Google stirred up a hornet’s nest recently when it announced that Gmail now cached images within emails. While image caching improves the user experience, the email marketing community scrambled to understand how caching impacts image downloads, which serve as the mechanism for tracking email open activity. After reviewing the responses from several notable email service providers, including Campaign Monitor, Constant Contact, ExactTarget, MailChimp, and Responsys, it appears that the overall change is positive for email marketers.
Here are the 5 things that you need to know:
I recently saw a funny video on big data that I just had to share. The concept of big data is that meaningful information can be extract from voluminous data — the kind that is too big for a standard database.* Nonetheless, big data is valuable in that it can predict what customers want (before they know that they actually want it!):
Big data is so hot right now primarily because (A) there’s lots of data sources (eg: Google Analytics, eCommerce transactions, in-store/catalogue orders, social media, etc.) and (B) data can be cheaply processed. But it seems that marketers believe that big insights only come with big data! To that point, it also seems that small data is all but useless! But is that really true?
Well, while bigger may seem better I recently
was reminded learned in my Data Analysis MOOC (aka online class) that big insights can also be found in smaller data sets! It just isn’t always feasible to have a super-sized data set — client may not have a large amount of data. And fortunately for them and for data heads, small data along with inferential data analysis (along with random sampling) can deliver big insights.
To get started, you just need a business problem, a theory and data to prove (or disprove) your idea! So don’t let the lack of big data stop you from doing the analysis.
*Big data is more than just voluminous (see O’Reilly).
For the past 5+ years, Google Analytics has been my go-to web analytics tool. While it isn’t as robust as Omniture or WebTrends, the pricing model (Free!) and easy installation & simple configuration processes have resulted in widespread adoption. According to the technology adoption and trends tool BuiltWith, Google Analytics is used by more than 44% of the top 1 Million website. In comparison, Omniture is used on only 1.35% of the top 1 Million websites.
I’ve been spending significant time with Google Analytics over the past few months and I seem to be running into more limitations each and every day. Here are the 3 things that I would expect to be able to do with Google Analytics (but I can’t):
- Advanced segmentation isn’t really advanced. After I wrote my post about about the robustness of advanced segmentation, a colleague asked me to help her with creating a report on user behavior using internal and external visitor segments. Knowing that I’ve set up Views where I’ve excluded traffic using an internal IP address, I began searching for the “Filter by IP” field but could not locate it under any of the available options. Once I realized that this was not possible, I resolved to creating the 6 essential Views that we set up with all client accounts so that she could report on this behavior in the future.
- Custom Dashboards aren’t really customizable. I met with another colleague before the Thanksgiving holiday break to discuss the buildout of a custom dashboard. He sought my help with creating one since I had built a custom dashboard for my blog. We attempted to create a basic widget that displayed on a daily basis the total visitors vs. new visitors vs. returning visitors — a graph that a marketer would commonly look at. While the visitor metric could be added to the graph, we couldn’t add the visitor type dimension. To work around this limitation, we added the % new visitor metric. Furthermore, we could only add a single metric!
- API’s aren’t really open. I add an annotation every time that I publish a new post on this blog. Since my blog posts get automatically pushed to social media networks when they are published, I began investigating whether I automate the process and cut the manual step of adding these annotations. I looked into the Google Analytics API’s and while Google has multiple API’s — API’s for data collection, account management, and data reporting — none could be used to create annotations on the fly.
Google does have a support forum where new features can be requested so I posted my suggestion for automating annotations. While the features that I want are not currently available in either the standard or enterprise version, I’ve noted that Google has invested significantly in the platform this year. I fully expect the product development team to continue to release more valuable functionality in mid to late 2014.
What features do you think are missing in Google Analytics?