There are standard report settings within every analytics solution that can segment website traffic. New visitors versus returning visitors is an example. But there are times where a setting has to be tailored to text related to a visit. This is where filters come into play.
The skinny: Filtering limits reporting to specific kind of traffic in which you know you would or would not consider. The benefit is a more efficient reporting. Filters should be planned to that they compliment a specific strategy, layout, and traffic trends. For example, a filter can be set so that reports show activity that occurs on a certain set of subdirectories.
Just about every web analytics solution provides a filter capability. Because it focuses on text, filters can assist in narrowing the data in a variety of different situations.
Filters can help gather text shared across a number of domains.
Filters can include or exclude IP addresses (or a range of address) – A possible usage can be eliminating site visits by employees, keeping the data more accurate. It can also be used to interpret data across
Filters can be set by geography
Filters can also reflect segments of data – referrer, client browser settings, page titles, etc. – this can be handy for a segments which reflect a persona of a target market.
Filters aid your business operations by narrowing the reporting scope on the activities that relate to your business. This saves time in developing strategic solutions based on the data reported.
Early this year, Zimana received the privilege of being named among the Top 100 Twitter accounts that covers big data and related topics. The Peer Index #bigdata100 Twitter campaign began by asking the Big Data Republic site audience to nominate their favorite Twitter accounts that provide thought provoking big data topics and conversation. 181 nominations were selected. Zimana was ranked 38 among the final 100 selected.
Zimana is truly grateful to be included among a stellar list of big data experts and specialists. “I wish all the nominated accounts the best as the analytic world continues its mission to positively influence the world,” says Zimana founder and Chief Digital Marketing Strategist Pierre DeBois. To see all 100 accounts selected, read this overview by Big Data Republic.
In the race to improve analytic capability in companies, marketing teams can sometimes overlook the technical elements make analytics work. Thus incorporating analytics tags early in a digital marketing plan can reveal the tasks most relevant to business objectives and more vital than launch tactics.
If your marketing team struggles with vetting tags, they are not alone. Agencies are encountering new challenges for implementing client-server tagging. But tag usage is certainly not abating. In fact the number of web tag types used by agencies and businesses surged 53% in 2012 according to Adage. A revealing statistic: While 45% of tags were applied directly by the publisher, the rest came from other sources. Thus control over where data is being captured is an increasing concern. Privacy issues occur if left unchecked.
Early consideration of analytic tag placement can reveal potential security hiccups. It can also bring forth productive talks and tasks. In one instance, it can educate non-technical managers on the technical aspects to a digital marketing campaign launch. Many professionals have adopted computer usage, but not every professional understands client-server technicalities and programming that belies a digital ad or social share. A tag evaluation can help managers see what needs to be checked, and see how changes in data usage and associated code can aid business decisions.
Second, early tag implementation can lead to better refinement of a company’s website measurement against current digital trends. For example, most professionals can appreciate that data can appear at client-side and server-side, but apps in mobile and tablets have created new functionality for client-side data. This means planners must express content and associated tags to accommodate different screens, to balance customer activity on varied devices, and to capture metrics that reflect business objectives.
Third, early tag implementation organizes measurement complexity, easily highlighting needed skills or processes. For example, a team can achieve good tag quality assurance with an appreciation of client-server interaction. Verifying tag functionality does not require a deep knowledge of machine language, but translating business objectives to a website requires an imagination of where tags can be placed and which metrics are best recorded.
With early incorporations of tags, the good news is that many agencies are learning better ways to manage the teams involved. I learned about one such discovery while attending an Ogilvy and Mather presentation in their Chicago office. Benjamin Hong, Director, Marketing Analytics and Mike Armstrong, Technology Director explained the tag process to the Chicago HTML5 Meetup audience, a group of web developers. The fact that this presentation addressed developers highlights the ideas that it’s never too early to talk about tagging concerns, even with a website wireframe.
As you can imagine, gathering tag requirements for an analytic practice best starts with a holistic viewpoint from designer, developer and marketers. Doing so surfaces the reasons for why tagging is being requested in the first place. “We need to talk about web analytics as analytics – what is the relationship between the things we do and what our outcomes are, “ explained Hong in the presentation. “We may be given an assignment without really being given the outcome. Analytics focuses on behaviors caused by the activities that drove behavior.”
Understanding how to best translate marketing activity to URL queries is clearly valuable to any tag evaluation. And given the volume of media channels and publishers using tags, such translation has become prime real estate in a digital marketing neighborhood.
Winds of changes do not always come with a roar. In fact many come with a hush. One terrific hush that came in 2012 (and still going in 2013 – hey, tech never stands still!) was the refinement of analytic dashboards. These applications were meant to pull data from web analytic solutions, allowing analysts to quickly refine the data into charts or combine with other data queries to support business decisions. One of the earliest for Google Analytics has been Excellent Analytics, an open source plug in for Microsoft Excel for Windows.
A while back, I had the pleasure of exchanging an email Q and A with one of the EA original developers, Lars Johansson (@webanalyticsinfo). Based in Stockholm, Lars developed the plug-in as a necessity to pull and manage data. He explained some of the details behind the plug-in development that lead to the current team behind Excellent Analytics.
1. How did the team behind Excellent Analytics came to be? What attracted you to this open source development?
I came up with the idea while running an analytics consultancy, Mark Red. I had used Excel plugins for other web analytics tools previously and seen the benefits, but there was none for Google Analytics. My colleague Christoffer agreed that it was a great idea, so we brought in a student to work on EA as his project. The idea was to get the community involved in the development to ensure that Google Analytics would have the best Excel plugin of all web analytics tools. That’s why we made it open source.
2. You have spoken with a number of well-known analytics professionals, such as Stephane Hamel and Paras Chopas about analytics. Have you or the EA team encountered a professional audience broader than the analytics community since the launch of EA?
I would say so, yes. We count the users in tens of thousands. It’s not just used by web analyst. In fact, our main criteria when making Excellent Analytics was to make it easier to use than all other web analytics plugins for Excel. It should be so easy that anyone can understand how to use it after watching a short introductory video. As far as I can tell, we’ve succeeded with that. For Excellent Analytics Pro we are facing the challenge of adding more features without making it more complicated and scaring non-analysts off.
3. Can you share some success stories and examples of how businesses have improved their analytical modeling with Excellent Analytics?
The most common story we hear is how Excellent Analytics is saving them a lot of time on the tedious part of analysis: extracting and combining data for analysis. Just by saving your queries and reusing them again you save a lot of time. In Excel you can also use plugins for other types of tools and combine data from multiple sources in a single view. Basically Excellent Analytics is a tool that generates more time for actual analysis.
4. Many other open source developments, like the databases (MongoDB, Couch) have a community, which supports their development. With EA being an open team back an open source free product, do you find it difficult to find and add developers to assist with refinement and development?
We have had a number of developers sign up to help us out. To our surprise, however, they have not contributed anything to the project. Maybe it’s because they’re not that familiar with the technology used.
I and Christoffer left Mark Red (which in effect was just the two of us) in June 2010 to start inUse Insights, a web analytics consultancy. We also started the web analytics product company Ampliofy. We can’t put endless of hours into the open source project unless we have a different source of revenue. That’s why we also created Excellent Analytics Pro, which has been coded from scratch to allow for more automation and advanced features. We are making sure both versions of Excellent Analytics will live on through Ampliofy’s developers.
5. What inspirations or new developments in analytics have caught your interest? Where do you see the budding community of analytics plug-ins headed?
I’m impressed by Paras Chopra’s and Wingify’s fast, customer-centric, development of Visual Website Optimizer. I also enjoy following Dennis Mortensen’s latest venture, Visual Revenue. Different solutions aiming at making website tagging for web analytics, and other tools, simpler, faster, and less IT-demanding, have also caught my interest for some time.
This latest webinar from Webtrends features Forrester data and a great overview of how analytic is changing the face of new digital devices. Play the webinar below, and see how any of the concepts can respark your analysis approach. If you’re stuck regarding how to regard your web analytics results, consider how your metrics reflect the digital data inputs or correlate to your business data. How relevant are the results to your business today?
Great webinar by the Webtrends team and wonderful support from Forrester.