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).

Bar-guments

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.

OH SNAP.

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

Yep, none of that. DOUBLE I’M ON MAURY POVICH AND YOU AIN’T THE FATHER SNAP.

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, he 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 his 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 (see Optimizely).

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?

ANOTHER CALL TO ACTION. CLICK HERE TO REGISTER NOW!

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


Is ROI the analyst’s greatest frienemy?

In the world of marketing and business, it’s all about ROI, right?

Well, not if you want to understand what is happening and what you can do about it.

Extremes are our enemy. Typically, we get tangled in the extreme of over-complication. We want to run statistical analyses, regressions, econometric models, and the like on our data, even sometimes on relatively simple data sets. This is when we alienate our audience by trying to look super smart rather than keeping the story simple and digestible. When we involve all of this mathematical alchemy, we can lose touch with the underlying business questions and get lost in the numbers, muddying the message.

On the other hand, overly-simple is equally a pitfall. That overly simple view typically boils down to the viewpoint that everything has to have a demonstrable ROI. And that, as they say, is poppycock.

I can’t prove this, but I think that on any given day, the vast majority of your “customers” (visitors on your site, people on your Facebook page, etc.) are in the high-funnel. Maybe not even in the funnel at all. They are just beginning their search for a washing machine. Just researching what replacing their old digital camera will get them in terms of picture quality.

In our media mix, we have keywords, emails, social engagement, display creative and more targeted to the high-funnel. Remarketing campaigns have the sole purpose of bringing customers back after an “unsuccessful” visit. Keywords like “best digital cameras” drive consumers to commerce sites, when the consumer is almost certainly looking for content to help them narrow the field and is not yet a buyer.

And what do businesses do? They measure it all to ROI. Spend vs. return. They see everything through the lens of our business, rather than through the lens of the consumer. And that’s really just not the best approach when you want to understand what will lead to greater financial success in the future. This view just doesn’t give you enough detail into why things are working or not working or what you can do about it.

A consumer’s interaction with our business is a chain of micro events that hopefully leads to macro outcome in terms of a sale, a subscription, a lead, etc. It’s in these micro events that our business “leaks” customers. And the only way to see this leak clearly is to zoom in to each element and measure the business’s success at that level.

I think that luxury hotels offer a great metaphor for how this works. Luxury hotels want your loyalty. And the way they earn it is not a single coup de grace, it’s a sequence of tiny little events that all go perfectly.

When you arrive at the Four Seasons, for example, the valet will open your door and ask you if you are checking in (unless they recognize you, in which case they will welcome you back). When you give him your name, the valet will wait for you to turn around, immediately radioing to the front desk where they will look you up to see if you are a repeat customer. The desk then immediately radios back to the valet and doorman. By this time, you’re at the doorman who is swinging the door open. He says, “Welcome back, Mr. Smith.”

Wow.

Throughout your stay, you notice everything. The flowers in the lobby. They politeness of the front desk clerk. The professionalism of the bellman as he asks if you’d like your hanging clothes to be put into the closet for you. You notice every aspect of the room: its cleanliness, the smell, whether the clock on the bedside table is correct.

When you come back out into the hallway to head out for the afternoon, employees you see in the hallway step aside to let you walk by. They push carts out of your way and everyone greets you and wishes you a good day. On the way out the door, they will hand you an umbrella if rain is in the forecast and may offer you a bottle of water and directions, if you need them.

And this goes on and on throughout your stay.

Now, here is the thing. Each of these actions has an ROI, it’s true. But each of these things is partially or completely dependent on all of the others. The ROI of the doorman can’t be localized to the doorman. If the room smells funny, your entire experience could be marred. Your opinion of everything else changes because of one “leak” in their system.

With your web site, your social media, your marketing channels, etc., it is no different. The ROI of your marketing channel is completely dependent on your landing pages, your product detail pages, your cart, your checkout process, everything. Yet we measure this channel to an ROI. And going even a step farther, we measure even the high-funnel segment of this channel to ROI as well. These being people who are not there to convert; they are there for a different micro case you could measure and optimize against.

The only way to be an effective analyst is to intimately understand the role of each of your micro-events and find opportunities to improve. Almost zero A/B or multivariate tests should have sales, revenue, or leads as the goal or measure. There is simply too much in-between — this is not to say don’t look at it, just realize that any single interface is rarely intrinsically tied to the end-game. You need to look at the pieces themselves. Make each piece serve its function perfectly. As you eliminate leaks on the micro level, the macro level will take care of itself. Faith-based initiative? Sure. What isn’t?

I know that the culture of ROI exists in most companies and your colleagues aren’t going to want to talk about sissy pants micro conversions. But that’s where the magic is. Your customer reacts to every little thing presented in your marketing, your architecture, your interfaces, etc. Consciously or not, your customers judge you and interact with you by the micro. So if you want to keep more customers and make your existing customers more valuable, judge yourself like they judge you.


6 keys to a killer career in web analytics

Every day, I become less of a dumbass, usually as a result of reflecting on what happens when I am one. Here are a few lessons I have learned that may be helpful to you, whether you are just getting started or if you’ve been doing this for a while. I hope you’ll add your own lessons to the comments.

So, here are 6 lessons I feel, if I had learned earlier, would have really helped me out.

1. Learn the tool(s).

Duh.

Get training. For Omniture, you can’t do better than Keystone Solutions. For Google Analytics, you can talk to us, or any GACP. Learn the way the tool is laid out, how to use its advanced features, how to get lost going down a rabbit hole but still know what you are doing.

And then this (warning, you might not like this): take 2 vacation days and spend it getting completely lost in the tool. Click on surprising data to see why it’s doing what it’s doing. Click on unsurprising data to gain an appreciation for the surprises that probably lurk underneath. The vacation days will allow you to get away from everyone else, get away from specific requests, and focus on getting lost in the data and the tool’s capabilities. You aren’t going to break it. Learn all of the nooks and crannies. Click on everything you can possibly click on (maybe not in the admin side of the tool, watch your clicks in there). Make a list of questions, and get them answered by someone who really knows their stuff.

Finally, learn more than just the basics of implementation. This will do two things. First, it’ll help you understand how the data is gathered and why you might see odd things happening. Second, it’ll help you understand the pain involved in implementing and how “something simple” really isn’t. Use this understanding to build a relationship with your IT team, or even better, justify a tag management system (Satellite, Ensighten, Tagman, Brighttag) that will get you focused on using the data, not getting it. Focusing your time on getting data is not a good thing.*

* Don’t give me the argument that without getting data, there is no data to analyze. Without celery, there is no ants on a log. Without rain, there is no celery. Without evaporation, there is no rain. Without glaciers and the ocean, there is nothing to evaporate. Without hydrogen, there are no glaciers. Without the big bang, there is no hydrogen. Give me a freaking break. Which brings me to #2:

2. Focus on the output

Particularly, when presenting. Know your audience and deliver first, before anything else, a message that gets their attention. Your process is your content. Your conclusion is your headline.

Maybe conclusion is a crappy word, since it’s usually something you figure out a the end. But rather than making your presentation a playback of the process you went through, reverse the order and start with what you found out at the end. Usually, this is just the “hook” that you need to get everyone’s attention, get them asking questions, and help them arrive at the same conclusion you did.

I’ve found that when I start by walking through my process, the audience knows they are in for a long, boring meeting where I don’t get to the point for quite a while.

3. Focus on YOU

YOU can answer questions. YOU can get information and numbers. YOU can tell executives what people think about the web site. Not tools.

Yes, the tools provide this information, but YOU put it into terms (a la “focus on the output”) that the business can consume. SiteCatalyst was not custom-built for Best Buy. OpinionLab is not only installed on Williams-Sonoma. These tools have to be built to handle any web site and every business model. It is you who is valuable; you are the one who adds context and a sense of reality and applicability to the data.

Without tools, you can’t answer questions. But with tools, it doesn’t mean you can answer questions effectively.

How many people saw Tiger Woods crush the competition at the Masters and then went out and bought the clubs he used to win? Did those clubs work for these people? People think they can buy a better game. They think the tools will get them on the podium. Unfortunately, my golf game proves without fail that this is not the case.

Try to get people to ask you the question, not ask you to get data. If they do ask you for data, show them what they asked for behind a page that you put together. Try to illustrate on that page why the request for the data could have led them to the wrong conclusion (if that’s true) or didn’t tell the whole story. You don’t have to do it in an overt way, just show that the human is where the value comes from, not the tool.

Once you realize that you are the bomb, it’s time to…

4. Focus on THEM

When you are delivering your powerful message and wrapping that in your own brilliance, remember that even if your conclusion is the same, you will see that people from different departments will grapple with your ideas in radically different ways. The same sentence read by or spoken to a CEO, a CFO, a CMO, a Paid Search Manager, and a Usability Engineer may mean different things. Some may feel the message helps them. Others may feel threatened by it. Some may see savings and cost reduction while others see upside. Some will see increased productivity while others will see their fiefdom shrinking.

I have made huge mistakes in my work by throwing an “unframed” idea out to a mixed group of stakeholders or by framing it the same way to all stakeholders. Huge mistakes.

By learning what goals and motivations each of the players has, you can show each player how an idea benefits them. If it doesn’t benefit them directly, you can help them understand how it benefits others in such a way that it may warrant sacrifice (which may be repaid in the future). You will also understand their goals and motivations for the future, allowing you to be on the lookout for ideas that do benefit them, which will build a tremendously successful relationship.

If you see salespeople or other charismatic people who are seemingly able to do this on the fly, don’t despair. There is no gene for this: these people spend a lot more time than they let on trying to see things from other peoples’ perspectives. Charismatic people work hard to understand others’ wants and needs so they come into these meetings prepared to speak in a way they know will be successful. By giving others’ perspectives some forethought, you literally stack the deck in your favor, but it does take conscious effort.

5. Be the closest thing to a graphic designer possible

If a picture is worth a thousand words, why do so many people just say, “wow…,” when you put something truly amazing in front of them?

Some of my most successful presentations had just a single chart on the first slide. I make an introduction, and say, “Here is what we need to figure out today…,” change to this slide, and just watch the faces in the room.

A book written by the company that helped Al Gore design his famous “Inconvenient Truth” presentation shows a chart of two different kinds of companies. One line (red) shows the market cap of companies who have design deeply-ingrained into their company and culture. The other, blue line shows the rest of the companies in that exchange (a UK exchange). Over a period of about 7 years, the companies who had design at their core had grown by a factor of 2x compared to the companies that did not.

wow…

When you are able to convey ideas clearly, your customers know what your product is, what it does, how it works. When you can convey your thoughts clearly, and this usually happens graphically, people “get it” instantly. They want to know more. And they trust that when they ask questions, those questions, too, will be answered in a clear way.

Looking at companies and people who do not communicate through effective design, on the other hand, you may feel that interactions with these people are cumbersome and unproductive, that your questions are answered in round-about or indirect ways, and you are generally less-likely to interact with someone or see their value clearly.

Personally, I’m about as good of a graphic designer as Hellen Keller. But I try as hard as possible. I try to strip things down to their most basic elements, show them to people, get feedback. I try to be a student of effective communication. I can assure you it is a skill that can be improved.

6. Focus on reaction, not perfection

If you could answer a question 10 times (instead of just once) on Jeopardy, what would be your strategy? If it was me, I would answer as quickly as humanly possible with a semi-educated guess. What if Alex told you if you were getting “warmer” or “colder” with each answer? Yeah, I’d be jumping all over that buzzer to ring in.

Online, this is exactly how it works. Yet we are obsessed with trying to answer the question “right” the first time. We believe that analytics is a practice designed to help us make better decisions. I disagree.

I think that digital analytics is best used to help us make more decisions, more quickly. I would just about wager my life that if I can make 5 decisions in the time it takes you to make 1, I will get a better net result almost every time. This is the premise of A/B and multivariate testing, but even with tests, people criticize the “loss” in the test variants that fail to find upside or in a test where all variants produce inferior results.

“Getting colder” is the same as “getting warmer.” Remember that.

When we use analytics to make better decisions, it’s like when a shop owner tries to learn everything he possibly can about how to organize his shop, stock his shelves, hire help, and get it all just right for opening day. Imagine the OCD shopkeeper who delays his store opening for a month because he keeps getting little bits of information, reading just a few more articles in hopes he’ll get it just right on opening day.

Then the store opens.

Which period of time do you think taught him more about his customers and how to run his store? The months before opening, or the hours after?

When we use analytics to “open the shop early” and get ideas out into the real world, we can learn quickly and react. In the time it would have taken us to learn what should work, we can learn 5 times what does work.

There are exceptions, but to me, this is the rule.

See the light

What is the eventuality of your career? Where is this taking you? In 10 years, when someone else is putting the reports together, delivering the types of presentations you are delivering today, where will you be?

I don’t know the answer to this question. Not by a long shot. But my gut tells me that what we are doing today will train us for some pretty impressive roles in the future. And if that is the case, my gut tells me that these roles will get farther away from the kinds of metrics we work with today and closer to the kinds of metrics and questions that Wall Street works with every day: How efficient is your company? How is it growing? What is the promise intrinsic in the business’s plans for the future? What evidence is there that new business opportunities will pan out?

Those are things we are probably pretty good at today, and will be incredibly good at farther down the road.

Your turn

This has just been my experience and a few things I feel help me. But what about you? Share your thoughts in the comments.


Avoid Firing a Cannon from a Canoe (how to make your analytics count)

For my birthday, I gave myself the gift of re-reading Dale Carnegie’s great masterpiece How to Win Friends and Influence People. In the very first chapter, Dale was explaining the research behind the book: the polls they conducted, other published material they researched, people they interviewed, etc. They reached a conclusion that sort of blew my mind:

Less than 15% of what influences someone’s success in their career is their actual competence or skill in their craft. 85% of your success is determined by your ability to handle people and get them on board with your way of thinking.

This probably isn’t all that surprising. Looking at the most shining examples of success, people like Jeff Bezos, for example, we know for certain that his success doesn’t come from his unparalleled ability to ship packages, stock warehouses, build a web site, etc. And when we get out of the clouds of uber-success stories like Jeff and into more everyday situations, we may think the scenario changes, but it doesn’t.

So what’s with the cannon and the canoe? I was watching Mythbusters the other day and Grant had created this harpoon shooter that could shoot a 10 lb “anchor” 60 feet, or something bonkers like that. It used compressed gas at 3,000 psi to do this.

In their test run, Grant set up a mattress to catch the anchor, put the cannon on top of a tripod, pressed the fire button, and watched the tripod go flying backwards, crashing into the back wall of the warehouse with enough force to just about kill someone.

Whoops.

This episode reminded me of this “firing a cannon from a canoe” thing, and it all got me thinking about what we do. How we have this incredible, amazing power to effect change, but often struggle with making it happen. Perhaps it’s because we work so hard to become amazing at what we do, but that, unfortunately, may not be the place that needs the most focus.

Now among the community of brilliant people in our industry, I am yet to meet a person that I didn’t find convincing. When you work in our field, it’s hard not to be: you are highly intelligent people who have such great information. So, I think we are prepared to succeed at both the skill and the people side of things, it may just be a matter of how we apply these abilities, or a misunderstanding of what the people side really is.

Rather than pretending I am capable of helping 1% as much as this book, I’m just going to briefly summarize. Pick up a copy of the book and give it a read. You’ll see some things that are almost laughably simple, but work. Simple things like learning what other people are interested in, forging great relationships, building on success and learning, rather than focusing on failure. Ways we can create rapport and relationships that build a stronger base for our cannon, most importantly by not talking about the cannon at all.

The surprising thing is that the 85% isn’t our “delivery,” because the 85% has nothing to do with what we are going to talk about in the 15%. Our relationships with people are more human than that. Yes, a significant part of (and probably the impetus for) our relationships are professional in nature, but what Dale Carnegie writes about is world leaders talking about stamp collecting, boats, hunting, and other personal interests in order to lay the foundation for the professional discussion that follows. The 85% is truly a person-to-person connection, and once that is achieved, the potential for your talent to make a difference is amplified immeasurably.

Once that foundation has cemented, I’ve found that my cannon can actually do some real damage to inefficiency, poor execution, and misallocation of resources, rather than the ill fate I’ve suffered many times where I have just blasted myself farther away from my target.

Thoughts?