Honest Talk About Tag Management (TMS) and Site Speed

Do tag management systems (TMS) make web sites faster? Yes!

Does this differentiate them? Sometimes, but not a whole lot.

Has a customer ever left one of the major TMSs on the basis of poor site performance (or better performance from a competitor)? Not to my knowledge.

How much should site performance influence my TMS decision? NOT AT ALL (not if you’re comparing the top-tier providers, which I’d expect you are).

It’s incredible to me all of the talk about site performance coming from TMS vendors. The truth is this: among the top 3-4 vendors, the real-world differences in site speed are probably negligible (there are differences, which I’ll talk about below). Each of these vendors has customers raving about site speed improvements, so doesn’t it stand to reason you’ll be happy with any of them, when it comes to this [completely tangential] measure of potential success with a TMS?

If we think for a moment about why we are buying a TMS in the first place, the answer is simple. We are buying one because we have users (whole/segments/individuals), data, and actions/events (those users doing things on our sites or in our apps) that we care to know about and act upon with our marketing tool set. That’s it. Tag management, from the bottom up, is designed to identify when users go places, click things, provide information, etc., and allow us to react to those stimuli with the appropriate responses, including collecting data, delivering chats, surveys, A/B tests, etc. That’s it.

The trouble with this simple stimulus/response formula, historically speaking, is that it involved technical people in different departments. We would say, “When the customer goes to page X or does thing Y, I want tool Z to do A, B and C.” Replicate that ask hundreds or thousands of times, with varying complexity in the individual question and you end up with a mess where IT can never get it all done, get it all right, or stop breaking it as they work on requests from other stakeholders in the organization.

THAT is the problem TMS is solving. Not site speed. TMS solves for the issue where a stakeholder has to rely on an outside department or agency to do work they are uniquely qualified for (picture a pilot relying on a second person to steer the plane, and the only person who knows about flying is the pilot, who has to teach this person as much as possible while in mid-air so they don’t crash). TMS puts power directly in the hands of the stakeholders, so the pilots can steer the planes themselves.

When a business is thinking about investing in, structuring around, and realizing the potential of a TMS, they need to think about how, when, where and why they will use this tool day to day to complete their needed tasks.

Let’s talk about the mechanics involved in site speed

Site speed is a pretty basic concept. Browsers observe a specific set of laws, and maximizing site speed boils down to just a few key things.

The first part of site speed is simply downloading files. Most web pages are made up of dozens or hundreds of files that make up the copy, formatting, fonts, images, functionality, layout, etc. of the page. Certain files have to download sequentially (one must finish before the other can start), while other types of files can download in parallel (two or more files, up to 8 in most browsers, can download at the same time).

The two factors that make up the total time it takes to download these files are latency and size. Latency is kind of like how many times the telephone rings before the other side picks up, and size is the length of the conversation before you hang up.

So when we’re talking about making a site faster, we have a few things we can do:

  1. Reduce the number of files being downloaded
  2. Reduce the size of the files being downloaded
  3. Make the connections (phone ringing) faster to the sources of these files
  4. Make some files that used to load sequentially load in parallel

You’ll hear a lot of buzzwords like asynchronous thrown around in this space, but many of the sales people talking about these things struggle to explain them, or have the technical expertise to connect the dots in real world terms. The above 4 mechanisms are the ONLY ways we can improve a site’s speed, and the TMS vendors have all cooked up a few recipes that all work pretty well.

For #1 and #2, all TMSs strike a balance on this one. Platforms like Ensighten have a server-side process that hybridizes the approach and allows the platform to only send the necessary files and tags down to the browser, based on the page that visitor is on (or other criteria). This means that it sends a payload that is lighter and hypothetically faster. If Ensighten were to send all tags for the whole site to the browser at once, that file would be much larger, and therefore slower. Tools like Tealium and Adobe’s dynamic tag management take a different approach. Rather than having a server make the determination, these tools deliver a lightweight central set of logic, and then load specific branches from that central logic file based on decisions within that logic (like, again, what page the user is on, what data is present on that page, etc.).

BrightTag, too, has played their cards on these speed factors, and they do so in the form of server to server communication. Rather than loading 10 tags in the browser, they load 1 or 2 or 5, and load the others in the background from their servers. While this seems like the path to the chosen land, the truth is that many tags aren’t compatible with this type of approach, so it’s applicable in some cases and not others.

So in real world terms, what does this mean? How do they score?

Ensighten: Blazingly fast
Tealium: Super duper blindingly fast
Adobe/DTM/(Satellite): Slap your grandma fast
BrightTag: Yowza bo bowza fast

So what about the ideas of #3 and #4, where we improve responsiveness and parallelize these files? On #3, that is why all of the major TMSs serve their files from a CDN, multiple CDNs, or allow you to choose your own architecture or an architecture of choice (like Adobe DTM/Satellite). This ensures the telephone is answered instantly. But that’s not the whole story. Even if the TMS answers its phone quickly, that doesn’t mean your other vendors will, too. Will Google answer the AdWords or DoubleClick phone right away? Will Silverpop, Facebook, Google Analytics, Foresee, Opinionlab, Optimizely, Adobe, and every other vendor you’re delivering through your TMS pick up that phone like a tween expecting a call from their BFF? Probably not.

And that’s the last factor. BrightTag, as we discussed above, moves as many of those calls off the page as possible, while DTM, Tealium and Ensighten manage them directly on the page (which I like because that’s how these things were designed to be used). DTM, for example, has mechanisms that can parallelize these tags or calls, letting the phone ring on 8 calls at a time (or the maximum allowed in a browser), without letting one hold up the other. It and other tools have mechanisms to take calls that are never answered out of the queue, and time the calls to minimize or eliminate the impact on user experience (I have more experience with DTM than others, since I made it, but they all have powerful tools that will probably all converge and not differentiate from one TMS to another soon enough, if they haven’t already).

So where does that net out? The best TMSs are super fast themselves, load tags and tools smartly, and are growing in their capability set. In simple english: practically zero difference. I’m sure sales guys will try to tell a different story, but if you go with simple science, it’s pretty straightforward.

Take a look at the facts and gear yourself and your organization around real-world execution in the tool. Look at TMS as a chair that you and other stakeholders need to sit in practically every day in the future. Buy the chair for its recurring comfort, ergonomics and longevity, not for its tangential benefits that are mostly one-time things.

Don’t Be Average. Destroy Average.

On Peyton and work…

Ever feel like Peyton did last night? Peyton is one of the best quarterbacks of our time, yet even sometimes he can look and feel like nothing is working. He can choose in those times to question himself and his talent, or he can realize that there are times when super talented people are in situations where their talent can’t shine.

Some of the smartest and most capable people I have ever met are like last night Peytons in their work place. They have strong beliefs and philosophies, the intellect to build a plan and the ethic to execute, yet their environment or their teammates won’t let them shine. It amazes me how many people who are perfectly capable of thinking and acting in the big picture start to question themselves in these environments and maybe even stop pushing for what they know is right, thinking they aren’t good enough to get it done. There are literally billions of people on this earth who choose to not make a difference by giving up and falling into the current of their surroundings, and then there are the tiny few who realize the current is just a bunch of averageness for them to swim through.

If you can beat averageness, you can change the world. It might just be a little part, or it could be a big part. But don’t let the world make you start thinking you are average, because you probably aren’t unless you just let yourself be. Don’t underestimate your impact, either, because even the Snuggie changed the world.

Most of the things we love were created by people who thought the average way was not good enough. Sadly, most of those people had to leave their prior work environment to get it done because of the sea of averageness there. The sad part is that they could have gotten it done where they were if others had jumped on board. You see, breaking averageness isn’t always being the inventor, either. Sometimes it’s seeing something and being kindle or even gasoline on that flame. Honestly, those who enable change and make the flame burn brighter are so much more important catalysts for change than the inventors (who often just seem crazy or unrealistic).

So whether you have the vision of how the world should change (even if it’s only a blanket with sleeves) or you’re the one who believes in and can amplify another’s vision, you play a critical role in destroying averageness.

Peyton is going to be just fine, because he is either going to get into the right place or he’s going to help these people learn from yesterday and emerge a lot less average. Sports is a cliche go-to in business, but what these people do have is a mental strength and the deep knowledge that they are born to stand out. Don’t mistake their mental strength and their physical strength. You might not have the outward physical appearance of an NFL athlete, but that’s only because God gave you those muscles in your head or in your heart, instead. You are born to stand out. Go do something awesome (not a blanket with leg holes, though).

Minimum viable product vs. minimum viable idea

If you want to do something big, it is true that you need to start small. But don’t confuse starting small for thinking small.

If you’ve read the Steve Jobs biography, there’s a chapter that describe’s Steve’s ambitions to create the original Macintosh. While it’s cliche to go to a Steve Jobs example when talking about stuff like this, I think that the quote about Steve really does apply to a lot of people and situations where innovation and excellence is king:

Steve did the impossible because he didn’t know it was impossible.

There are dozens of factors that separate great products from mediocre ones and great product companies from mediocre ones. Same goes for suppliers of consulting and services. One factor I’ve always been interested in, in particular, is whether a company lets itself try to change the world (or at least a tiny part of it). Does a company have an attitude that builds their products or services out of a construct of what’s possible in the world around them, or do they think about what they would do if there were zero boundaries or restrictions? Companies typically fall on one side of this line, or the other.

How many meetings happen every day where people try to shrink ideas with statements like:

  • “That won’t work”
  • “That isn’t how things are done here”
  • “People won’t get it”
  • “You can’t change those people”
  • “That’s not realistic”

It happens all day, every day at most places. The issue here isn’t that these people are wrong. In fact, they are probably right. They are filtering ideas through their understanding of what is possible and not possible, and weighing in. What these people are seeking is not the minimum viable manifestation of a grander idea; they are seeking a minimal, compatible, compliant, innocuous idea.

The problem with this approach is that it is destructive in nature. It directly shrinks the ambition, not the product (and therefore indirectly shrinks the product, irrevocably, too). It shrinks creativity, disruption, innovation, and other things that make amazing people, places, and work…well…amazing. By shrinking the original goal or idea, iterations that happen down the road are destined to be bolt-on rather than a seamless, elegant growth in product maturity (have you ever seen a franken-product or software duct taped together at every possible point?).

What we need to be seeking instead is to launch the minimum viable product. The simplest viable form of a big idea. A crack in the rock where water can enter, later expanding and breaking the rock apart. Nobody has a crystal ball and can see into the future of a product, service, or company with absolute certainty, but if the product is a result of the minimum viable idea, we do know for certain that what happens later will be a retrofitted mess, rather than a part of a grander plan.

When you think about where you work, are you trying to accomplish something grandiose by starting small and iterating toward the endgame of best-in-class sophistication, features, process, communication, etc., or is your company trying to avoid the grandiose, stay in the now, and think small?

This is no different for the analyst than it is for the product manager, visionary, or any other role you admire in amazing companies, charities, or in artists, etc. What can we be “thinking big” about? What can we be focused on that would revolutionize our company or our industry, and then start with the smaller pieces that get us into the cracks in the rocks? There are so many amazing opportunities in multi-channel, mobile, social, with our web sites, in testing, in better understanding our audience, and so much more. Big, big ideas.

The Mac was built one piece at a time. One line of code, one board, one nickel-plated screw of the case, one part of the mouse and choice of typography for the keyboard keys…each at a time. The Mac was built at the micro level, fueled by a macro vision (and the vision itself was about what computing would look like 10, 20, 30 years beyond; not just for that single computer).

The world around us requires us to execute small, but what’s important is that we don’t let anyone force us to think small.

This is how we think about our products, our consulting, our clients’ businesses and our own business. And I can promise you, working this way is way more fun.

4 Awesome Digital Analytics Segments You Probably Haven’t Considered

Segmentation is key in analytics…that is something probably nobody would argue (hopefully). Today, our segments are based largely around things like traffic sources, landing pages, visitor profiles (sometimes very good profiles), technology/devices, and more. This got me thinking about a few “dream segments,” where I could look at people based on real-world scenarios of how people use the web, apps, devices, etc.

So, here are a few segmentation pipedreams I’ve had on my mind lately, and a glancing swipe at how I’d try to identify them.

On the move

Do you know the percentage of your mobile users who are running, walking, sitting, on a bus, the subway, or otherwise? The state of motion a user is in may have a profound impact on their experience. What if I could tell CNN the percentage of traffic, by hour, of people on their site who are on a treadmill, and what their habits are vs. other types of users in cabs, riding the train, or walking down the street? How about by time of year, geography, etc.? And what if we could optimize that user segment’s experience?

Creating the Segment – Here’s a super simple example of an approach I cooked up: It’s over-simple for this example, but predicts whether the user is sitting, walking, or if they’ve placed their phone on their desk while reading. OPEN http://www.learn-analytics.com/motion on your iPhone (that’s all I tested it on).


How many times has a person whipped out their phone to fact check when someone runs their mouth about something they heard from some guy somewhere? Do you know how many of your visitors are coming to your site to prove a point to their friends? How can you do a better job monetizing that traffic?

Creating the Segment – Look at bounce and low-engagement traffic coming from search. Can you classify some of your content as bar-gument worthy? Maybe you can create some sort of a social ripple like a tweet or facebook status saying you won a bar-gument on this site. Keep score. Could be fun and I’d imagine it would offer a lot of insight into this segment for content sites.

@ Work

Do you know how many people on your B2C site visit from their workplace? Chances are, your retail site is very poorly optimized to the chopped-up and hurried experience a customer is possibly trying to squeeze in without being caught. You should understand which size companies and user profiles people visit your site from, use that to personalize the experience, and more. If someone is visiting Saks from an F500 and they are an HR executive (data you can easily get from bizo with surprising accuracy), couldn’t you show them some great work and vacation clothes on the home page? Couldn’t you provide them a streamlined experience for shopping? Couldn’t you even do some special things to help some of your consumers circumnavigate their stupid firewalls? Probably yes.

It would be great for the large B2C site to know more about visitor habits while at work. Which workplaces offer a more lax policy? Which have hurried users? Which have firewall issues? Some of the daytime commerce or engagement metrics you think aren’t so hot today could probably be easily explained by some of this information…

Creating the Segment – Why doesn’t every major retailer invest in Bizo or DemandBase or the like? It makes total sense to get this data (just do a trial if you have doubts, and use Satellite to make installation trivially easy). Then, dig into the experiences of at-work consumers. Are they in a rush, and which sub-segments aren’t? What can you learn about some of your historical data and future targeting of these consumers?

Everybody has to go at some point

So, I’ll end on the obvious one. The smartphone is a very popular device in the…facilities. Are you providing some continuity to consumers who want to start, continue, or finish their shopping or browsing experience in this zone of solace in the workplace or at home?

Creating the Segment – This one might require some creativity around timeframes, amount of motion (see above), devices, and more. Maybe for this one, I’ll open it up to suggestions? How do you know when someone’s having personal time at work or at home? How would you create this segment?

My predictions and hopes for digital analytics in 2013

Well, it’s that time of year again! But this time, we’re rocking with DIGITAL analytics, not just web. A lot of new stuff, and a lot of good, solid fundamentals applied to new things to be conquered in 2013. I hope 2012 was a good year for you (no doubt!), but I think 2013 is going to be a HELL of a lot better.

First, let’s recap the 2012 predictions from this post:

1. Analysts need to stop talking about savings. And boy did we ever. I knew you badasses were up to the task. What we do is not about shrinking businesses or not participating. It’s about growing them. Yes, it’s a perfectly valid idea that in order to reallocate budget, you have to trim waste, but in my mind, that’s not a strong sell. I think that there’s something [sadly, yet] deeply satisfying about looking at something hugely inefficient, calling dumbasses out on their poor work and waste, and recouping the losses. But not nearly as rewarding as turning losses into gains over and over again. This is a cycle that will not stop. You can’t / won’t clean house just once.

It’s awesome to see conversations about superior investment, multi-channel, and…ick…big data blossoming, all in the context of efficiency, shared learning, more complete understanding, networked thinking and upside, not just where we should trim the hedges. Lovely stuff indeed.

2. Get businesses to stop chopping our jobs down to bite-sized questions. When I wrote this last year, I was seeing a lot of businesses only asking for what they knew was available in reports, rather than sharing their true needs and challenges. Again, I have to say HOLY SHNIKEYS our industry murdered this one.

I’m now hearing so many more businesses coming to us, our competitors, in-house analysts and even evil vendors with real business questions. Analytics tools are now being bought on the basis of being able to pick apart complex, segmented, multi-session/channel behavior, not on the basis of pre-baked reports. Tag management is being widely adopted to solve efficiency and process problems that plague operations. Testing platforms like Optimizely are becoming more WYSIWYG than JS. We are catapulting into an era where the tools are becoming easier to use in the course of business, where stakeholders can take more control, and where analysts are less technical in nature and more business-oriented.

Analysts today are asked the big questions, and when you are, you deliver. Awesome to see.

So, I’m pretty much pumped. 2012 was a huge year in the understood and captured value of our industry. So, what’s up now?

Well, there are a lot of buzzwords flying around these days, all about big data, R (I guess this is technically more of a “buzzletter”), data science, multi-channel, attribution, and more. And for the most part, people are really thinking these problems through. Businesses seem to be cooling their jets on finding the next magic bullet and they’re getting serious about putting significant intellect and funding behind tackling big, complex problems. This is awesome for us, and will introduce a lot of choice into how career paths look moving forward. Years ago, you could either be a marketer-type or a tech-type. Now, there are so many things it would make your head spin.

So, how does that play into predictions? Well, that’s tough. Now that we’re out of our infancy and even adolescence, the market has fragmented. Not long ago, web analytics happening at a small, savvy business wasn’t all that different looking than web analytics happening at a Fortune 500 (you can fight me on that one, but I have to warn you of my stubbornness). Today, they are radically different. Enterprise analytics is separating from the “pack,” if there even is a pack, and that separation seems to be widening by the second. Enterprise is committing to huge investments in both efficiency and sophistication, and the multi-channel strategies in place are simply something most smaller businesses can’t afford.

But I do think that there are some shared ideas or enterprise themes that other businesses can borrow. So I’ll do my best to make this make sense. If it doesn’t, hit me with a rubber chicken next time you see me.

2013 in Digital Analytics

Prediction 1: You can’t buy maturity any more

Over the course of the last 5 years, there have been a number of analytics “maturity models” used to score businesses. These have been awesome, as they typically highlight strengths and weaknesses, and help a business identify where they need to put their attention and their money. Historically, though, these models have put a somewhat heavy emphasis on both the sophistication of tools and the types of people your organization has hired. Also to note, the models have looked at your KPIs, goals, etc.

The problem with these models of maturity is they measure potential rather than productivity. Newer models are focused on the altitude, speed, and direction of your shuttle, rather than the quality of the launch pad. You can buy your way into potential. You have to fly your way to actuals.

I would strongly recommend that every large organization assess their maturity in a qualitative and quantitative manner. We do this with every single one of our clients, whether that client uses our consulting or if they use Satellite, as both product and consulting have enormous implications on the way your business will work.

When you assess your organization’s maturity, you need to look at actuals. Don’t ask, “Do I have a testing tool with segmentation capabilities?” Instead, ask, “How many segment-driven tests have yielded conclusive findings that were adopted widely in the organization, in the last quarter?” Also, you need to identify whether the maturity of your organization occurs in rogue pockets or if it’s widely accepted and embedded into the culture, goals, process, and executive mindset. I can’t tell you how many great analytics, testing or personalization operations or people I’ve found inside of an organization that deploys their web site twice a year and doesn’t know what these peoples’ names are. Rocket fuel inside a Pontiac Aztec.

Prediction 2: Widespread use of consultants

Building on #1, I see people really getting help this year. Not just tactical help with implementations and not just strategic help with seminars or executive retreats. Real soup to nuts help. Just look at what Eric Peterson is doing at Web Analytics Demystified: that organization is growing into something that won’t just teach you what swimming is, but will let you swim on their backs, have them swim next to you, swim for you, or whatever it takes to get you there. Results. Actuals.

The truth is this: there are a lot more open slots for great analytics leaders than there are great leaders or analysts. Every company wants to hire in-house talent to absolutely rock the house with analytics. And while there are tons of total badasses out there, there just aren’t enough.

So, here’s an idea: get a absolute killer rock star consultant FIRST. Let them tell you who to hire. Let them manage the transition. But don’t even start if you aren’t ready to have rockets strapped to your ass and lit. You’re wasting everyone’s time if you aren’t ready to roll. Analytics consulting is not a daycare. It is more like crossfit in space at 10,000 mph with pods that will automatically shoot morons and progress preventers into deep space.

Prediction #3: Small wins will give big data big momentum

You like to say, “big data,” huh? Think that makes you tough?! Well, in 2013, it will.

Here’s what I think will happen. Big data is currently the closest thing we have to a “magic bullet” obsession in our industry. Hopefully we’ll get over that pretty quickly so we can get to work on it. I think the first step in tackling this mountain is to break it down into tiny little wins, and each of them will be awesome. But let’s set expectations ahead of time: just because it’ll be awesome does NOT mean each win will magically rain money down on our heads. So get over that and you’ll be ready to take your first steps.

The first steps will be in simple cross-channel and tangential data connections. There are some incredibly cool projects happening around the country right now when it comes to this. Here are the questions I’m excited to start answering:

  • How does our conversion vary by happy vs. upset customers (social)?
  • How does our conversion vary by geography by weather and other external events?
  • What are correlations to capital markets, pricing indices, legislation, or news?

Now, for many businesses, these types of things may not be relevant. But at huge enterprise scale, I think that all of the modeling and R work being done to assess forces within our small ecosystem are probably brewing a fresh, giant pot of false positives and negatives. It’s time for us to think more like the BI side on this front, looking at external market forces equally, if not more. Wal Mart stocks strawberry Pop Tarts on the basis of weather patterns and has for decades. Our jobs are thousands of times easier when dealing with complex or incongruous data marriage than Wal Mart’s was when they explored this for the first time, so let’s take advantage of that. But, of course, that’s not a small win, necessarily, so I digress. Just saying the precedence and success stories are there…

Large brands are currently in the process of making big data small by breaking it into pieces. I’m hearing great stories about user-level (anonymous, of course) understanding of sentiment vs. site behavior. This is taking a really potentially lame social media metric and marrying it with really not-lame business metrics on our web sites. I’m also hearing about cool basket analyses, multi-session trends (for predictive suggestions), and some smart attribution…

Prediction #4: Attribution will be appropriately…uh…attributed

First click. Last click. Weighted. Time decay. Brain decay…

The problem with our current approach to attribution isn’t just related to the sequence of the click, but also the relevance of the conversion type. Conversion type? What the hell are you talking about, Evan?

I’m talking about the fact that today, the vast majority of marketing channel efforts are measured against one thing: conversion. The way we then tie credit back to earlier interactions is through attribution. That keyword, email, or display creative “opened” this relationship, while another one “closed” that customer. Poppycock.

Here’s where we start to mend this fence, though: marketing needs to trust analytics to handle this, and the business needs to trust marketing to “soften” some of their metrics. Let me explain…

While there may be a “conversion” on your web site, more often than not, that conversion is a business use case, not a user’s use case. The majority of your users are there to research, compare, consider, hunt, etc. We will start to solve attribution when we credit appropriate to the use case for the user, not just the business.

One cool thing we’re doing with Satellite is assigning meta to your different site actions and audiences. Certain interactions like image gallery views, video views, product list filtering or ordering, site search, etc. would be considered “high funnel” interactions, while things like newsletter subscriptions, whitepaper downloads, or sales would be considered “low funnel.” Now, you can have as gradiated a funnel as you like, but simple high/low is a good start. Now, you take your search campaigns, emails, tweets, wall posts, display creative, etc. and you figure out what each of those is supposed to do. If a user searches for reviews, ratings, product pictures, or comparisons, don’t measure success to financial conversion. Measure it instead to those high-funnel interactions that make sense for that user’s use case. For a 1-day sale creative, go ahead and measure to monetary conversion.

What you’ll start to see is that when breaking your media and your conversions down and pairing them appropriately, your effective rate of converting users based on their use case will be extraordinarily high, restoring faith in these “high funnel” media investments. You’ll then also be able to model out consumer lifecycle: users who search high-funnel and have one or more high-funnel conversions in that session are x% more likely to return and purchase, and the “middle-50” value of that purchase will be between y and z dollars. That’s a lot more transparency than some simple, “This was the third click out of 7 so we attribute dollars based on the assumption that all mammals are dogs, which has the same empirical value as current attribution models.”

Predictions 5+

I had a few more of these ready, but this post is already ridiculously long. I’ll turn it over to you, instead. What are the big themes you think we’re poised to tackle this year? The fan is widening, so it’s getting tougher to write this type of a post! And that’s a sign of the success you’ve created in this industry. Let’s make 2013 epic.

Why your dashboards suck, and 4 things you can do about it

Dashboards suck. Big time. Why? Because the people who build them are not thinking about their purpose.


Let’s put together a list of what dashboards are not for:

  • Showing you what’s going on
  • Updating stakeholders on key metrics
  • Marrying data from different sources
  • Offering a “heads-up” view of the business


Dashboards are 100% absolutely not at all in any way whatsoever about information. That’s what reports and meetings are for. Dashboards are for one thing and one thing only: action.

Let’s break this down into two separate views. First, we’ll think about why this is the case. Then, we’ll explore comparisons in other parts of our life. Got 5 minutes? Let’s do it.

Why dashboards aren’t about “information”

When I used to see comparisons between Google and Facebook’s engagement metrics, I wanted to stab myself in the brain. The thinking was that since people were spending more time and consuming more pageviews on Facebook that Google was being bested.

Looking at this claim in terms of purpose rather than metrics, we can see this means that both of these sites are successful (and if Facebook’s metrics just passed Google’s, it also shows that Google was a hell of a lot more successful at that point in time than Facebook, not the other way around). Why? Because Google’s sole mission (for search) is to send people AWAY. Facebook’s mission, on the other hand, was to get people to stay. So, if Facebook’s visits, session duration and pageviews are just passing Google, that means Facebook (at the time) had a very, very long way to go to best Google.

Regardless of who’s winning, which site breeds more productivity?

Remember the claim up there? People don’t know why they’re designing dashboards. Dashboards that are trying to give people the lay of the land, provide information, context and a wide view are not functioning properly. Dashboards built this way draw the user in, asking them to spend time clicking different views and tabs, taking mental notes, drawing comparisons, and figuring out whether or not everything is okay. The dashboard is pulling when it should be pushing. The measure of a good dashboard is its likeness to Google, not Facebook. Good dashboards put people to work.

Pushing isn’t exactly the right word. Dashboards should be shooting you out like a human cannonball toward the things you should be working on. Dashboards need immediacy, urgency, alerts, all screaming at you like wild banshees about specific parts of your business, site, social presence, etc. LOOK AT THIS RIGHT NOW OR YOU WILL PERISH. That is what dashboards are for. They are tools for tacticians to target their efforts, not for generalists to broaden their understanding.

How this looks in other places

Let’s take a look at dashboards elsewhere. Cars, planes, stuff like that, for example.

Now before you start picturing a 747 cockpit that looks remarkably like your corporate dashboards, let’s think about a car and build from there. In my car, my dashboard tells me some pretty basic things about my engine (tach, temperature), speed, and fuel. There may be some niceties like outside temperature, etc. I may have a GPS that is telling me where to go, too. And my dashboard has a bunch of unlit indicators about other things like tire pressure, oil levels, windshield fluid, airbag status, etc. etc. etc. Keyword: unlit.

The purpose of all of this is twofold: one is sort of like realtime reporting: I can indeed see some non-critical basics (that could become critical, like speed) when I’m not having to pay attention to a traffic situation or a more pressing matter. But the second purpose (the important one) is what I normally cannot see in the unlit area. Things that will come alive when and only when I need to know about them. My GPS tells me when to turn and shuts the hell up in-between. Sure, I can look at it, but that’s again in my downtime.

Can you imagine what driving would be like if all of these indicators were on and I had to check in on each one constantly to understand status and what I should do in response?

Graduating to the 747, we have a lot more going on, but again, almost everything is unlit or not intentionally drawing attention. If the pilot wants to get a swath of information about the plane’s status, she certainly can by looking around (just as we can by leaving our dashboard and getting into our analytics tools and other reports/meetings). But she’s looking around in her downtime. She’s not looking at 300 dials when taking off. She’s not looking at 300 dials when the engine is on fire, because when the engine is on fire, there is a HUGE amount of focus drawn to the exact dials and controls the pilot will need at that moment.

The plane is a lot like your business. This data is available. It’s sitting around. It’s being produced in reports. But mushing all of it together into a dashboard is not the right thing to do. Mushing all of these dials into a cockpit isn’t the right thing to do, either (it was necessary before today’s technology), which is precisely why most cockpits are starting to look more and more like our cars (a lot of the dials are unused or redundant and have been moved to an as-needed LCD in front of the pilots).

So, great dashboards are…

QUIET when things are not whacky. You look at them, don’t see anything special, and know you have some time to focus on a project you’ve been meaning to pay attention to, you can schedule a meeting to think through new ideas, or you go dig into your data more deeply to find opportunities. A quiet dashboard is a signal that you have the freedom to work on new priorities. All dashboards need a quiet, unlit capability.

LOUD AS HELL when things are whacky. When you log in or view them, the dashboards will tell you immediately that you need to cancel your meetings, hold your calls, order lunch in, and focus on the buzzing alarms and dials out of their tolerable ranges.

TAILORED to the people who are going to look at them. Have a report or meeting if you want/need/have the time to talk about other peoples’ lives and wider status. Your dashboard should be about your plane, not all air traffic over the pacific.

CONTEXTUAL to purpose. If you have a table that looks like the one below, your dashboard is a complete and utter failure:

Why? Because this is out of context, lumped together, and not actionable. Is the purpose of your paid search homogenously to attract new visitors? Is every keyword indicative of a user ready to convert? Should the conversion rate of social be compared to your SEO efforts? Everything on the dashboard should live in the context of purpose. You should have a page about audience attraction, a page about high-propensity converters, a page about amplification and content acceleration, a page about different audience segments and expected results. Then, when you look at the dashboard, you know specifically where you are deficient and maybe even what you need to do about it, not just what the conversion rate of your display campaign is (which is completely useless to anyone who can do anything about it, when presented at this level of granularity).

So, the next logical step is to share some good dashboards with you. If you’re interested in seeing the types of dashboards that actually cause action and keep information in context, leave a comment or contact me on twitter (@evanlapointe).


The Real Housewives of Tag Management

I’ve been carefully avoiding writing about things like this for a few reasons. You don’t want to upset people. You don’t want to pick fights. Plus nobody trusts vendors anyhow. But the TMS space’s maturity levels have descended to a laughable state.

Anyone who has been a partner, client, or potential client in the space has seen the sad state of affairs. They’ve heard the “statistics” on competitors’ performance, seen the comparison tables, read the “research” on the space. The hilarious part is that these businesses must have forgotten that they are selling to analysts. People who get to the bottom of things for a living. Analysts aren’t suckers who believe things just because they’re said or written. They’re going to go through the trouble of actually looking and investigating.

So here’s what I’d like to point out. Despite all of the noise and FUD flying around, most of the players in TMS actually deliver tangible and immediate value. While they may not all live up to their own marketing (which often closely resembles a North Korean display of supremacy), they also don’t live up to the criticism levied on them by competitors.

What these sales people don’t realize is that if everyone is flinging insults, mistruths, and FUD at each other, all that does is introduce confusion. While they think they are making themselves stand out, they are just another source of noise. The net effect of this confusion is decreased sales, increased churn, decreased trust in the client relationship, etc. Certainly from the TMS provider’s perspective, this is bad on all fronts. But what’s more important is that from the client’s perspective, it’s even worse: many clients who could benefit immensely from a TMS do not get one, and the ones who do are saddled with doubt as to whether they’ve made the right choice or face trust issues from colleagues who wanted another solution and are out to prove they were right.

So let’s all grow the hell up on the TMS end, and to the analysts, keep being you. Your natural skills will lead you through the FUD. Make the decision that is right for you. If you’ve made the wrong decision, re-evaluate, decide, and move on. Switching costs are low (that’s kind of the whole point), so you have agility. See through the fog, and call vendors out on their BS, “assumptions,” or reaches. Let’s stick to the facts. That’s what you’re good at.

Pegs & Holes – What “big data” is really about.

There’s a lot of talk about “big data” floating around these days. The next magic bullet, so they say. But what is big data? That’s what everyone’s trying to answer.

First of all, there are two axes of what it seems people are collectively calling “big data” today. Probably more, in fact. But the two simple axes are breadth and depth. There are big data systems like Amazon, where they have outrageously detailed information about individual users’ purchase behavior, product correlations, multi-year buying trends, etc., all in a single source with all data already joined. This is DEEP data. Then, you have big data systems where behavior from multiple systems is being brought together under one roof and joined with common keys of some sort. This is WIDE data. Wide data may have one or more data sources that are also deep, but the depth rarely has anything to do with how well wide data can integrate (you either have usable common keys or you don’t).

There is a lot of hope placed on big data. To what end, though? What is this all about? Justin Cutroni posed this question on Google+ this morning, and it’s sort of amazing that this industry is investing (mentally and monetarily) so heavily in an idea where few people really have discussed outcomes. There was a short discussion on twitter that said something to the effect of:

Duh…when you have more/better information, you can market better.

Academically, sure. In real life, I don’t see it.

This is exactly the hope placed on big data. We hope that there are answers on the other side of big data. This isn’t unlike me buying a pair of running shoes hoping that there will be more running on the other side of my purchase. It doesn’t happen. We invest based on correlation, and my fat ass is still on the couch a month later.

There are many, many examples of businesses who do extraordinarily well, whether they have big data or not. I think this is because they are in sync with the consumer. Big data is certainly one way to get information that can be used to get in sync, and will likely prove to be one of the best, but the business still has to get in sync. Some businesses will spend millions consolidating information and do nothing (a circle peg through concrete). Some will merely learn how to more effectively message to their audience with creative and timing (circle peg through a square hole, in many cases). The best will use big data to drive new and improved products and offerings (circle peg, circle hole).

There are so, so many cases today where consumer needs are simply not met by the present array of products and services. Marketers are so focused on selling their current portfolio, they seem to have completely forgotten that it is possible to make new stuff. Startups do this every day — how many entrepreneurs leap from larger brands to solve for an unmet need? Great brands let these offerings grow. They seek information to improve the portfolio itself, making the sales and marketing process frictionless. And there are all sorts of brands that are in-between.

If all we do with this “360 view” of a customer is figure out when to poke them with a stick, that is pitiful. If, instead, we figure out what their unmet needs are, we are apt to start all sorts of interesting things. I like interesting things. Whether your data is deep or wide or both, you probably already have what you need. If you have the motivation to get in sync, you have all the ingredients you need. But if the motivation isn’t there, your shoes are going to sit and collect dust.

Analyze your brand – how a hospital’s new logo can make you a better digital marketer

At Search Discovery, the very first thing we do when we work with a client is focus on their customer or client. Our early work with every client is about understanding the industry, brand, and micro need/workflow from their customer’s perspective, often temporarily sidelining discussion of the client’s product or service until we feel we can understand it from a consumer’s perspective. This Kool Aid avoidance helps us see the site, the marketing, and the offering itself in a more objective sense, often giving us a radically different perspective than the business we’re working with, as they have been in the day-to-day focus and grind, which often makes it very difficult to step back.

I’ve been wanting to write this post for a while, but I was struggling to find a concept to really anchor it to. Today, on my commute to work, I noticed that a hospital I drive by every day had just redesigned their logo and updated their signage. I love logos, because when done well, I think they often give you a really interesting view into how a brand thinks of itself. The typography, colors and certainly whatever images are used really paint the picture.

The new logo for Piedmont Hospital certainly doesn’t disappoint in this regard:



The tagline that accompanies this new logo: “It’s time to get better.

Nice, huh?

But look more closely. I think this logo tells us a lot more about how this hospital thinks about itself than how a patient thinks about a hospital.

Presumably, the square is an allusion to wellness. The dark red is a very strong color, synonymous with pain, blood, suffering, etc., and I’m guessing this represents a patient who is unwell. The remainder of the illustration is that patent’s path to wellness, a series of progressively less severe colors in a course Piedmont guides you through on your way to getting better.

So far, so good. But here’s where the hospital’s view of their business and the patient’s view diverge radically: the hospital sees wellness as cyclical. Where is this path of wellness leading? Right back to being unwell.

Now, statistically speaking, the hospital is 100% correct (and you probably are, too, if you see your audience in a similar way). When they look at you or me, they see someone who is either well or sick, and someone who is nearly 100% likely (statistically speaking) to get sick several times in the future. Doctors, pharmaceuticals and the like will tell you they are recession-proof. They say people who have beaten cancer are likely to see it return, so say their statistics. People with broken bones are likely to break more or have new things happen to them. The hospital is somewhere you will be back to, and when you come back, they’ll heal you up and wait until your next sickness.

But that’s not how we see ourselves or our wellness. We see our lives as linear, and illness is a temporary detour on our path. We want a hospital to send us back on our way down the path we see, that the yellow line doesn’t run right back into the red but instead hops right around it and goes on.

Now, this is really picking something apart and I could quite frankly be seeing this logo in a different way than its creators did, but I don’t think it’s a stretch. If you simply put arrowheads on each of these colored segments, it would be startling.

This hospital knows the truth the statistics tell. Often, analysts do exactly the same with their clients and brands. Is this how you think of your customers, too? Do you look at reports, trends, create models, and predict their behavior? Do they know you think about them this way (it’s probably a lot more obvious than you think)? Is your site, your marketing, your social messaging built around your view, rather than your customers’ needs? If you think that doesn’t affect your brand or your bottom line, you’ve officially misplaced your marbles. Yes, it’s good to understand your audience, but don’t lose sight of them as people, especially when they see the world differently than you do.

This is why we start with seeing clients’ industries and businesses from their customers’ perspective. How a brand communicates about itself and its philosophies through logos is one thing. What we see as analysts and digital marketers is no different: how a brand communicates itself through marketing messaging, landing pages that stick users in a hallway with no exits (except the back button to Google), pricing schemes that are intentionally confusing and intimidating, pushy vendor salespeople and web sites selling movie sets when customers think they’re buying real buildings.

I don’t believe these things businesses do are medium and long-term winning strategies, even if the multivariate test last week said they are short term gains. Be smarter than that. Your risk isn’t a foregone opportunity to increase conversion rate. Your risk is a newer, consumer-centric competitor doing it a better way, swooping in and taking your whole kingdom away while your ex-customers rejoice in leaving you behind.

When we did the logo design for Satellite (and made the tool, itself), we wanted people to see speed, motion, the future, clean thinking. Our competitors put images of tags and HTML characters in their logos. We think you want speed and elegance, not tags and markup. If you could forget about tags completely, wouldn’t that be a good thing? We think so, too, and we don’t want to have to redesign our logo once you get there.

How are you seeing the world? Through your business’s eyes, or your customers’? Give the other side a try, if you haven’t already. What do your customers and clients want from you? My guess is if you give it to them, things will go very well.


Don’t be foolish. Come to DAA Atlanta.

On May 17th, an incredible brain trust is descending on W Midtown Atlanta to discuss analytics and the future of our industry.

THIS IS A CALL TO ACTION, Click here to register!
(I am showing off my usability expertise here).

About the event

Speakers include:

  • Joe Megibow, Expedia
  • Bob Page, eBay
  • Matt FREAKING Gellis, Keystone
  • Peeps from Coke, Delta, UPS, Turner

And you will have the tremendous honor (although some may call it pain) of sitting through me moderating a panel of non-analysts talking about how analysts can help organizations drive greater success. You’ll hear from perspectives we don’t often get exposure to in our own industry events (leaders in SEO, Product Mangagement, Social, Mobile). I’m VERY excited about this panel because if we want to successfully “plug in” to other departments and other specialists, help organizations balance competing priorities, and more effectively share our insights with the people who have rubber on the road, it’s imperative that we understand their perspectives, not just our own.

So, sign up now. May 17th is my anniversary. I am literally risking my marriage to be at this conference. What’s your excuse?


And now, click on these facetweet buttons to pin the social foursquare on your myspace geocity. Do it.

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