Top Ten: Signs You Are A Great Analyst

focusI am often asked what we look for when we hire Web Analysts or what quality do good Analysts possess or how to measure if a resource that already exists is optimal or how to mentor / motivate / guide our more junior Analysts to propel them to become great Analysts. This blog post is an attempt to answer all those questions wrapped into one.

We all agree that reporting is not analysis. We all agree that great analysts are hard to come by and few and far between (yet it is interesting that people disagree with the 10/90 rule and keep insisting on spending money on tools). So what makes a great analyst? Do you think you are a “great” Analyst?

Here is my personal point of view, a check list if you will, on what makes a great Web Insights Analyst (it is important to caveat that this is not me, I only wish I were this good, this is something I aspire to be) :

    # 10 You have used more than one Web Analytics tool extensively.
    While each tool is the same in our field, each tool is really different. The way Omniture computes Unique Visitors is very different from ClickTracks, or how either one of them handles sessions. Using different tools gives you a broad perspective on how the same thing can be counted ten different ways and at the same time a rich understanding of why some tools are great and some sub optimal. The interesting outcome of a diverse experience is that a great Analyst can work with any tool and yet find meaningful insights.

    You don’t have to be limited to what you have at work. If you do a View Source you’ll see that this blog is measured using MapSurface, Google Analytics, ClickTracks and AnalogX (so tagging and web logs and real time data and a paid and free tool, great for learning).

    # 9 You have not only heard of the Yahoo! Web Analytics group but 20 mins of each day is spent reading all the posts.
    The Yahoo! Web Analytics Group is the most awesome collection of smart people in our industry who share their wisdom on every topic under the sun that touches our world. I personally read all the posts every day and I learn about challenges others are facing, innovative ways to solve those challenges, general trends in the industry, pointers to the latest and coolest happenings that impact us and on and on. There are& repeat questions, the interesting thing is that even those get different answers all the time.

    # 8 Before doing any important analysis you visit your website and “look” at the web pages (site experience).
    This one probably sounds stupid. But it is amazing how many times, how many of us, simply look at tools and numbers and data but often have no idea what the website looks like. It is impossible to analyse the data without a solid understanding of the customer experience on the site, what the pages look like, where the buttons are, what new "great" navigation change went live yesterday. A great Analyst stays in touch with the website and the changes constantly being made the the designers and marketers on the website.

    For example: Great Checkout Abandonment rate analysis is powered by actually going through the site, adding to cart, starting checkout (using all options available), going through checkout all the way and getting a order confirmation email. Then you will look at numbers in a new and more meaningful way, I assure you that you will then not have to torture them for insights rather they will sing to you.

    # 7 Your core life approach is Customer Centric (and not Company Centric).
    In the morass of data quality and TV and UV and cookie values and ab test id’s and sessions and shopper_ids we look at massive amounts of data and forget that real people are using our websites. Great Analysts have a customer centric view that makes their mind a lot more amiable to think like customers, all 1,000 segments of them, and you are aware of their personas and challenges (this is awesome by the way for data segmentation). This keeps you grounded in realityand will help you apply Occam’s Razor (because data trends and patterns without a "customer mindset" will always complicate thinking).

    A great Analyst is capable of descending to the Customer level from the "analytical heights" and help her/him to move forward (because customers can't fly).

    # 6 You understand the technical differences between page tagging, log files, packet sniffing & beacons.
    This is specific to Web Analysts. How data is captured is perhaps the most critical part your ability to “process” the data and find insights. Each data capture methodology comes has its benefits and dangerous negatives. You understand hard core the technical differences between each data capture methodology and then appropriately adjust the kind of analysis you do and the value you extract from whatever your company uses.

    # 5 You are comfortable in the quantitative and qualitative worlds.
    Clickstream, on its best day, should be the source of 35% of your data. Rest comes for site Outcomes or Qualitative data (the Why, see post on qualitative data). Great analysts are just as comfortable in the world of parsing numbers as the “open ended / ambiguous / soft” world of observing customers, reading their words, inferring their unspoken intentions, sitting in a lab usability study to glean insights etc.

    You have a inherent ability to hear people and their problems and all the while in your brain you are thinking of 10 interesting ways in which you can slice the Site Overlay or other clickstream metrics to validate. Great analysts follow a slide on core clickstream / outcomes KPI’s with a slide on Segmented VOC Pareto Analysis.

    # 4 You are a avid “explorer”.
    Reporting is straight forward. There are inputs, outputs, KPI’s, tables and rows. Analysis is not, it has no predefined paths to take, it has no preset questions to answers. It requires having a open mind, a high level of inquisitiveness and after hearing a ambiguous business questions a deep desire to find new and better ways to use data to answer those ambiguous questions. You don’t worry about the if and how it will work, you save that for later. You seek out possibilities and the non-obvious.

    When faced with “incomplete / dirty” rather than think of all the reasons why you can’t analyse data you make reasonable assumptions and can find a nugget of gold in a coal factory. A vast majority of us fail at this, we face bad or incomplete data and we get paralysed. Framed another way you are really really good at separating Signal from Noise (be it using data segmentation, using statistics, using common sense, understanding your customer segments, or other methods).

    # 3 You are a “smooth talker”.
    In our world Analysts rarely have the power to action things or implement recommendations. Great analysts are great communicators, they can present their message in a very compelling easy to understand manner, and  be a passionate and persuasive advocate of company customers / website users. The 15 hours of complex multivariate statistical regression model analysis is hidden, they keep ego aside, and tell the “simple minded” decision maker that the changing product content presentation will have the highest correlated impact on revenue. They are just as comfortable talking to technical folks as presenting to the VP of xxx or yyy and selling either one of them a boat that they don’t need.

    # 2 You are “street smart”.
    Great analysts are not “theory sprouting making things complicated and much harder than can be in the real world types.” Think Occam’s Razor. They have oodles and oodles of common sense and a inherent ability to degrade a complex situation to its simplest level and and look at logical possibilities. This does not mean they can’t look at complex situations, on the contrary they have a awesome ability to absorb complexity but they are also scrappy enough to look through the complexity rather than end up in rat holes.  They know how & when to keep things simple.

    (The original version of this was: You are Business Savvy. I think that is a incredibly hard quality to find, even harder to judge in a standard interview. Yet it is perhaps the one thing that separates a “report writer” from a “analyst”.  The ability to see the big picture, the ability to understand and solve for strategic objectives. But in my own experience I have found that people who are “street smart” inherently have this ability and hence the framing of #2 as you see above.)

    # 1 You play “Offence” and not just “Defence.”
    Most of us in this field play “Defence”: we supply data or we provide reports or we at times provide dashboards. Mostly we react. But we don’t play “Offence”:  we don’t get in front of the business and say this is what you should measure, we don’t reply to the question “show me what the tool provides” with “tell me your strategic objectives and I’ll tell you what insights I can provide with the data I have”.

    Great analysts spend 30% of their time looking at all the available data just to look for trends and insights, time they don’t have and doing things that no one asked them to do. But that 30% of the time that allows them to play Offence, to provide insights that no one thought to ask for, insights that drive truly impactful actions. You do it because you realize that you are smarter about the site and data than anyone else out there and you do it because it is a lot of fun. :~)

This was supposed to be a Top Ten but here is a bonus:

    # 0 You are a “Survivor.”
    The reality of the world of our web decision makers is that most of them just want to measure HITS (KD Paine's definition of HITS: How Idiots Track Success). The other day someone asked me to give them a "Site Counter" to put on the website for measurement, I am sure you have not heard the words Site Counter to measure anything in the last few years.

    A key skill of being a great analyst is the ability to have patience, survive and stay motivated in a world where people might ask for sub optimal things. Of course you know better but transforming perceptions is a very hard job and take a long time. But you are a survivor, except the part about a million dollars in the end! ; )

This is how hard it is to be a great analyst:

  • If you meet five of the above criteria you are a good analyst and you are on your way to greatness.
  • If you meet eight you are a great analyst. Congratulations (please send me your resume!).
  • If you meet all ten (or 11) criteria then you my friend are a Purple Squirrel and I bow in front of you (oh and most surely send me your resume!!!).

Agree? Disagree? Would you have not included something above? Ranked something differently? Did I miss something all together that you value?

Please share your feedback and your own submissions via the Comments form below. If I get enough different ones I’ll create a new list and publish that (with due credit to you).

(Tip of the hat to Michelle, Oleg, John and Steven. You guys rock!!)

Comments

  1. 1

    Avinash,

    You are far too kind! It's well past midnight and I'm too fried to respond to the full post (altho I suspect I'll agree with you largely) but I noticed the traffic in my referring domains report (yeah, I watch that, go figure!) and I had to see what you said this time. Brilliant as usual!

    All the best,

    Eric T. Peterson

  2. 2
    LarsJ says:

    Avinash,

    There are maybe five web analytics blogs that are essential to subscribe to and I'd already say that one should subscribe to your blog first of all! It is important to stress the importance of people and you're doing a good job at it. I think many companies are trying to save money by cutting back on the time spent on web analytics. Then all they get are reports..

  3. 3
    Mike Samec says:

    I think you can add to point #3, 'educator.'

    An educator needs to be able to teach, communicate and must have patience. Few people really "get" the marketing process let alone understand Web analytics; the tools, the reports, how to read the reports…many are still stuck on 'hits' as you mentioned.

    Site counter? Really? Did they want you to also include a guestbook for people to sign :)

  4. 4

    Mike:

    ….you can add to point #3, ‘educator.’

    I agree on that completely. I should have added evangalist as well. What I find is that people are absolutely open to learning and evolving but we all have to do a better job of educating (of course I hope you consider my three UBC lectures as me doing my part!!! : ))

    Thanks for taking the time to comment Mike.

  5. 5
    Sean Fraser says:

    My suggestion for Item 11, "You are a Data Analyst". Data must be collected from clients and client-competitors alike. Tools give one statistics; site review gives one clues Statistics + clues = data.

    And, I would adjust Item 3 "…and not selling either one of them a boat that they don’t need." "Smooth Talker" – for me, anyway – connotes Shyster.

    It's a comprehensive checklist, you have. It's interesting reading this list in a Mix-and-Match fashion: it articulates what methods should be employed for the scope of a project.

    Item 10 and Item 9 are similar in that – to me – they are both tools. Item 7 and Item 8 blur because they should be commonsense to analysts. Items 1 -3 blur because they are mutually inclusive.

    Perhaps, No. 12 could be "You are somewhere between W. Edwards Deming and Richard Feynman". :)

    Are you penning a TopTen Signs for Shyster Analysts?

  6. 6
    KathyJ says:

    Great Analysts have a customer centric view that makes their mind a lot more amiable to think like customers

    They can also put that information across in a way that mmakes sense to the "doers" in the company who will actually take action on the information.

    My job is a little different from web analytics, but I work as a stock insight analyst for a large retail company and one of the hardest parts of my job is explaining to the high ups why that particular element of customer psychology relates to the data that I'm reporting. My favourite was trying to diplomatically explain that a customer will switch from one bread bran to another if one is on promotion when it's the same variety of bread in question. I swear that most of those high ups have never actually done their own shopping, so have no idea how the average customer actually thinks when they're traipsing round the stores.

  7. 7

    Maybe I have maybe get 5 out of the 11 points down pat. I'm curious how different analysts would solve this question:

    A large corporation with operations all over the world monitors its search traffic and one month noticed the search referral traffic jumped 3%. The analyst does not speak the language-btw. How would you trace, using web analytics – the actual cause of the increase of traffic down to the specific campaign(s) and company promotions that caused the increase of search referral traffic? The search referral traffic was from Japan.

    I'm curious to know how different analysts would solve that problem? I'm also wondering if the 10K tool would work as well as the 100K for that kind of question?

  8. 8

    Marshall (aka Webmetricsguru): I'll take a bite. There is not enough information in your comment to really give you a perfect answer. But it is extremely clear that both the 10k tool and 100k tool (and I even say free google analytics or clicktracks apptizer) will give leave you equally handicapped.

    The reason is Data Capture.

    If your client site received this surge in traffic due to PPC then each tool would have captured campaign identifiers the same way (or not at all). In which case you find source or not. So try to see if you can learn something doing a ppc campaign query.

    If the surge was due to SEO (Organic) then again all the tools capture the data the same way. A million dollar tool will process the google q parameter (with the search phrase) the same way as the free guy. So try to see if the key phrases by search engines has any insights for you.

    If your client did not do anything to cause search traffic like showing a TV ad then I would look at google trends as well (see if there is anything like press releases).

    If not that, if you have access to HitWise which we do, check out if the competitors website has done some promotions or campaigns or press releases and maybe there is a halo effect.

    Finally don't forget blogs and our dear friend technorati, mine the blogs to see if there is any "buzz" there becuase even small buzz can cause a 3% spike (oh and 3% on most sites, except say IBM, might not even be statistically significant, you should check that first: is it significant and from your comment it sounds like it is).

    Bottomline: There is nothing in the expensive tool that could make it smarter in a dumb data capture environment. The sole difference is they might have some extra bells and whistles to present the data better or create a extra slice or two.

    Please post your comments on this. I encourage the readers of this blog to take a whack at your problem or my thoughts above.

    Thanks for posting Marshall, always welcome.

  9. 9
    Sean Fraser says:

    I agree about Data Capture and expensive tools. Though, for me it always falls to the analysis of 10/90 Rule.

    The 3% spike may have been caused by past marketing campaigns (especially with new products/new technologies which take numerous weeks for a buzz to develop). Always consider historical data. On what pages from search referral traffic do the spikes occur? What pages showed daily traffic increases? What were the search phrases? By viewing those three data sets, one may be able to deduce a reason for the spike? My question to Webmetricsguru, what sort of spike? 3% in a single day? 3% over several days? An aggregate of 3% over thiry days?

    Expensive Tools are expensive tools. Analysis isn't.

  10. 10
    Manoj Jasra says:

    Very interesting list,

    Coming orginally from a technical background (software development) I find that the hardest skill for me to achieve was good old business common sense. I think that this type of skill comes from experience and really looking at things from a customer centric perspective.

    This skill separates implementation specialists from analytics consultants/analysts.

  11. 11
    Jim Novo says:

    Great list, awesome.

    "Shoes of the customer" we used to say when looking at the data. Who are they, and what were they thinking? And once we have an idea of who and and what they were thinking, is there a way to test if we are right?

    I find the great analysts are those that can come up with a "thesis" based on the data, which they then can turn into a test of the thesis. Unfortunately, many analysts think that part is somebody else's job on the business side.

    Most of the great analysts I have ever met also had one common trait outside the expected kinds of business things above – they knew how to read music, typically because they learned to play an instrument when they were younger.

    How many people reading this blog also can read music?

  12. 12

    Jim: You might be on to something, reading music. That could also explain why I might be good at this, sadly I never learned to read music or play a instrument (well other than air guitar at which I am quite good!! :~))

    Thanks for the kind words and taking the time to leave your comments.

  13. 13
    Jim Anderson says:

    Avinash,

    Great post, very informative and speaks to my environment real time. I consider myself fortunate to have worked with (albeit briefly) both you and Mr. Peterson. When you guys talk, I listen.

    I believe your reference to Eric's Yahoo! Web Analytics Group and the importance of knowledge sharing will be one of the keys for me trying to go from good to great.

  14. 14
    Fred Kuu says:

    I wonder if I should start using a pseudonym when posting on the Yahoo! Group just so folks don't confuse me with the infamous fred.

  15. 15
    Oleg Zhukhovitskiy says:

    I would add "… and never frustrated seeing the gap between what he can do and what business can understand at the moment".

  16. 16

    I've just discovered your fantastic blog. I wish I had had this when I was working on web analytics at PayPal. Now that I'm on my own in a smaller company, I'm hungry for the knowledge that experienced leaders like you are providing in the blogosphere. Many thanks!

    To this great list above, I'd add the following:

    * Thinking like a business unit owner, especially when implementing solutions. One has to understand how the business looks at and thinks about the data to implement a content architecture that is actionable and easily understood from the UI or in the custom reports.

    * Vision/Optimism. The ability to look a few years down the road and see where Web Analytics can take a business. This allows analysts to remain optimistic, even when asked "why don't our metrics match Media Metrix's scores?" for the 20th time.

    Best of luck on your quest for the Technorati top 10,000!

    Melinda Byerley
    Senior eCommerce Marketing Manager
    iWin.com

  17. 17

    Hi Avinash,

    I recently discovered your blog.

    This piece could easily fit in a best selling BI book. Interesting choice of words:

    "inherent ability to degrade a complex situation to its simplest level"
    "play “Offense”"

    You have selected a balanced mix of business and technical skills.

    Enjoyed reading your post.

    K

  18. 18
    Shree says:

    Avinash,

    Great Post! I feel that you brought out a lot of points that we always felt but never surfaced. My two cents ..

    I think an analyst(not just web analyst)who is in internet and marketing field should above everything know how to present his findings to his audience. When I first joined a company after grad school, I struggled why people did not get my analysis (I use to spend hours touching and making sure all strategic points are well covered). I spent hours perfecting my "analysis" but at the end it really did not pay off..It was only when I took an opportunity with another company that was more sales oriented research I realized what was it I was missing in my earlier job. As you mentioned "decision makers" or "creative minded marketing folks" do not think as deeply as analysts do – They need something simple, spoonfed and quick and that is where one presentation skills come in. I started perfecting that and I already feel that I am getting the response that I always desired…

    Keep the ideas flowing fellows.. I just joined this blog but feel this is the best group with some very bright folks with interesting ideas..

  19. 19
    Rohithpras says:

    Great notes to read, I have been spending some time reading you blog posts. surely there is a long long way to go for the people to understand the importance of web analytics and also the analysts.

  20. 20
    Bhupendra says:

    I totally agree with you Kaushik. But I have a question for you.

    Is the number given to each point with one more important than the other or it is just the serial number?

    I would give highest weight to "understanding of customer needs".

    Also, I feel a good analyst need to know his competitors well. He should first find who are the other players in the industry and among them who are potential competitors. He needs to know the position of his company's offering w.r.t. the other similar products in the market. In addition to it, he needs to analyze competitors website and find the trend of evolution with time. By doing this he will be able to predict the future change and make counter moments early.

  21. 21
    Ankur Mody says:

    Hi Avinash, this is the first blog i have ever subscribed to. You are doing a wonderful job. Carry On.

  22. 22
    hiutopor says:

    Hello

    Very interesting information! Thanks!

    Bye

  23. 23
    Jeff Noethen says:

    Hi Avinash,

    Loved the blog, though it appears I am about a year and a half late in responding! I can't agree with you more about your top ten signs of a good analyst. I can honestly say that I meet 8.5 of the 11 (including bonus). Unfortunately, my company only uses one analytics tool, and, while I'm signed up on the Yahoo analytics group, I rarely participate and/or read through the discussions. Additionally, I have never taken a statistics class, so I can't say that I have mastered the quantitative side of analytics. However, the tools that I have along with my excel skills make up for what I lack in actual statistical experience.

    I personally, come from a mindset that the quantitative should only back up what the qualitative infers. In other words, I enjoy getting into the customers mindset first and trying to understand how they physically interact with the site, and then use the data to prove my instincts.

    Anyway, again, this is great stuff and I look forward to reading more of your (more recent) blogs!

    Thanks,
    Jeff

  24. 24
    Jeff Noethen says:

    I should probably clarify, we have several other tools that we use to measure other pieces of the puzzle but we only use one "analytics" provider to track KPI's on the site. This is mostly due to the vastness of our site.

  25. 25
    Matt Gershoff says:

    Good blog. I think points #5 through #2 are really about the ability to construct a meaningful narrative and the ability to tell it as a compelling story to the appropriate audience.

    One thing I wince at just a bit is the assumption that you can find "a nugget of gold in a coal factory.' Sometimes there is only coal in that factory and finding any gold is only self deception. While it is important to think creatively about problems it is equally important not to ‘see’ signal were there really is only noise.

    Thanks

    Matt Gershoff

  26. 26
    Kris says:

    Hi Avinash,

    These "top ten signs" are great reminder for us analysts to review the competency required to do our job. I think this post goes well together with the other post you wrote "How to Excite People About Web Analytics", since these ten signs will definitely support making your business folks move forward or get excited.

    Reason I brought this up is, I personally feel challenged regards to exciting the business to take action based off the actionable insights. There are several signs you mentioned such as communications and playing offense, these are things that I feel web analysts are even more challenged, since we need to justify the return on investments on those analytics tools.

    Once again, thanks for this great posts! I am always reminded from your posts on many fundamentals that we live with, but sort off buried in our daily tasks.

    Thanks,
    Kris

  27. 27

    Avinash:

    Many of the methods you outlined are still widespread in practice, even 2 years later. I wish I had the same passion for analytics as you do, but my passion is more on the organic side rather than delving deeply into the results.

    As a rule, I typically cross reference 2-3 analytics tools to find a cross section of data to extract. I have clients who have click tracks installed and I am not particularly fond of the way it splits each page into multiple near duplicate ids, just for the sake of measurement. When the process of finding tangible benchmarks crosses over to an SEO liability, does the tool warrant its use?

    I particularly enjoyed #8 about shopping cart abandonment, it is easy to get lost in the numbers and forget the gist, the human element.

    Amazing how doubling conversion doesn't have to imply doubling traffic, just minor tweaks with the right trigger for emotional staging.

    In any case, I look forward to studying your posts for further insight, since you cannot have one (SEO) without the other (analytics) and the ability to measure it.

    All the best.

  28. 28
    büyü says:

    I personally, come from a mindset that the quantitative should only back up what the qualitative infers. In other words, I enjoy getting into the customers mindset first and trying to understand how they physically interact with the site, and then use the data to prove my instincts.

  29. 29
    Angela Beggs says:

    This applies to me as an analyst and I don't work in web analytics. I am a research analyst and work on the buyer side.

    I am so glad I read this because to be honest sometimes I wonder why I try so hard to have people buy into some of the ideas for projects that I have.

    I often play offense; I have made a lot of headway but at times get discouraged and feel that management are not asking the right questions. When I offer my insight – it can be a battle. I was actually thinking about a career change, but the fact of the matter is I am a good analyst. I just need to learn how to communicate the reason for smart objectives – to get buy in.

    Thanks for the post – I needed a reminder that I am in the right career. I am an extrovert too; it can be tough to sit at the computer all day.

  30. 30
    Roman says:

    Great read, often question myself and go through the mental torture of asking myself how good I am.

    I followed an unusual route in to web Analytics having studied IT, went in to sales, run an SME business and I am now an Optimisation and Insight Analyst in a corporate business.

    Coming from a non corporate/technical grounding I am amazed at how badly people operate in the digital space but then I wonder if it is just me, do I not get it?

    • 31

      Roman: You most probably get it. Digital analytics is definitely a tough space and I do believe that we have a bit more than our share of posers. But a part of it also is that most companies are run by people who are stuck in a world from 20 years ago in terms of the possibilities they think exist in marketing and measurement.

      You wanted to measure yourself and evolve…. checkout this blog post. It outlines my view of what an analysis ninja should be, and in the small chance that you are not there already then what to do about it:

      Web Analytics Career Guide: From Zero To Hero In Five Steps!

      Good luck!

      Avinash.

Trackbacks

  1. […] Avinash Kaushik has another excellent post about the topic of what makes a good metrics analyst.  The mix is a great balance of what I usually called curiosity, intuition, exploration and customer-focus.  Avinash creates a neat Top 10 list with the aspects of great analysts.  I can’t agree more with this list, as my #1 was his was #4.  You have to be an “explorer”. […]

  2. […] Occam’s Razor by Avinash Kaushik » Top Ten: Signs You Are A Great Analyst "I am often asked what we look for when we hire Web Analysts or what quality do good Analysts possess or how to measure if a resource that already exists is optimal or how to mentor / motivate / guide our more junior Analysts to propel them to become grea (tags: webanalytics careers) No Comments […]

  3. […] Want to know what makes-up the perfect web analyst? Avinash has put together a list of key traits to look for in a web analytics specialist. […]

  4. […]Leuke vraag, want de experts schieten als paddestoelen uit de grond. Logisch, want er is ‘business’ te halen. De aankomende jaren zal de vraag naar de echte expert alleen maar toenemen. Hieronder wat punten waar je volgens WA expert aan zou moeten voldoen (special thanks 2 Avinash): […]

  5. […] Almost about a year back, blogger, consultant and Web Analyst Avinash Kaushik, in his Occam's Razor wrote about a very interesting and informative topic on identifying a great Web Analyst. It was a very well composed writing in which he had narrowed down his experience down to a check list of 10+1 points pinpointing out the virtues of this breed. He also speaks about a 10/90 rule which is on the same line as the 80/20 rule much spoken of with regard to McKinsey'ites. Along with his insights, there are also the comments which tries to fill in any thing which he might have missed or his readers felt should have been there in the check list. Though the article was posted way back in June '06, its still effective and good to read. Surely among the entries in his check list one can find mentions about Web Analytics tools used, technical know-how's and the Yahoo! Web Analytics group but there's more to it that deserves a read and thats why I consider it as a winner. […]

  6. […] more difficult to find quality web analysts. Avinash Kaushik posted a while back about the "Top Ten Signs You Are a Great Analyst". The post made it's round and people all over the world left great comments like this […]

  7. […]
    Do you prefer to have a nice, clean, and pleasant place to live; or a real mess where you can’t find anything? For a web analyst, it’s easier to get those skills when you’re in category #1.

    Well, your Google Analytics account is like your home. OK I might exaggerate a little bit, but you got the picture! Profiles should be well organized for several reasons:
    […]

  8. […]
    The situation with Marketing Automation reminds me most of Web Analytics. In the early days, Web Analytics was touted as the tool that has all the answers. But as Web Analytics guru Avinash Kaushik described, the 10/90 rule applied: for every dollar you spend on a tool, you need to spend 9 dollars on analysts to get the most out of the tool.

    If you believe in the 10/90 perspective, it’s suddenly much more important to hire the right people. Avinash has great advice for that in his Signs You Are a Great Analyst blog post. But that’s for web analysts. Let’s try to get a similar list for Marketing Automation managers.
    […]

  9. […]
    Not surprisingly, Google adapted (yet another reason to avoid costly software licenses). Log into Google Analtyics (GA) today, and you’ll see multi-channel conversion funnels, social events, and much more. The truth is that we, as analysts, have a lot more learning and testing to do. While we’re capturing more of the information, and even beginning to find ways to process it, we’re still a far way off from connecting customer behavior tightly to business and marketing strategy because of the sheer complexity and mixed-media environment that our constituents live in.
    […]

Add your Perspective

*