How To Come Up With Questions To Ask Web Analytics Data

It’s said that the successful use of web analytics requires asking the data the right questions. So where do you get the right questions to ask? Some questions start with data and some questions end with data.

Recognizing a trend or change in the data can lead to a good question. This requires creating key performance indicators and watching them as time goes on. You may notice that the amount of purchases that include a sale item is increasing year over year and you want to answer the question as to why – which may lead to an insight that then leads to a change in how your marketing dollars are being spent, how product is merchandised or a page is displayed.

Or a question might first come from outside of the data. Looking at a competitor’s site causes you to wonder what it would be like to do what they are doing. Or something bothers you about the old looking design of your product detail page and you wonder what would happen if you changed it. Those questions then lead you to look at data to validate your questions.

A healthy combination of both approaches – watching your data for trends and watching the competitive landscape for trends, can and should be employed to get the most out of web analytics to improve your online business.

Content Marketing Quality Versus Quantity

You want to create some content (videos, info-graphics, blog posts, podcasts, social posts & tweets, etc.) in hopes that it will drive traffic, improve search rankings, give utility to your brand in the mind of the customer and sell stuff. But you have a limited budget. You had to decide between a little content that has a lot of polish and high production costs versus more content but lower quality.

I say go for quantity over quality every time.

The first reason to put quantity over quality is that there’s no correlation between how much something cost to make and how interesting it is. A hundred million dollar movie can bomb and a video made for free can go viral.

You’re also competing with 300 hours of video uploaded to YouTube every minute, 2 million blog posts published a day and more than 3 billion Facebook posts a week. In other words, there is a lot of other content vying for attention. The more content you can make with unique titles, different perspectives and varied angles the better chances you have at finding the people looking for the content you make.

So, if there’s so much competition and money isn’t related to interestingness, why do brands choose quality over quantity nearly every time? Over-the-top production values are a place to hide. It’s easy to cover up boring with something pretty, but it rarely works.

Unintended Consequences Of Key Performance Indicators

Narrowly focusing on key performance indicators can have unintended consequences,
optimizing for the wrong things at the expense of something else.

For nearly every metric that an organization can focus on with web analytics, there is potential for backfire. Here are a few:

Engagement is a buzzword these days that refers to making an experience “sticky”, or that the user finds content so compelling that they develop a stronger relationship with a brand. Metrics like average time on site and page views per visit are often used to measure engagement but these metrics can be wrongly translated as frustrated visitors who can’t find what they are looking for.

Increasing visits to a site can’t be wrong can it? Not unless in an effort to reach a certain level of visits you engage in spammy tactics like click-bait headlines or spend lots of marketing dollars that in the end produces lots of unqualified traffic. Why praise increased visits if none of it takes the actions on the site that make you any money?

Measuring your advertisements reach refers to how many people are seeing the ad. The more the better is not necessarily true. In the age of precise targeting online, who sees your ad is more rewarding than how many.

Increased conversion rate is every site owner’s goal, but an unhealthy obsession can lead to marketing that only targets people who are the most likely to buy, and the most likely to buy are those people who are already familiar with your brand. Left unchecked, you never gain new customers as your marketing preaches only to the converted.

A high bounce rate is never good but continually changing content to decrease bounce rate can turn into an inverted curve – bad to better to bad again. Content goes from irrelevant to more generally applicable to banal and watered down.

Increasing revenue at all costs is the most obvious short-sighted metric and the result is what you see in many failed business: lower quality, less return customers, decreased goodwill, lower customer satisfaction, decrease in perceived brand value, the list goes on.

Finding The Real Source Of Website Traffic

With web analytics you can see sources of traffic via your traffic sources report, but it’s not really the sources of traffic.

With this report you can see the different sources of traffic like search, direct, email, etc. and their associated metrics like revenue, visits and conversion rate. This is beneficial to be able to optimize spend so that more money goes towards sources of traffic that have the best return. But there is an inherent limitation here that is often overlooked: the reason behind the user’s decision to access the site.

You know that a user came from paid search, but why did they decide to buy something to begin with? Did the product they were using wear out and they need a new one? Did a new life event happen that required them to make the purchase? Did they decide to buy after seeing the product used by a friend?

I think it’s important to remember that the ultimate motivation behind the user’s decision to come to the site is unknowable. Data from traffic sources is a blunt instrument at best to figure out how you can generate more sales. Directionally, it’s beneficial to invest marketing dollars to the extent that return on ad spend is efficient at the highest volume possible.  But don’t be deceived because you can (sometimes) see what keyword they used in a search engine, what device they used, what the email offer was, the coupon code used, the product they purchased, ect.; trying to replicate winning scenarios doesn’t always return like a math problem does.

Online marketing is still marketing, not a math problem that can be solved if you could ‘figure out the data’. Customers are irrational and make purchase decisions based on reasons that web analytics data can’t explain. You can see what happened and as a result improve the site’s usability and marketing investment, but trying to increase why people buy is not as easy as web analytics makes it seem.

Zach’s Best Of 2014

Best Movies/TV:
(This year I watched 103 movies, a 17% increase over last year & 123 episodes of TV, a 43% decrease over last year)
Grand Piano
Cuban Fury
Edge Of Tomorrow
Lego Movie
True Detective Season 1
Silicon Valley Season 1
Newsroom Season 3

Best Books:
(I read 40 books in 2014, a 14% increase over last year)
Down There by David Goodis
Clockers by Richard Price
Gone Girl by Gillian Flynn
The Fifteen Lives Of Harry August by Claire North
Altered Carbon by Richard Morgan

2014 Best Music Playlist:
Mariachi El Bronx – Everything Twice
Swingin’ Utters – Fistful of Hollow
Chris Staples – Dark Side of the Moon
Lagwagon – The Cog in the Machine
Rancid – Back Where I Belong
Tweedy – Low Key
The Copyrights – Slider
Reaganomics – Bite Your Tongue
Jake Bugg – Lightning Bolt
Masked Intruder – Saturday Night Alone
Cheap Girls – Slow Nod
The Menzingers – In Remission
toyGuitar – Words Between Us
The Thermals – You Will Be Free
The Methadones – Murmurs in the Dark

Most Exciting – Publishing my first book, This Side of the Dirt

Proudest Parent Moment – Training wheels came off my daughter’s bike

Proudest Husband Moment – Seeing my wife crush it as a realtor

Most Painful – Sliding across a hardwood floor in socks getting a huge sliver jammed deep into my foot

Happiest – Adopting my son

Scariest – Hiking over Pawnee Pass in Indian Peaks Wilderness at 12,500 feet in a storm

The Future Is Now Moment – Streaming movies uploaded to Google Drive to my home theater using Chromecast and the LocalCast App

Most Exhausting – Buying a house and remodeling it

Most Stressful – Travelling to California with three kids, three car seats, two strollers and 5 bags

Most Fun – Playing on the beach in California with my kids

Most Sad – Four chickens dead from raccoon attacks

Most Annoying – Stupid mice traps don’t do crap to catch mice in my house
Runner up – Missing turn on road trip that cost me an extra three hours in the car

Best Purchase – Presto PowerPop microwave popcorn popper
Runner Up – Teach Me Time! Kids Alarm Clock (if your kid constantly wakes up too early you can train them to sleep in with this (most of the time))
2nd Runner Up – Shorai Lithium Iron Motorcycle Battery

Adobe Analytics: Hierarchies vs Site Sections

On the surface in Adobe Analytics, the hierarchy variable and capturing site sections with channel and traffic variables seem to accomplish the same thing, so why do both? It’s smart to do both because the reports look very different to the analyst and can help them achieve different goals.

First of all, the hierarchy variable (“s.hier1=”) records site structure and is used to determine the location of a page in your site’s hierarchical page structure. It allows the analyst to start from the top of the site’s hierarchy and drill down through it. Once you start drilling down, you can’t see other groupings of pages at that same level outside of the hierarchical chain.

Site Sections are very horizontal in nature. They show you metrics for groupings of pages at a particular level across your entire site. The channel variable (“”) is used to identify a section of your site. When sections have one or more levels of subsections, you can use additional Custom Traffic Variables (“s.prop=”) to identify such levels.

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You could opt for only implementing the Site Sections via s.props and then correlate the different levels using the correlation function to drill down between levels. The only drawback is that the Page View metric is only available when breaking one Traffic Report down by another. If you wish to see Visits and Unique Visitor metrics at each level, use the Hierarchy variable.

Beware Of Filler

Studies show that people serve themselves in proportion to the size plate that they have been given. As a result, a person tends to over serve on larger plates. So, use a smaller plate and there’s less space to fill, and less food will be consumed.

Increasing lanes on the highway does not decrease traffic. The answer as to why is found in “the fundamental law of road congestion: new roads create new drivers, resulting in the intensity of traffic staying the same. If you expand people’s ability to travel, they will do it more. Making driving easier means that people take more trips in the car than they otherwise would.

The cable news station has twenty-four hours of airtime to fill, but important stuff doesn’t happen every single hour of every single day which leaves cable news with the problem of filling all that air time. So what they came up with to fill all that air has been celebrity gossip, wild conjecture and sensationalized drivel.

It is well known that meetings kill productivity in the office. A common suggestion to improve productivity is to not schedule meetings to the default hour time length. Why? Allotting an entire hour for a meeting may lead your attendees to fill the entire time slot just for the sake of it.

You see where I’m going with this. Whether it’s over-consuming calories, unnecessary travel, useless information or wasted time, there is a problem with assigning time/space first and needs second. Turn that around and analyze what the need is first and then assign the correct amount of time and you will end up with no filler needed.

One of the biggest offenders of the time/need scenario is the modern-day office. I am convinced that there is no place on earth that creates more useless filler than the office. Because the employee is required to be in their seat for 40 hours a week, work is created to fill the time that does little to nothing to move the ball down the field. Our culture of busyness does nothing but reinforce the problem. Being busy equals being productive which equals being a good employee. No one wants to look like they don’t have enough to do so productivity theater ensues.

Carefully consider looking at your behavior through the lens of filler/not filler and reduce the filler. Be careful to accurately align your time spent with the time the thing deserves.

Purchasing Channel Versus Decision Making Channel

94% of retail sales are still generated at brick and mortar stores. This stat is usually referenced to defend traditional retail when people see Amazon increasing their revenue from 2009 to 2013 by $50 billion, and state that the death of the traditional retail store is a foregone conclusion. The big effect that the internet makes on shoppers is not on their purchasing channel, it’s where they make their purchasing decisions that has changed.

This is why most consumers know what they want before they show up at the store. The reaction between stimulus and purchase is not going to the store, but the customer accessing the internet with questions like “how do I keep diapers from leaking through the night?”, “what kind of jeans is Beyonce wearing” and “what will remove crayon marks from my wood dining table?”  Even if TV advertising is the stimuli, the internet intercepts the purchase funnel at some point.

You wouldn’t think this insight has been made if you were to review most multi-channel retailer’s today. Online marketing efforts are still overwhelmingly focused on driving sales online. A big part of the problem is calculating how much revenue is driven offline from online advertising. Since online advertising’s effect on online sales is easier to measure, it has a bigger budget.

There is a change coming to the marketing departments of multi-channel retailers and that is, all advertising for retail stores will soon be online (the day is coming when TV and the internet are one in the same, and those ads will be scrutinized with the same criteria as online ads). Regardless of which channel the customer chooses to purchase from it will all be from digital advertising.

How Much Longer Do We Have To Tolerate Mobile Apps?


I dislike the whole premise of mobile apps. Why can’t I just use the internet on my phone? Why all of this app account logging in, downloading, updating nonsense? I have to believe that mobile apps will go extinct in the future.

The only reason the idea of downloading applications on a mobile phone made any sense to begin with was because mobile devices and wireless carriers couldn’t handle internet at the speeds needed to make anything useful. Once the internet is faster on phones and I can get the same experience online as on an app then what’s the point of having apps?

Nobody downloads apps on their desktop computer because they can just use the internet. And the internet is a far superior experience than using apps. Think of all the easy things you can do online that suck on apps: linking between sites, buying stuff, and updating a webpage requires nothing from the user.

Apps are particularly challenging for ecommerce sites. You already have people navigating to your mobile site, why build something outside of your site where all your traffic is already going? Once you build an app then you have to advertise to get customers to download it and then find a way to get them to use it.

Apps also give centralized control to Apple and Google over what apps can exist and which apps get downloaded the most. Unless you know what you want, at both app stores you are shown leaderboards to pick from. Search is a horrible experience. Discovery is worse. A decentralized system, like the internet, offers much more opportunity to start ups and diversity to consumers.

Apps suck.


Stop Telling Stories With Data

There are so many variables when it comes to ecommerce that I’m convinced that the idea of knowing why visitors do what they do is not really possible. All you can know is the results, not the why.

But not knowing why doesn’t sit well with our human brains. We yearn for patterns, explanations and stories to explain why what is happening is happening. Not knowing why also makes it difficult to get buy-in from others. If you’re trying to convince a manager to make a choice based on your data, you can be much more convincing with a story coupled with data, instead of just the data itself. Storytelling is a powerful tool, but if taken too far it can quickly go from presenting what happened to pushing an agenda.

The problem with creating stories with data that reach too far is called the narrative fallacy, made popular by Nassim Talbm in his book The Black Swan:

“The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship upon them. Explanations bind facts together. They make them all the more easily remembered; they help them make more sense. Where this propensity can go wrong is when it makes us think we understand it more than we really do and as a result, become more confident in a story that isn’t true.“

When you think you understand what the visitors on your site are doing more than you really do, you may start to let the data take a back seat going forward, and fall into the trap of confirmation bias where you start paying attention only to information that confirms your story while ignoring information that challenges your preconceived notions.

Somanyblogs are promoting the idea of telling stories with data without a bit of warning on the dangers of that approach. The world is a very com­plex place, and there is almost never a sim­ple  answer or a sim­ple series of events to explain any action. In the end we don’t actu­ally need sto­ries to make deci­sions. Stop pushing agendas and get over who gets to take credit (I don’t think it’s a coincidence that the ones most interested in story telling  are the same insufferable people who want to put off doing anything until after a meeting is held about it).
To make a deci­sion, you sim­ply need the abil­ity to com­pare num­bers and choose the best one. I don’t need to know why vari­ant C was bet­ter than B, I sim­ply need to know that it was 10% bet­ter and then I can take that insight, apply the change and move forward.