Web analytics

Find here my latest thoughts and findings about Digital Analytics. #measure
What to expect? Articles, Thoughts and Tips about Digital Analytics Practice. 2 Areas of focus : Site Analytics – How-to measure your website performance, what to look for and why ? Media Analytics – How-to measure your media campaign performance? How each channel influence the overall upper and lower business objectives. 2 major tools tips: Adobe SiteCatalyst & Google Analytics.
Keywords: Measure, Attribution, GA, SiteCatalyst, Dashboard, Reports…

Develop your analytics skills ! 2014 and beyond challenges…

Develop your analytics skills ! 2014 and beyond challenges…

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Happy New Year everyone!

I wish you all the best for 2014, may all your dreams come true ! Days were slipping before the end of this month and the end of the new year wishing window although where I live today I do have an extension as Chinese New Year is coming pretty soon ; so this note will be short but still, I can’t start this year without this.

Who says New Year says New challenges and New opportunities, at least that’s what I want to hear. Last year, I had my Analytics roadmap for 2013 with 6 items :segmentation with personae, cross-platform analytics, analysis exchange, attribution modelling, site search and Tim’s Ash book to finish) , well as you can expect I didn’t cross all 6 items but some of them. I had the chance to participate to one project with Analysis Exchange for WWF Vietnam ; I read Tim’s Ash book about Landing page optimization, even though I still owe you a second post about the 2nd part and work on some pretty exciting analytics projects about campaign performance, site optimization, reporting enhancement among others subjects.

This year I’ll keep the same spirit : develop my analytical skills is my one and only focus and have fun doing it.
data-life
So 2014, here we are ! Where to start: 3 things that I am already excited about :

1. Kick starting today a new Analysis Exchange project

I am very happy to mentor this new project, hopefully I’ll share more with you in a few weeks.
Few words about Analysis Exchange :

2. Acquiring a new skill : “The Power to Predict”

I know this another 2014 buzzword word as many others, but I had the chance to participate to a “Data Analysis” course last year online via Coursera and touch-based a little bit about statistics, predictive modelling, R programming: how to organize a data analysis, the structure of files in a data analysis, how to get data, and the basics of how to clean data… This arouse my curiosity hence my challenge will be to firstly understand the basics of Data Analysis with a tool as R then using R to predict.

3. Working in Asia.

The last release of APAC DIGITAL MARKETING PERFORMANCE DASHBOARD – which look into the advancement of digital marketing across the Asia Pacific region – stated that 41% of the world’s Internet population resides in Asia, 78% of Asia Internet population in under 45, 69% of APAC marketers are measuring and testing digital campaigns and more importantly:

“In India, 28 percent of marketers rate their ability to measure the value and return on
digital marketing as excellent or very good, and Australia and Singapore also rank highly at 21% each. However, in comparison, Korea (3 percent), China (7 percent), Hong Kong (9 percent) and the rest of APAC (12 percent) are not yet as confident in their ability to demonstrate return on investment”

That is in my opinion a mine of gold from a learning, knowledge-sharing and skill improvement point of view. How exciting !

Hopefully, I’ll have new challenges and opportunities coming on the way ! You never know.

What about you ? What are your analytics challenges coming ahead? How would you develop your skills?

If you liked this article, please spread the data-love…

Adobe Analytics 1.3, what’s new ?! Classification enhancement !

Adobe Analytics 1.3, what’s new ?! Classification enhancement !

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Reading Notes: Please bear in mind that this blog post is for intermediate users of SiteCatalyst.

Wooooh a lot ! Mid July Adobe Analytics 1.3 went live and some expected stuff were launched at this time: a new UI, new segmentation capabilities in Discover, Discover changes name by the way – it’s now “Adhoc Analytics” and more importantly some new Classification feature : Rule Builder !

Let’s dig, for those who works with SiteCatalyst SAINT Classification for a while, this is purely awesome ! Not perfect but still best news ever. I was pretty excited when I first heard about the coming Rule Builder, as I was working (and still am) working on a media campaign reporting project with one of my client, this tool came in the nick of time. But let’s begin with some definitions and context.

What is SAINT Classification ?

SAINT is a feature in SiteCatalyst which allows you to categorize retroactively data that you captured. Generally speaking, if you have thousands of items captured under the same variable (such as the keyword variable or the product variable), you may want to categorize them into some groups to have a better understanding of those items interactions and performance.

When do you need SAINT Classification ? Real-life examples.

Product classification

If you own an ecommerce website, you’ll use SAINT classification to have a better understanding of your sales, optimize your upselling and cross-selling features for instance. SiteCatalyst will capture your product ID when a sale is completed, but if you just look at your report which a bunch of product ID you’ll certainly not get any insights from it.
Does this make sense to you ?

Does this make sense to you?
Does this make sense to you?

But if your product ID can be reclassified into meaningful dimensions then you can slide and dice and reports on something pertinent. Meaningful dimensions would be for instance to classify your product IDs:

  • by ROI type such as low/high/mid-margin product,
  • or by promotion-type buy 2 get one, 50% off, 2nd purchase offer…
  • or by seasonnality…
  • or anything which makes sense with your business.

For instance, some examples from others analytics fellas:

Copyright WebAnalytics Demystified
Sales classified by Key Promotion Dates – Copyright WebAnalytics Demystified

Classification dimensions examples for your product – Copyright Adobe Blog

This is the kind of reports SAINT enables you to get!

Campaign classification

Adobe Digital Distress Study
Campaign classification is one of the tool to help resolve those 2 issues “Understanding & Proving your campaign effectiveness”. When at the end of the day, you marketer, need to look at all your initiatives and decide which one was successful or not , which one engage your prospect enough to continue their journey in the funnel you decided for them.
By default SiteCatalyst enables to look at your incoming traffic by referrer type, then if you use tracking codes appended to your landing pages urls you can get more granular and breakdown by channel : PPC, SEO, OLA, Social… (learn more about campaign tracking and best practices in creating your tracking codes)
The ultimate is to get even more granular and classify your tracking codes by:

  • by campaign strategy,
  • by product category,
  • by creative type or message,
  • by publisher,
  • by CTA type…

and reports on your campaign beyond the channel dimension and not channel by channel as from a customer perspective the channels split do not exist. Hence you’ll be looking at how your CyberMonday, Black Friday, Christmas… campaigns performed against each other all channel mingled !
Weboptimeez, unified view of your campaigns
That’s what SAINT Classifications allows you to do! Getting a unified view of your campaign performance

What’s new with Rule Builder?

At the end, you’ll be able to do exactly the same thing and get the same reports. But you’ll be more efficient doing it and well time is money. Before Rule Builder your classification was to be done manually via an excel file such as the one below. You will manually input on each row the associated categories values to the tracking code captures and import it back into SiteCatalyst. This was time-consuming and also sources of mistakes.
SAINT excel file example

So here is the before, step by step to create classification reports:

  1. Thing ahead at your categories
  2. Create your classification menu with SiteCatalyst admin
  3. Download an example file with all the items listed (screenshot above)
  4. Classify them manually within excel
  5. Upload the file
  6. Done

Now with Rule Builder step 3 to 5 are combine into one step directly in Sitecatalyst interface: Classification Rule Builder. This interface allows you to create rules to classify your tracking codes/key. For instance when looking at the example above, I’ll enter a rule saying that if a tracking codes starts with aa70 then the Industry category will be “Financial Services” see below:
Capture d’écran 2013-11-30 à 15.24.47
Save it and done !

And this the after, step by step to create classification reports with Rule Builder

  1. Thing ahead at your categories
  2. Create your classification menu with SiteCatalyst admin
  3. Create your classification rules in Rule Builder
  4. Done

Find here some details about how to get the most of Rule Builder: 4 articles from Matt Freestone.

What about you, how do you use classification in SiteCatalyst ? Are you happy with the Rule Builder?

Why is data scientist the next sexiest job ?

Why is data scientist the next sexiest job ?

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You may have heard this statement over & over. “Data Scientist : the sexiest job in 21st century”

Honestly, to most people this doesn’t make any sense ; but when you start thinking about it and put your marketer/analyst/geek hat it’s starting to make sense.
Quite recently, one of my client told me

“I can’t believe I am saying this but yeah I am very excited at the sight of getting this report”

 

, hearing is this is sooo rewarding. Yes that’s true Data are exciting ! And I’m glad that from time to time, despite the data austerity first impression, I am able to communicate this to client, colleagues, friends…

Why is Data Scientist job sexy? From my point of view when I work at pulling data, cleaning them, finding the gem, organizing them, making sense of them, presenting them and finally turning them into action plan I feel like I am MacGyver & Sherlock Holmes & Lara Croft: ALL IN ONE !

  1. MacGyver because I am starting from a mess and tons of raw data and have to find a way to create a bomb with it.
  2. Sherlock Holmes because I am conducting a very serious investigation and need to rely on strong logical reasoning to avoid making false assumptions and solve the issue.
  3. Lara Croft because I’ll search and not give up until I find the gem and needless to say she is sexy…!
You got it, huh?

More seriously, I am not per say a Data Scientist as my background is mostly Digital Marketing related and I don’t have Mathematical or Science PHD or whatever but I always was keen to love math and solving riddles and today in brief my daily job is to ‘find the right data to capture, report & analyze it to allow better business making decision‘ hence in my ongoing research to improve those ‘data mining, data scientist, Business intelligence, data visualization…’ skills and find new tools to play with data, I came across those 3 books which I’ll advise for those who either are just curious about this job or wants to learn about the skills or start seriously digging into data.

  • Curious ?
    Read this one: “What is Data Science”In this very small book, you will learn about the general concept of data science with a nice orientation on ‘what for?’. In other word, why would any company need to use data science skills ? To create products. By products the author means real products or services for a client, e.g. Linkedin or Amazon recommendations feature. The author goes through the data science definition and scope, the data lifecycle 1. Data conditionning & cleansing or how to get to the point where the data you have are somewhat usable
    2. Data visualization or how to make your data tell a story and data scientist skills.
  • Want to know more about the job?
    Read this one: “The little book of Data Science”This book though concise will go more deeply into the concept of Data Science: concept, rationale, tools, applications & skillset. Starting with defining Big Data which is kind of a concept inherent to the data science, as in today applications the data captured are numerous, various & in movement, the author continues with the tools such as Hadoop the main programming platform used in this context: a Java-based programming framework that process data used by Google, Yahoo, EBay, Linkedin… The book goes on with more details about the data lifecycle as well: data cleansing, structuring, modeling, prediction, visualization, correlation…
  • Serious about digging into data?
    Read this one: “R in a Nutshell”This book is “a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.”
    This book is going to be my bedside book for the few weeks coming and in preparation for my Data Analysis course this winter… Looking forward sharing this experience with you !

Well, I certainly hope you’ll enjoy them as much as I did !

Also, for those who really don’t like to read ; here is an interesting video from Edel Lynch who is working in one of Accenture Analytics Innovation Center – her background is much more scientist but at the end the skills she described as essential to a data scientist / analytics role are: math, solving problem abilities, communication & business acumen. Watch by yourself, from 0:40 to 1:56 she is focused on the power of Analytics ; from 4:41 to 5:43 she is focused on skills & talents required for a career in analytics

I don’t really know if it make sense to say that this set of skills or this job is the sexiest to be, even though I quite understand the thrill of it and the demand for it. Anyhow, the possibilities are endless and from my point of view I can’t see a best career path.

If you liked this post, don’t be shy, spread the data love…

Data Analytics challenges in the real world

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Happy Friday !
A short insightful video from McKinsey about are the challenges for businesses with data analytics and what to make of it ? Big data challenges: volume, velocity & variety and also determining which data to use: defining your measurement strategy, broaden your methodology to include external data such as competitive data, markets data… how to visualize those analytics data to facilitate their usage & communicating to stakeholders to act upon it !
In summary:

Turning your pile of data into actionable insights to make the difference among your industry!

A lot to cover, that’s why our job are so exciting !!!!

My previous articles about this topic:

Analysis Exchange, a great initiative for Analytics passionate and non-profit in need!

Analysis Exchange, a great initiative for Analytics passionate and non-profit in need!

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If you are passionate by Web Analytics and willing to give some of your time for a good reason, please continue reading and hopefully I’ll convince you to sign up as well !
I took the great and challenging opportunity to sign-up as a Mentor for the Analysis Exchange and participated to one project so far for WWF Vietnam.
What is the Analysis Exchange?

I signed up in July 2012 and finally participated to my first project recently. The project was with WWF Vietnam website that we helped to ensure that their analytics platform – Google Analytics – was properly set up and we tried to guide them into taking the most of it.
As a mentor, I tried to give guidance to Trish – the student – who was very involved and willing to provide the best to WWF Vietnam. On the first meeting with WWF Vietnam, we* came up with a simple project plan to define WWF Vietnam objectives in this project, our objectives as analytics consultant and deliverables they could expect from this project.
*By we, I mean Trish and myself knowing that Trish did all the hard work, I was here for her when needed and to give her advice and guidance in the way to approach this project and some documentation as well.

For privacy purpose, I will not go into too much details about WWF Vietnam expectations, however the project objectives were the following:

    • Ensure appropriate configuration of current Google Analytics tracking tools
      Identify key traffic metrics to be gathered, analyzed now, and monitored in the future
      Provide insight into Analytics data for WWF-V team moving forward

    • 3 main deliverables came out of this: we started with a 1) technical audit to understand their Google Analytics configuration and take this chance to help them configure some customized variables to get a better grasp on their users’ engagement against their content.
    We then configured for them 2) a dashboard displaying the key metrics and following a straightforward “visitor journey” structure and answering to their main business question.
    For instance:

    Lastly, we configured for them 3) two custom reports, one focused on the traffic sources performance and the 2nd one focus on their article performance.

    About the experience in itself, here is what I would bare in mind for the next ones:
    Pitfall : Timing and Scope
    Before participating to this project, I read another article where the writer, speaking of his past experience in the Analysis Exchange, encountered the same issue for his project. Even though the project is supposed to last around 3 weeks and even though I was aware of this possible issue, we end up spending around 2 months on the project.
    Why? It would be a fair guess to say that the issue was coming from a too large/vague scope which I should have notice and reduce from the beginning. However, at the end our project didn’t fail, we just spent more time than expected at the beginning.

    Tips for success: Communication
    – Good relationship with the student and the organization
    – Allow regular time to discuss with the student
    – Review and agree on the scope with the organization to make sure that the work scope stay reasonable
    All those items turn around Communicate, Communicate, Communicate!
    If there is one thing, I’ll do differently for sure next time, it will be to make sure that the organization stay in the loop all along the way and engage them even though they are not very active.

    Aside from being pretty happy to have one of my action item from my 2013 Analytics roadmap achieved, it was a really interesting and rewarding experience that I look forward to renew ! And again, if you have the time and desire, sign up 🙂

    Why should you sign-up?
    Student: It’s a great opportunity to have hands-on experience on analytics and support from experience analytics professionals and your resume will certainly not suffer from it !
    Mentor: No need to emphasize a lot, as soon as you are passionate I guess it just make sense to spread the love…
    Organization: A great, great, great opportunity for FREE to get insight on your website, understanding users behavior and get some sense of what could be optimized, what is already working very well, where the budget should be spent…

    Want to know more? Need inspiration, Documentation for a Non-Profit measurement framework?
    – Analysis Exchange Website
    – Analysis Exchange Blog
    – Analysis Exchange Twitter
    – I just ran into this fantastic post from Justin Cutroni which bring grist to my mill: “Measuring the Non-Profit: From Planning to Implementation“, in the nick of time!