Posts Tagged ‘web analysis’
Managing Web Analytics is about managing limitations
Web Analytics, while still very much an emerging discipline, is constantly under intense scrutiny by its practitioners. Not surprising, since the entire goal of the space is about clear understanding and continuous improvement.
In the early 90s, web analytics was not a marketing activity. Rather it was about technical performance of the website, and the reports were generated from logs and owned by the same guys and girls who keep the server room running. At some point in the mid 90’s, Marketing realized that they could use that data to understand the business impact of the website and a discipline was born. This was the golden age of WebTrends, the first marketer facing web analytics tool.
Because of the fact that this software was built by IT, the unit of measurement was around hits, or individual calls to the web server. 10 images on a page would be 10 hits. Not the richest data for business analysis. An analyst could discover which elements of a site got the most ‘hits’ but could not tie them to types of visitors or business goals in such a way that they could affect change.
In the late 90’s new vendors like Omniture, Coremetrics and WebSideStory entered the analytics space (as well as Urchin, DeepMetrix and IndexTools, which would later become Google, Microsoft and Yahoo Analytics). These vendors built products around marketer requirements rather than IT, and this gave rise to both page tagging (removing the main limitations of log analysis), and richer reports designed for Marketers.
This period from 1997-2000 (when the first dotcom bubble burst) was the first big vendor gold rush in digital marketing. Many of the bigger companies (and lots of the failed ones) in digital marketing were founded in this period (think Akamai, Offermatica, Lyris, ATG etc.).
The limitations of these types of analytics tools and vendors are significant:
Tracking the Visit and not the Visitor: While tracking visits is a lot better than a server call, it is still not the best base unit for measurement. No one sells to a visit they sell to a visitor, and a lot of high value information is left on the table because of the lack of this kind of tracking. Want to know how many visitors to your site created an account and then came back later to buy? Forget it.
No sharing of data: Each product has it’s own proprietary reports, data capture and data naming conventions. This means that it was impossible to create a decent report on a full set of digital marketing campaigns. This taught most digital marketers to treat each use of a product as a ‘campaign’, and analyze each campaign as a standalone. This explains why offline marketers will think of a marketing campaign as a multi-message, multi-medium program (think TV ads, radio ads, sponsorships), and online marketers will think of a campaign as a single activity (think one email newsletter, one personalized ad, one coupon code).
Last week, I finished up presenting our Napkyn Analyst Program report to my clients. Working with a number of clients’ web analytics data and then going through the data, insights, and recommendations with them is an amazing process – it reveals something new about the nature of the web and website visitors each month.
Some of these pages are so deep, you'll need a shovel. Or a search engine.
For a particular client this month, I attempted to chart (or graph, depending on your persuasion) traffic by medium, top landing pages, second-click pages, and then transaction or conversion… and the chart landed up looking overly complicated. I didn’t present it to the client, but the research behind this messy chart was invaluable.
Through a maze of arrows, boxes, and pie charts, one realization came to the fore: Every page is a landing page. For web analysts, this might not be a grand revelation, but some small or medium-sized online business owners, it’s not said often enough.
Here are 3 steps to improve conversion and serve your deep landing page visitors better.
One of the most common recommendations that Napkyn makes to our clients is to properly tag emails so that they can be tracked in Google Analytics. The key to actionable and insightful digital analysis is clean data that properly represents an online business – and tracking email sendouts is a pretty simple way of cleaning up your data.
How do we set up email tracking?
Unless you’re lucky enough to use one of these fine email marketing services with automatic Google Analytics integration, you’ll have to set up email tracking manually with a bit of coding.
First of all, let’s stop thinking in terms of email tracking and start thinking ‘link’ or ‘URL tagging’. That’s the key. Your emails contain links back to your website, and if you want to monitor the impact of your email sendouts, you have to add tags to all your links. Tags are short additions to the URL that tell Google Analytics how to categorize traffic.
But not to worry, it’s actually pretty simple.
Let’s get started!
Great! A little effort now will make your data much more valuable in the near future. Let’s use the Contact Us button on the upper right-hand corner of this blog as an example. It really doesn’t matter if you’re tagging a link in an email, on a blog, or on a website.
It links back to:
But I wanted all the traffic that was sent to napkyn.com using that button to be noted that it was coming from this blog and from that button. So I added some tags to the URL – this will not interfere with sending traffic to the right page, it just labels it. Now the button links to:
You can plainly see how I wanted the traffic labeled.
Source = ‘contact_button’
Medium = ‘blog’
Campaign = ’04152010′ (The date the button was placed on the blog)
Now, when I look at the Napkyn.com Google Analytics account, I can see that the source and medium have been labeled as we intended.
For an email, you may want to label your traffic differently than I’ve done here. For example…
Source = ‘newsletter’
Medium = ‘email’
Campaign = ‘fall’
You can use the Google URL Builder or the excellent tool from Cutroni.com to make this process easier.
Of course, there’s a lot more to digital analysis than proper link tagging. So give that wonderfully tagged Contact Us button a click, check out napkyn.com, or leave a question in the comments.
One of the most interesting things about working at Napkyn is that every discussion with a prospect or new customer is a fascinating one. The reason is that every serious owner of a web presence, whether is it a store, lead gen site, non-profit, or even blog is running analytics. Because these analytics tools are only 2% utilized, each discussion we have tends to be informative (for both sides), and interesting, aligning different reports with different unique business requirements.
While every business we talk to has individual needs, there are definitely questions that are pretty standard. A few of them have been discussed in the last posts, but today’s post deals with a biggie:
Should I use a free analytics tool, and which one should I pick?
This is a topic worth a book, not a blog post. In order to keep this interesting (and under 20,000 words, I am going to do two posts on the issue. This one will be on the biggest points to consider when examining free analytics tools, and the next will be a discussion and comparison of the ‘big two’ of Google and Yahoo’s analytics tools. (before I start getting emails with suggestions of other tools that should have made the list, finish reading the post….explanation to follow)
There are a few high level points that should be considered when thinking about free analytics tools:
They aren’t actually free: Any free or open source tools you use come with zero support. You have to do the integration yourself, you need to troubleshoot yourself, and you need to learn how to use the product yourself. This means you are going to end up paying a consultant or you are going to offset the direct cash spend with the indirect spend of the time of you and your team. It is for this reason alone that many firms choose a paid vendor, and is definitely something to consider when going the ‘free’ analytics route.
Additional Reads on this topic:
Why Web Analytics Tools Fail – Judah Phillips
Web Analytics Tool Selection – Avinash Kaushik
Just say no to log files: Without spending too many words on the issue, log file based analytics tools read what happens on your web server, require a lot of maintenance, and don’t deliver a lot of great data for the purposes of your average marketing question. If your current analytics tools is log file based, it is time for an upgrade.
(You will notice that each of the additional reads gives pros and cons to both page tagging and log files. I firmly believe that the disadvantages of logfiles completely outweigh the advantages, especially when you think about the advantages of doing ongoing analysis with the new breed of page tagging tools, feel free to comment with your two cents)
Additional Reads on this topic:
Should I use Log Files or Tags? – SCL Analytics
Wikipedia Entry on Web Analytics Logfile vs Page Tag
Stick with the big boys: If you aren’t a fulltime analyst, or someone who is excited about being an early adopter of technology, don’t choose a tiny company for your web analytics. There are some really cool products out there (woopra for example), but as mentioned in the first point, you are going to be learning and doing a lot on your own. The bigger the user community you are a part of, and the bigger the company that you are working with (i.e. Google or Yahoo), the easier it will be to get ramped up.
Additional Reads on this topic:
Forrester Web Analytics Forecast: WASP Data – Stephane Hamel
Wikipedia Description of Early Adopter (if you qualify, feel free to disregard the big boys statement)
No plan, no value: This is one of the biggest issues we deal with when talking to companies that have been running analytics for years but don’t feel they are getting any value. Most firms know they need analytics, so do a basic deployment of a tool without thinking of the data needs of their business. This means that they aren’t able to ask good questions, or get good answers. Before you choose or deploy, think about what you want to accomplish, what questions you want to ask, and what reports you want to see. Remember also that your analytics tool should be reporting on every thing you do that affects your digital channel. Doing a lot of email? Track it in your analytics. Decided that twitter will grow your business? Track it in your analytics. Do 60% of your call center sales originate on the web? You get the point.
The next post will cover what we feel to be the two free analytics software options for companies that want to make to get into data driven decisionmaking. Google Analytics and Yahoo Analytics are both very valuable, and very different. Learning more about them will help understand the vendor landscape, and help make better decisions about building your digital analysis plan.