Upcoming LunaMetrics Seminars
New York City, Aug 4-8 San Francisco, Aug 11-15 Los Angeles - Anaheim, Sep 8-12 Washington DC, Sep 22-26

Archive for the ‘Analytics’ Category

Segmenting Google Analytics by Session Frequency

Segmenting-Sessions

Segments are one of the most powerful features of Google Analytics, and they are often useful for zeroing in on the sets of users who are most valuable to us.

One way of looking at potentially valuable users is to look at the frequency with which they visit the website. Let’s look at a couple of ways to do that in GA.

(more…)

Data Processing Options for Google Analytics and Big Query Export

data-processing-blog

In this blog post, I evaluate several of the numerous (and potentially overwhelming) options for the processing and reporting of Google Analytics data. The default  Google Analytics web interface is great for quick ad hoc data exploration, but limited for deeper analysis and the development of automated reports.

Whether we’re mining for hidden trends or trying to report on hard-to-extract dimensions, there are a number of third-party tools out there can that help ease the burden.

In the first half of this article, I explain the difference between the two types of Google Analytics data: what’s available from the standard interface and what’s available through the BigQuery export.

The second half of this article is an evaluation of three different solutions for processing, visualizing, and reporting on Google Analytics/GA BigQuery data. I evaluate these three solutions (ShufflePoint, Tableau, and R) based on objective features and my subjective scoring of performance.

I only evaluate three data processing solutions in this article. Think I missed a good one? Let me know!! We all have a different background in data analysis tools, and I would love this conversation to continue in the comments section.
(more…)

Dynamic Data Viz: A Better Way to Plot Rows in Google Analytics

Have you ever tried to use the “plot rows” feature in Google Analytics and it literally falls flat?

It happens because you can’t keep the chart from graphing the metric total. That thick blue line across the top of your chart flattens everything else. It keeps the size of the chart static, rendering it useless.
Drink me potion and key on table next to miniature door

Wouldn’t it be great if you could graph only the rows you want and the chart would dynamically resize?

Here’s the key to turning those flat, plotted rows into dynamic data visualizations: motion charts. (more…)

How a Local Business in Seattle Can Gain Street Level Insight in Google Analytics

Street-level

Did you ever want micro-level geographic information inside Google Analytics? What if you really need “street level” knowledge about your users; like where are they, what neighborhood are they in? Often, when we talk and write about Google Analytics we’re thinking about the big guys. National or even International traffic, filtering by country, comparing one region to another. We’re thinking macro, not micro.

I wrote previously comparing DMA areas to gain insight, but that’s really only helpful if you have a true national or bigger presence. What if you’re just a local Seattle business, and don’t really have much call for looking at traffic outside the Seattle-Tacoma metro area?

Well, first thing you should do is think about taking our Seattle Google Analytics, AdWords, and Tag Manager Training (shameless plug). Second, read on…

Seattle is actually ahead of the game when it comes to data, which is the real reason I’m using them as an example. The city has a Chief Technology Officer, and data.seattle.gov was started in 2010 as a central hub for all local Seattle data. In fact, a number of businesses claimed that the use of this local data helped them with their businesses.

How so? Well, if you’re a local business then the traffic from, and information about, the Queen Anne neighborhood of Seattle might be more important to you than Downtown or Riverview.

But how can you use Google Analytics to help you on this sort of granular level? Also what if you DO care about national level data, but you care about it on a very granular local level as well, maybe looking for interest in your brand to help place billboards, or expand your franchising? The truth is that you can’t, at least not right out of the box. But with a few very easy additions, you can start getting some great local data that can let you make street level decisions about your business in Google Analytics. (more…)

Duplicate Transactions in Google Analytics – The Check and the Fix

duplicate-trans-big

By far the most common issue I’ve come across with ecommerce sites; duplicate transactions can inflate revenue and ecommerce metrics, altering your attribution reports and making you question your data integrity.

When talking about where to put the ecommerce tracking code, Google suggests the following for Universal Analytics:

… If successful, the server redirects the user to a “Thank You” or receipt page with transaction details and a receipt of the purchase. You can use the analytics.js library to send the ecommerce data from the “Thank You” page to Google Analytics.”

The missing step here is to ensure that either A) the user cannot access the page more than once or B) you have logic in place to make sure the transaction is only sent once. The biggest issues I’ve seen are when this receipt page is automatically emailed to the customer, with the ability for them to return as frequently as they please, each time sending a duplicate transaction.
(more…)

The Only* Statistical Significance Test You Need

You’ve heard the term “statistical significance”. But what does it really mean? I’m going to try to explain it as clearly and plainly as possible.

Suppose you run two different versions of an ad, and you want to know if the click-through rate was different (or you are comparing two different landing pages on bounce rate, or two campaigns on conversion rate). Ad A has a click-through rate of 1.1%, Ad B is 1.3%. Which one is better?

Seems like an easy answer: 1.3% > 1.1%, so Ad B is better, right? Well, not necessarily.

Consider a quarter

file7161235071306Suppose you have a quarter (and it’s a fair quarter, no tricks). The rate of getting heads when you flip should be 50%, right? If you flipped the coin an infinite number of times, you could expect it to come out heads half the time. Unfortunately in web analytics, we don’t have time to flip the quarter an infinite number of times. So maybe we only flip it 1000 times, and we get 505 heads and 495 tails. Do we conclude that heads are more likely than tails? What if we only flip it 100 times, or 10?

You can see that sometimes, the difference we measure is merely due to chance, not to a real difference.

(more…)

Google Analytics Data Mining with Big Query and R

Big Query and Big Query Export for Google Analytics give us the power to visualize and explore virtually any trend in our GA data. It’s really quite powerful stuff. Because this tool is still very new, I want to get the conversation started on how advanced reporting can augment our digital analytics.

In this post I discuss data mining and the advanced reporting of Google Analytics data. I provide an R script for generating an E-commerce report with visualizations that are not possible within Google Analytics.

(more…)

Are You Missing Referral Traffic in Universal Analytics?

Don’t fall for that old Jedi mind trick and simply ignore what Universal Analytics tells you to ignore… they might be the referrals you are looking for.

fooling the troopers with an old mind trick

Did you know that Universal Analytics’ default setting is not to count referrals from your domain? That’s right, Universal Analytics is going to ignore self-referrals by default. This may not be a good thing if you need the information to fix coding errors, but that’s another story.

Today’s story is how to make sure that your idea of self-referrals matches what Universal Analytics is calling a self-referral. If it doesn’t, you may be ignoring some referrals that you didn’t want to ignore. Depending on your situation, you may need to change a setting or even add some custom code to see all the referrals you want.

Read more to understand what’s really going on with referrals in Universal Analytics so you can make an informed decision about what to ignore.

(more…)

Using Google Alerts and Google Analytics for Online Reputation Management

What is Online Reputation Management?

Online Reputation Management

“Online Reputation Management”, or ORM, can be thought of simply as SEO combined with online public relations and social monitoring – how you or your brand is perceived online. How can you know what your online reputation is? Is it possible to measure if your reputation is affecting revenue? Since search optimization plays a huge role in a brand’s reputation, the two are often connected. However in addition to a strong SEO effort, there are several methods to manage your online reputation.

Many software-as-a-service solutions monitor conversation online – from free widgets to enterprise-level applications. These SaaS platforms are great for in-house customer service outreach and monitoring conversations on Twitter and some public Facebook pages. However a major investment may not be not worth it if you are looking for clean, reliable, consistent data.

Facebook, other social networks, forums, news and aggregator sites have changing privacy settings, nofollows and robots.txt to prevent site crawling which can block ORM monitoring software from finding keywords. Again, these providers may prove useful for other purposes, but I believe there is no catch-all ORM tool currently. The good news is that you can use free tools like Google Alerts and Google Analytics to begin to understand and measure your online reputation.

(more…)

Campaign Tracking with a Dynamic Source

Where-do-you-come-fromDo you want to track your press releases or distributed content (widgets, infographics, embedded content, etc.)? I’m going to show you a much better way to do that with campaign tracking in Google Analytics.

I was recently asked a question by an attendee to our Google Analytics training in Los Angeles about using campaign tracking in Google Analytics:

We distribute press releases that get distributed and posted on various websites.  I want to be able to track any traffic generated by those pickups as part of a campaign, but also know from which sites the traffic is coming.  What happens is I simply leave utm_source out?

(more…)