This Week in Web Analytics & Optmization
February 18, 2012 By Leave a Comment
Referring Domains Demystified – Part II
November 21, 2011 By Leave a Comment
In part I discussed how the referring domain and pages are reported by a web analytics tool. In this part I will discuss why your own domain shows up as the referring domain.
There are following three main reasons why your own domain name shows up as the referring domain.
1. If a user waits for 30 min (or whatever your session time out is) before clicking on the next link on your site.
It is a standard practice to use 30 min session time out. This means that if a visitor waits more than 30 mins to click on a link on the website, the click constitutes a new visit.
As in my last post, let’s take an example of visits for one visitor. For this example I am only showing 5 fields (s-ip, data, time, URI stem, cs(referrer) )
Below is the data for a visitor:
The visit started with a referral from http://www.google.com/?q=seattleindian. The referring domain in your web analytics tool will be Google.com
Let’s assume, this visitor goes on a lunch break leaving the site open in her browser. Come back after an hour and clicks on the home page links, here is how the log file will look like as
This constitutes a second visit (I am assuming a 30 min session time out). The referring page will be http://www.seattleindian.com/seattle/advetise.asp and the referring domain will be SeattleIndian.com for this second visit.
If you are a content site that has long articles or have downloads that takes more than 30 mins to complete, chances are you will see your own domain as the number one referring domain.
2. If you intentionally or un-intentionally exclude one or more of your pages from analysis either by not including javascript tracking (tag-based solutions) or specific exclusions that does not allow that page request to be tracked(this applies to both log file-based and tag based solutions)
Let’s assume http://www.seattleindian.com/seattle/default.asp, the home page of seattleIndian.com is not tagged with the web analytics JavaScript code or for some reason is omitted from the analysis (hard exclude either intentionally or unintentionally).
Taking the same example as above, the log file will look like the following
Note that the first log line
is no longer there. The log file won’t even contain Google.com as the referrer because the visit did not begin at http://www.seattleindian.com/seattle/default.asp (since it was not tagged or was excluded). In fact, according to the analytics tool, the visit began at /seattle/bollywood.asp and was referred by the non-tagged (or excluded) page, the home page of SeattleIndian.com. In this case /seattle/default.asp, the page which is not tagged will show up as the referrer and the referring domain will be the domain itself SeattleIndian.com
Note: I have seen a lot of unintentional excludes that affect the reporting. It is highly recommended to use a third party accuracy audit to make sure your reports are configured properly. Contact me if you need more details or help with this. We do this all the time.
3. If you have sub domains that have their own reporting profiles or suites (or whatever you call them) they could cause your own site to show up as referring domain.
Let’s take an example of http://www.usaindian.net which has several city-specific subdomains e.g. seattle.usaindian.net, ortland.usaindian.net etc. Any reporting that excludes http://www.usaindian.net home page will show a lot of referrers from its own domain i.e. usaindian.net
Here is the log file of a user who searches seattleIndian on Google and then clicks on the link to seattle support page (http://seattle.usaindian.net/seattle/support/asp) from USAIndian.net home page.
Say you want to create a profile for Seattle area only i.e. exclude everything else and only report on traffic to seattle.usaindian.net domain. If you only include traffic from seattle.usaindian.net (or s-ip of 1.2.3.5 in the example above) in your reports then the referring domain will be http://www.usaindian.net, i.e. your own domain.
I hope this was helpful. This concludes my two part series on Referring domains and pages. As always send me your comments and questions.
3 Reasons I'm Not a Web Analyst
October 3, 2011 By 2 Comments
I’ve been proud to call myself a web analyst ever since I realized there was a title for it. It’s an emerging field full of talented people. Frankly, it’s the future of business management, and a web analyst possesses a critical skill set and mentality for any company to have.
I’ve come to realize, however, that I can no longer call myself a web analyst. There are three main reasons for this conclusion. [Read more...]
Future of the Web Analyst
September 27, 2011 By 2 Comments
Tomorrow’s web analysts will look very different from today’s.
Being a web analyst today usually means being lonely. Most companies don’t hire full-time analysts to work onsite. They hire consulting agencies or they hire a web analyst and make them do SEM work on the side (or vice versa). In the few companies that do hire a full-time analyst, that person ends up being by themselves. That means being lumped into an existing organization that doesn’t make sense (IT, marketing, new media, etc.) and needing to defend analysis and recommendations alone. [Read more...]
Web Analytics Careers: 4 Great Blog Resources
September 19, 2011 By 1 Comment
Career chat has always interested me. When I was a new college grad I spent a fair amount of time in my alma mater’s career services office, getting advice as I prepared to make a start for myself. I’m glad I did it. The career counselors liked me enough to use my resume as an example for other new grads, and I managed to land an internship at a multimedia CD-ROM publishing company (which, back in 1995, was so totally cutting edge).
After more than a decade out in the workforce I feel like I’ve learned a great deal about my strengths, preferences and motivations when it comes to my career. But I also know that career planning didn’t end when I left my college campus – it’s something I must always keep in the back of my mind. I like hearing about how my peers are handling their own career choices, and I think it’s a productive thing for us to talk about with each other.
So I’m planning to write about career-related topics, now and then, in this blog. Before I get started I’d like to acknowledge 4 fellow bloggers who’ve already written some great web analytics career-related material:
- Alex L. Cohen
I appreciate Alex’s enthusiasm – right now he’s doing an interactive marketing tip-a-day for the entire month of November [really, Alex, even on Thanksgiving?]. Occasionally he writes about career-related issues, including this piece on how to write a good web analytics resume. - Stephane Hamel
As Stephane was contemplating his own impending career move he wrote this very compelling post on the importance of doing regular career self-evaluations. I liked it so much I wound up using it in my presentation on career management at eMetrics. Neither Stephane nor I can fly a kite too well, but luckily that’s not a requirement for our line of work. - Avinash Kaushik
Oh, what’s not to love. I wouldn’t say Avinash has written about careers, though, so much as he’s written about the flip side of the coin – hiring. I thought this post about whether to hire fresh blood or old hands was especially good, and you can see from the comments that many of his readers turned it around and talked about the issue from the job candidate’s perspective. - Anil Batra
Anil has compiled a whole collection of interviews with web analysts; as of this writing he’s accumulated 32 career-related posts. I’ve really enjoyed reading the interviews – just to get a sense of who “we” are – but I think they could be equally valuable to someone who’s contemplating an entry into web analytics.
Read what these fine gentlemen have to say, and read my blog, too. I think there’s still more we can and should talk about when it comes to careers in web analytics, and I aim to be a part of that conversation.
Originally posted at: http://june.typepad.com/june/2007/11/web-analytics-c.html
Who moved my traffic?
September 11, 2011 By Leave a Comment
Your site traffic is down, you are running up and down the hallway freaking out. Wait before you get all anxious about the traffic, d
ownturn in your traffic might not be something to freak out.
Below are some of the things to look at to find out why your traffic is down. Some reasons are within you control (stop freaking start working) some out of your control. Some might be very obvious and some might not.
- Seasonal Impact – Do year over year comparison and see how the traffic pattern was last year.
- May be overall traffic is down even for your competitors (do comparison at http://www.alexaholic.com/ )
- Has a new competitor entered the space? How is their traffic?
- Traffic drivers – How was the traffic from these sources?
- Campaigns (Banners, Search, Emails) – Has anything changed.
- Email – Did anything change there? Did you send out your regular emails, newsletters?
- Search – Did you change anything here, have search engines changed their algorithm.
- Search – Did you change your site? Meta Tags? Content?
- Affiliates – Has any affiliates changed their site.
- Environmental Factors – How is the weather in the geographical region where you have most visitors from? Nice weather can keep people outdoors, resulting in lower traffic.
- Was there any site outage
- Have you made change to your web analytics tool configuration? If yes, investigate what those were? Problems in filter could be filtering out a lot of traffic.
This was originally written in 2006 at – Web Analytics, Behavioral Targeting and Optimization by Anil Batra
Online KPIs – Back to Basics
September 10, 2011 By Leave a Comment
Those who have been doing web analytics for a while know how important it is to define proper online Key Performance Indicators (KPIs). But believe me, there are a lot of marketers who are confused about online KPIs, difference between KPIs and metrics and how to define them. So I am going back to basics with this post.
What are KPIs
Web analytics tools collect a lot of data and provide a lot of metrics and reports. In fact most of the web analytics tool vendors proudly talk about number of reports that can be created in their tool. These reports, metrics and data might look interesting but we all know interesting is not necessarily important. KPIs, on the other hand, are the important metrics; the metrics that provide a view into the health of the business and are tied to the business goals. They allow business owners to focus on the things that are important to drive their business. Key Performance Indicators tell a business owner whether he or she is meeting their business goals or not. Good KPIs provide context and hence are usually represented as ratio, percentage, indexes etc and not as raw numbers. KPIs drive actions within an organization.
KPIs are specific to a business role. So, not all people in the organization have the same KPIs though all the KPIs should ultimately be tied to overall business goals. The CEO has a set of KPIs, a merchandising manager has a set of KPIs and a marketing manager has yet another set of KPIs. However, all of the respective executives (departments) need to be defined keeping overall business goals and CEO’s KPIs in mind.
Another way to understand KPIs is that they are the metrics that make people freak out when they go in the reverse direction from the expected and call for immediate actions.
Since so much is riding on the KPIs, it is very critical that you pay due attention in defining your KPIs. Understand what business goals are and then think about what activities and/or user behaviors relate to your business goals. Put together a list of all the metrics that will measure those activities and/or user behaviors. Weed out the unimportant metrics, figure out what are important metrics and what are critical few (and hence KPIs) that have an impact on the business goals. Note: For your analysis you will need to look at more than your KPIs to provide you a bigger picture. Remember, all KPIs are metrics but not all metrics are KPIs
Characteristics of KPIs
Dennis Dennis R. Mortensen lists following 7 KPI characteristics on his blog “Visual Revenue”
- a KPI echoes organizational goals
- a KPI is decided by management
- a KPI provides context
- KPI creates meaning on all organizational levels
- a KPI is based on legitimate data6. a KPI is easy to understand
- a KPI leads to action!
Those are all great characteristics of KPIs. I however differ a little on point number 2. In my opinion great KPIs are those that are agreed upon by those it directly impact and will be taking actions so they are not just handed down by the upper management. And as I said above they should all be tied to overall business goals.
How many KPIs should you have?
I don’t think there is any rule but in my experience you should limit it to no more than 6.
Reporting on KPIs
KPIs should be presented in an easy to consume dashboard. Web Analytics tools have built in dashboards but most of them are limited in terms of the functionality and flexibility. My recommendation is to present KPIs in a separate dashboard that not only shows KPIs but also trending and brief analysis. Without trending and analysis the KPIs might not provide a complete picture. Excel, PowerPoint or third party dashboard tools work the best for reporting the KPIs. Since they are outside the web analytics tool they also allow you to integrate other data sources, as needed.
Books on Web KPIs
Eric Peterson has a great book on the subject, called The Big Book of KPIs
Originally Posted on Web Analytics, Behavioral Targeting and Optimization by Anil Batra
Top 10 Things I Wish I Knew When I Started in Web Analytics
September 9, 2011 By Leave a Comment
I remember what it was like to walk through the door at my brand new job, my very first job as a web analyst, wondering what I’d gotten myself into. In retrospect, what did I wind up learning the hard way? What would been helpful to know up front? What should I have been prepared to expect? With that in mind, here are 10 things I wish I knew when I started in web analytics:
- You will sit between the techies and the marketers. Figuratively, and maybe literally. Make friends on both sides of the fence.
- You will learn all about your business. Not just the stats part. Not just the web part. The work you do in web analytics will only make sense once you’ve put it in the general context of your business.
- Ahem, what is this thing you call a “Visit”? Know your standard web metric definitions by heart, and be able to recite them concisely for people who ask. They will ask.
- Dirty, dirty, dirty. Numbers won’t match, they won’t add up, they won’t make sense, sometimes they won’t even exist. Know how much dirt you’re willing to live with, then accept it and move on.
- You will learn to love the query string. You will come to see it as a beautiful haiku. You will know it backwards and forwards. You will repeatedly explain its usage to people who need to append campaign codes to URLs.
- CSV stands for “comma-separated value” … it’s a file format, every data analyst’s friend, and – inexplicably – it doesn’t even have to be comma-separated. Huh.
- Operators are standing by. Know the support hotline number for your commercial web analytics vendor of choice, and don’t be afraid to call. If you have one sticky note on your monitor it should be that number. Actually two sticky notes. The other one should say, “Patience is a Virtue.”
- Don’t fall into the “report monkey” trap. Manually-repetitious activities are not a good use of your time, so automate wherever possible. Strive to spend your cycles doing thinking fellers work, and leave robot work to the robots.
- You are not alone. Right now there are other web analysts sitting at their own desks, somewhere between the techies and the marketers, and they’re facing exactly the same issues that you are. You will meet them at Web Analytics Wednesday.
- Think long-term. From the very beginning, think about where you want your career to go and make every effort to develop in that direction. Your entry-level position in web analytics can/should/will lead to other things, so know what you’re targeting and go for it.
Originally Posted at: http://june.typepad.com/june/2010/03/index.html
Looking to fill your Web Analytics or Online Marketing position? Post your open jobs on Web Analytics Job Board.
Individual Visitors Tracking or Aggregate Data – Which One Is The Right Method?
September 8, 2011 By 4 Comments
Should web analytics tool track visitors as unique individuals or at the aggregate level? John Squire, Chief Strategy Office of Coremetrics says that tracking at Individual level is the way to go and this is how his company is differentiating itself (from Google analytics). Brian Clifton, former heard of Google Analytics in EMEA, responded by saying that aggregation is the way to go.
In my opinion both of them are right. Which route to go really depends on what you want from the web analytics tool?
Aggregate Data
If you are new to web analytics or you just want to track and analyze the overall health of your website, aggregated data will work for you. If you want to know how your marketing efforts are performing in terms of driving traffic or online conversions than aggregate data will just work fine for you. If you want to know which pages of your site are bleeding and then conduct A/B testing or Multivariate testing to improve them then aggregate data will work for you.
Individual Visitor Tracking
However as companies mature in their use of web analytics data they will need individual level tracking.
A company which is ready to do personalization will need to understand each individual browsing/purchase behavior to put the right offers/products in front of her. That is not possible with aggregated data.
It sounds perfectly ok to know that 75% of visitors abandoned the shopping cart but won’t it be nice to know who those 75% are or a way to convert at least some of those 75%? This is where individual tracking will come in handy. If visitors, who abandoned the shopping cart, leave an email during the process then you can send them a targeted email based on how far along they were in the shopping process, what products they had looked at, what product they had in shopping cart, etc. You don’t need to analyze every single data point but you can have business rules that can trigger those emails. However, to do so you will need to track at individual level. Even if you don’t want to send an email if you know the cookie id of the visitors you can put a personalized offer in front of them when they return back to your site and this will require tracking at individual level.
Individual tracking also comes in handy when the sales people call the lead that they just got from the website. Knowing what the person, who filled the contact us form, did on the website could provide a lot of information to sales person who can then tailor their conversation based on this information.
There are several more scenarios where aggregate data just won’t work. You will need individual level tracking.
I agree that tracking individual has privacy implication that need be properly addressed before tracking each person. However privacy issues also exist when you anonymously track visitors at aggregate level and those need to be addressed too.
So should you choose a tool that aggregates the visitor data or the one that tracks them individually? It all depends on what you want to do with that data. If you need help in figuring out what tool will work best for you feel free to email me at batraonline at gmail.com
Comments/Questions?
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Looking to fill your Web Analytics or Online Marketing position? Post your open jobs on http://www.web-analytics-jobs.com/
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Originally Posted at : Individual Visitors Tracking v/s Aggregate Data – Web Analytics, Behavioral Targeting and Optimization by Anil Batra
