe’s solutions, adding Brian’s expertise on Test&Target to Adam’s SiteCatalyst-related offerings.

Brian’s offerings at Demystified will look a lot like Adam’s — audits of current implementations, strategic planning for testing and optimization readiness, systems integration architecture and support, and planning support for the entire end-to-end process of site and application optimization in the Enterprise. While Brian’s technology expertise is strongest on Test&Target, his knowledge of what it takes from a teams, governance, and process perspective to be successful transcends platforms and I believe will incredibly valuable to any large business trying to become agile in their optimization efforts.

Brian is taking a little time off before getting started mid-month but I will be adding his blog, a description of his offerings, and more about him to the site very soon. Clients are welcome to contact us directly to set up time to meet Brian (and if you’re not a client you can call too, that is if you have any interest in testing, optimization, or personalization.)

Brian will be with us at Emetrics, Adobe’s Summit in Salt Lake City, and of course he will be presenting at our own ACCELERATE event in Chicago on April 4th. If you’re at any of these events and would like to meet or connect with Brian, please drop me a note.

We hope you will join us in welcoming Brian to the team.