Archive for the ‘Google Analytics’ Category
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.
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…)
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…)
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.
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.
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.
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.
What is 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.
Do 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?
Want to segment your users by whether they live in a cool neighborhood in GA? We’ve got an API for that.
How Much Does Scrap Metal Cost?
About a year ago we were working with a client who wanted to bring some very specific data into their Google Analytics account. They wanted to compare their site traffic with the current price of scrap metal, by adding it as a Custom Variable on the visit. While scrap metal prices aren’t exactly something that would help many other clients, we started thinking more about different kinds of ways we could pull other information from APIs around the web, into Google Analytics, in ways that would increase our insight. (more…)
For this post, we wanted to take a step back and describe the Universal Analytics upgrade process in very simple terms. What is it, and why should you care? If your company is struggling with any of these common questions, feel free to download this one-pager and share with your company to help understand the benefits of upgrading to Universal Analytics!
Read on for more information and the full text of the one-pager! (more…)
Note: This article contains updates to the previous article “Statistical Significance Script for Google Analytics”, which has been redirected to this article. See the changelog for details.
In March I wrote a script for the statistical evaluation of time-frame comparisons in Google Analytics. The idea seemed well received, but who wants to have to hit F12, open their developer console, and then come back to my blog post for the code… every time you want to run the script?
So, I converted the script into a Chrome Extension (click below)!