Relevant information in non-perfect enviroments

If you lose more than 30 minutes a day analyzing your site its probably that you are not doing things as good as possibleMost of the people I know carry on the following analyzing process:

1- Login to the Web Analytics tool and I look at the traffic. If it looks similar to yesterday (or the same day from the last week), then we are ok. If the traffic is higher or lower, then I try to find why.

2- To find the “why” I look at the different reports and (if available) I cross data trying to get some insights. I also download the info to an excel file and keeps working on it there, since excel is more flexible. 3- I get so much information and things get more and more complicated. 4- I have lot of other things to do, so I leave everything as it is (still with no answer). 5- As the last possibility I ask people from other departments if they have any idea about that change in traffic. 6- Based on those answers and some interesting insights I´ve got, I infer the rest and get the answer that makes me feel more satisfied… Required time: 4 / 8 hours…(the rest of the people leave in the step 3).Even when it is true that the best thing we can do is integrating all the information in a main “repository”, allowing to answer all the question in the same place, it is also true that for some companies or persons it is not an option for both technical or time constrains. So what can we do if it is not possible to us a full integration? The simplest solution is having an agenda with al the activities are occurring in our company, not just ours, but from all the departments of functional areas. Companies are “systems” which mean a groups of things interconnected that work together with a unique mission. So if we modify one particular part of the system, we are also modifying the complete thing, and not just one part. Coming back to the agenda, why it is so important? Because, even when it won’t tell us immediately “why” we have an spike or drop in traffic, it will tell us immediately where can we find the answer. Example, we launch an Adwords campaign and in parallel our website get offline for an hour making that the spike in traffic from the Adwords campaign is counteracted by the offline time.Without an agenda with events or “milestones” the analysis would be: 1- Technology Department: Amazing, the server was down for about an hour but it had no impact to the site traffic. Don´t tell anyone!!!. 2- Marketing Department: The Adwords campaign generated no traffic!!!. 3- CEO: The traffic has no change, we are just great!!!. The event calendar gives the big picture making more efficient the analysis and decision making process.How can I have an event calendar (or agenda) when it is a non supported feature in my Web Analytics tool?The simplest option is having a Google Spreadsheet shared among your team. Simple and useful. You can also add this functionality that will export your Google Analytics report directly to Google Spreadsheet making your analysis even more flexible and simple. I hope you find this tip useful.

Google Code – All you need to know about Google Analytics

Google has launched a site focused on providing support to those needing measuring their sites in a more sofisiticated way. What can you find in Google Code? Lot of information about how to implement custom Analytics Installation on your site like “Change the longevity of your marketing campaigns“, “add a new search engine” to the list of those Analytics recognizes and “configuring tracking to use both Google Analytics and Urchin Software from Google“.If you are a Beta tester you can also find an entire section dedicated to Beta-testing event tracking. You can also find an E-commerce overview and E-commerce API reference. The sections “tracking code execution” and “how Analytics uses cookies” are just great.Great to hear that Google Analytics is getting smarter

Key Tips – Web Analytics for Blogs – Second part

As promise, the second part “Interaction”.

Interaction: When you created your blog, you did it for a reason, an objective, so you should measure if that objective is being achieved or not. Whatever your objective is, it may be related with some kind of interaction between your audience and your blog (unless your objective is not being visited at all…like an autistic blogger ) so, it is important to measure it. Let’s see how to do it:

a. Comments per post: This metric is as simple as useful; because it let you know if your posts are generating interaction among your readers. If you objective are interacting with your readers via comments, then this is your key metric. However if you just receive a few comments (or none) it doesn’t mean that your post was not successful. Some blogs give readers the space to leave comments while others don’t (consciously or unconsciously), so it really depends on you and your blog’s style. If you receive just a few (or none) comments per blog, I recommend asking your readers about it through a poll.

Comments per post

b. Comments per visit: This metric will allows you to find out the level of interaction between your readers and your blog. While comments per posts tell you how “interesting” was a particular post, Comments per visits tells you in average how interested are your users with your content.

Comments per visit

c. Internal search per visit: Another way to know how interested your visitors are in your blog is by looking at their internal search behavior. Those users interested in your content will keep looking at other content. However I recommend you to understand the user experience, because some blogs has very smart “content recommenders” which makes people go jumping from content to content without even touching the search box.
Internal searches can provide you another key information, which content is “relevant or interesting” to your readers. Remember that the keywords used to get the site by organic search just tell you how your visitors were able to get your site (depends on if the site was or was not available with a particular keyword) while “internal search” tells you what are they looking for, not matter your site is visible in organic search with that keyword or not.

Internal Search per visit

d. Average time per visit: No matter your blog’s structure (your blog displays the entire post in the home page or not) the Average time per visit helps you to understand if you are getting qualified visitors or not, and if your qualified visitors are interested in your content or not. If your visitors are not qualified you will have the most of your visitors in the segment of less than 30 seconds while the rest of the segments will remain flat or almost flat, however if your visitors are qualified but they are not finding interesting content then even when the less than 30 seconds visits segment will be the highest one, you will also have an interesting quantity of people in the 2 and 3 minutes segments.

Average time per visit

e. Average time per page: I just mention this metric to make you be careful about it. The average time per page depends merely on the large and difficulty of the displayed content and not on how interesting or not would it be.
What you can do with this metric is analyzing the top 20 pages with the highest average time per page and try to determine if the one with the highest time has something in common. Once you did it that is the variable you may tune if you are looking to improve that metrics.

Average time per page

Advertising on web 2.0 – Are we ready?

One year ago or so I was talking about something I called DAD or desired advertising (like this one or this one) that was based on delivering the right ad to the right person, and the right ad to the right person is linked to the variable “time”. And the variable time (when I want it) is expressed by the user in different ways, but always as an exteriorization of a desire.

When the people browse in a search engine, or search content within a site or navigate particular content, or even accept to open an email, quick message, or SMS those actions express their interest in some content they are like to get in touch with, while the frequency, time spent, and visit repetition, among others indicators give us a clue about the level of relevance that an specific content has to a particular user / consumer.

Some of the actions I proposed in my post where implemented and are very successful, like random advertising in youtube video (just to mention an example) but the key function is understanding user / client needs and desires and thats in my opinion what is not yet well developed. There is a lack of techniques for a correct desirability tracking and processing.

Are we really prepared for internet 2.0? Are we acting to drive internet to the 2.0 version or just reacting? In my opinion “If we keep doing what we are doing we’ll keep getting what we are getting”.

Juan Damia

Avinash Kaushik – an amazing interview

I’m so glad of presenting to you this interview with Avinash Kaushik. If you are reading this blog is because you are, at least, interested in web analytics, and of couse you know him, but just as a formality here is Avinash’s BIO.

Avinash is an Independent Consultant with a focus on speaking and consulting engagements that help organizations unlock the power of web research and web analytics to create truly data driven organizations and gain a strategic competitive advantage. He is also the author of the book Web Analytics: An Hour A Day, published by Wiley.

Currently He is the Analytics Evangelist for Google.

Most recently Avinash was the Director of Web Research & Analytics at Intuit Inc where He was responsible for supporting the decision making for Intuit’s 60+ ecommerce and non-ecommerce websites. His team focussed on Intuit’s needs in the areas of: Advanced Web Analytics, Competitive Intelligence Analysis, Experimentation and Testing (A/B, Multivariate etc), ClickStream & Outcomes Analysis, Customer Satisfaction measurement & VOC analysis, Web Research (Lab Usability, Site Visits, Heuristic Evaluations etc).

Avinash’s professional career has focused on Decision Support Systems at Fortune 500 companies such as DirecTV Broadband, Silicon Graphics Inc & DHL in Asia, Middle East and the US. If you are interested you can check out his LinkedIn Profile.

He is also thrilled to have the title of Associate Instructor University of British Columbia, having contributed three modules to the UBC Award of Achievement in Web Analytics course.

He has given keynotes / speeches at the eMetrics Summit in Santa Barbara and London, Ad-Tech NYC, Frost & Sullivan Internet Marketing Strategies 2006, Ad-Tech Impact and ATG Insight 2006. For a full list of speaking engagements click here.

JUAN: What does web analytics means to you?

AVINASH: I paused for eight minutes when I read this question! It has so many answers, some probably more philosophical than others. Let me try the straight answer…..

Web Analytics to me is a way of understanding the customer experience on your website with the goal of improving the experience so that the customer is able to complete her / his task as efficiently and as quickly as possible.

On the personal side, to me Web Analytics is the opportunity to collect and analyze data in one of the most interactive environments where you can have a direct and bottom-line impact faster than on any other channel on the planet at the moment. It is so cool when you think about it for a second.

JUAN: How would you define web analytics?

AVINASH: As a member of the Board of Directors of the Web Analytics Association I would be remiss if I did not first provide the official WAA approved definition, here it is…..

“Web Analytics is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage.”

Typically people tend to think of that in very restrictive terms, just clickstream data you can get out of Omniture or HBX or Google Analytics.

I think of Web Analytics as collection and study of any data related to the website and the web channel. In addition to clickstream it would include survey data, experimentation and testing, competitive intelligence, integrated off site and on site data etc etc. It is a much broader view to understand the holistic picture.

JUAN: Why should companies do web analytics?

AVINASH: Because it feels good to make lots of money, rather than staying poor, and it feels good to have happy customers who love you, rather than those who hate you with passion because your website is a hindrance and not a help.

JUAN: Some managers think that having a web analytics professional is not necessary because “anyone can manage the web analytics tool”. What is your opinion about it?

AVINASH: I have a rule called 10/90 rule that I had created three years ago. It came out of years of my experience in the space. It states simply: that if you have $100 to spend on Analytics then you should spend $10 on the tool and $90 on people. That should give you a feel for my opinion about the importance of people in finding insights. Tools are just….. tools.

You might invest in people in your own company to help you understand your goals and objectives and analyze your data to find insights and help drive change. If you don’t have that horsepower then you should go get it from outside, get a consultant who will do that work for you while you find someone and hire then and transition from consultant to your own employee.

I cannot state it more simply: If you don’t have the people (in-house or consultant) to truly analyze the data and find insights then why have the analytics tool?

JUAN: Would you recommend companies having a web analytics professional in-house or outsourced (a consulting company).

AVINASH: Ahhh I have a blog post for this one as well, here is the link…… Web Analysis: In-house or Out-sourced or Something Else?

In short my recommendation is that the end goal should be to have that expertise in-house because no one can understand your company uniquely like people in your company. But in the post above I recommend a four stage plan of moving from getting tactical help from consultants to finding someone in-house to training them to do tactical to transitioning consultants to only do cutting edge competitive stuff. That’s a simple lifecycle.

JUAN: You were part of the new Google Analytics version. Are you completely satisfied with the result? If not, what things do you think must to be improved in the immediate future?

AVINASH: I was, unfortunately, not a part of the new version of Google Analytics, though it sure would be nice to claim credit! The leadership of the new interaction model in GA goes to Jeff Veen and his merry band of design and UI experts. Google is lucky to have them.

I think that even Google’s competitors will agree that the new GA interaction model is a radically better and sets a new benchmark for how users should interact with data and quickly and efficiently find insights. Its strengths are data discovery, providing context everywhere, lots of interesting visualization, non-ecommerce reporting etc.

There are a whole bunch of things I would love to see evolve or added. Even since the release of version 2 of GA there have been two major releases with new features. This rapid improvement will continue because the team is passionate about solving real world problems of its users.

JUAN: Which technology do you prefer, page tagging, web log analyzers, hybrids, packet sniffers, others or it depends on every particular project?

AVINASH: This is a whole chapter in my book (note from Juan: you SHOULD read Web Analytics an Hour a Day, you have years of Avinash’s experience in that book) and I don’t want to bore your readers to death here. I do encourage them to read the book – or I have some posts about this on the blog as well – if they want deep details.

Each data collection methodology has its merits and should be weighed carefully, it is perhaps the single most important decision you’ll make about web analytics because once you make that decision you’ll be locked into the technology, people, organization structure, future evolution etc.

For most websites and businesses I recommend considering page tagging for two reasons they don’t think about as much:

1) Innovation: Most innovation in data capture, processing and reporting is happening on top of solutions that use page tags as a data collection mechanism. Vendors are not investing enough in other solutions, for better or for worse. So unless you have the wherewithal to build your own infrastructure and innovate in the web analytics space then it is perhaps more prudent to give stronger consideration to page tag based solutions (from any company).

2) Integration: You want your web analytics solution to integrate with your survey tool or your behavior targeting tool or your multivariate testing tool etc etc. That way you can understand customer behavior better and even optimize it. At the moment it is easiest for you to achieve this if you have a page tag based web analytics solution.

There are others who will swear by different ways of collecting data. I encourage everyone to take a step back from the tactical arguments and consider the choice in the context of the above two thoughts.

May the force be with you!

JUAN: How do you imagine the web analytics industry in the future?

AVINASH: I think we are in for a couple years of rapid evolution and revolution. Tools will change, the skills we expect from a Web Analyst will change, Marketers will get directly in charge of using their own data and driving changes, there will be consolidation and there will be closures and new starts.

I wish I had a crystal ball and I could pin point exactly what will happen. But I am convinced that the world of web analytics will radically change in the next two years.

On and in the next three to five years there will be no such thing as “web analytics”, it will simply be all “business analytics” because the web will be that big and all the business will be on the web!

JUAN: Which advice / recommendation would you give to a web analytics professional?

AVINASH: You are the hottest commodity out there, if you are any good, ask for a raise

On a serious note here are a couple of thoughts:

- If you are only well versed in Clickstream data and “web analytics tools” then it is time to expand your expertise. Clickstream is just a small part of what it takes to understand web customer behavior.

- Common sense is greatly underrated (and under applied) when comes to doing analysis. It is important to be aware of its importance (and always remember the principle of Occam’s Razor).

- Get close to your marketers and website owners. Being close to the business will give you the key context that you need to 1) know where to focus your analytical efforts and 2) understand your data a lot better than you otherwise would.

- Read Juan’s blog religiously, it is very good!!

JUAN: What’s the best book you’ve read?

AVINASH: Growing up I was a voracious reader, the Indian mythology comics (Amar Chitra Katha – http://tinyurl.com/yrpgju) perhaps had the greatest impact on me during my formative years.

In terms of western books I read Ayn Rand’s The Fountainhead (http://tinyurl.com/29bv3u) when I was very young, and another three times over the years. It left a very deep impression on me.

————————————————————————

I would like to personally thanks Avinash not just for participating in this interview , which took a lot of his valuable time,s) but also for all what he does for web analytics. He is one of the people that is driving web analytics to the next level. I always say that I don’t think that some people are more intelligent than others, but more passionate, and Avinash has a contagious passion. He probably is one of the most passionate and dedicated professionals I’ve ever meet.

Thank you very much Avinash!

Juan Damia

How to define and optimize funnels

If you want to analyze any special process from your site with the funnel function here are some tips.

The first thing you should consider is that your site is a system, taking into consideration the very basic concept (wikipedia: from Latin systēma, in turn from Greek σύστημα systēma, is a set of entities, real or abstract, comprising a whole where each component interacts with or is related to at least one other component and they all serve a common objective), and as every system is extremely important to understand what things flows through it, how those flows occurs and how every part of the system is connected and interact with the others.

A funnel is nothing but setting up your analytics tool to track “part of your system flows” that’s why is important to understand first the entire system and its interactions.

So once you designed your information system (how the information flows through you site) you must identify “the must track process” within the analyzed system. How to do this? Identify from your critical path the tasks you will easily interpret if any deviation (from planned) occurs. Those indicators will became the sensors will indicate you which part of your system became your RCR (restricted capacity resource) or normally called bottle neck and then why your are or are not achieving your goals.

This will take you for sure more time than just setting up the funnel for every goals that “all the people normally track” but does it make any sense analyzing every part of the system as an isolated thing? I guess not.

Please don’t hesitate in contact me is you have any question or doubt.

Juan Manuel Damia (Web Analytics)

Google model. Formal Business, informal behavior.

This is a very Google like way to communicate when something is not working fine.

I’ll try to apply it with my clients…

Just in case you can´t visualize the text: “Google Trends is very popular right now and we could´t process your request please try again in a frew seconds”.

Google launched some feature improvements

Last month Google launched some feature improvements for their flamboyant Google Analytics version. Those improvements are:

- “Go to box:” This function is very usefull since it allows you to jump direct to an specific row instead of scrolling up and down. If you have 5,000 referring sources and you want to see row 3,456, you can jump right to it.

- The Map Overlay report view now defaults to Country instead of Subcontinent.

- Content reports now have a Segment menu so you can cross-segment pages and sets of pages by referral source, keyword, visitor type, and other visitor segments. This is very usefull if your site is composed by heterogeneous sections and wants it to analyze them as separted sites. Thanks Brett, very welcome stuff.

- Drill down function in the “top content” report. So if you want to drilling down on a specific title in the Content by Title report now is available letting you analyze and follow up URLs sharing the title.

Good to know they are hearing Google Analytics users and reacting.

Juan Damia (web analytics)

Microsoft Web Analytics the first real Google Analytics competitor

Last 09th of January Ian Thomas posted in his blog (Lies, Damned Lies… “The unpredictable world of online marketing and web analytics) a note called “the rumors are true, Microsoft ‘Gatineau’ exists” with he following disclaimer:

“None of the information in this blog post constitutes a commitment on Microsoft’s part to deliver any particular technology or service. Any and all of the information here is subject to change without notice”.

But what Microsoft Gatineau is?

Gatineau is the code-name for Microsoft’s forthcoming web analytics tool based on technology they acquired from DeepMetrix Corporation last year. Gatineau is the name of the Canadian city where DeepMetrix was based for a number of years. Final naming for the product is still unconfirmed. Continue reading →

Do you want traffic? You need a social network!

Social networks allow people to interact easily with people and share interests and passions. Internet knew how to capitalize this trend letting people to interact and generate content. The results it amazing, just take a look at Alexa´s top traffic websites.

Social Network

RANK	Web Site
1	Yahoo!
2	Microsoft Network (MSN)
3	Google
4	YouTube
5	Windows Live
6	MySpace
7	Baidu
8	Orkut
9	Wikipedia
10	QQ
11	Megaupload
12	Hi5
13	FaceBook
14	Microsoft Corporation
15	Yahoo Japan
16	Blogger.com
17	RapidShare.com
18	Sina
19	Ebay
20	Friendster
21	Fotolog.com
22	Sohu.com
23	163

Analytics 2.0

Much more than just tagging

Category Archives: Analytics Tips