The 10 / 90 Rule for Magnificent Web Analytics Success

orchid.thumbnail Numerous studies have pointed out that while almost all Fortune 500 companies have great investments in "Web Analytics" they still struggle to make any meaningful business decisions. Most people complain that there are tera bytes of data and giga bytes of reports and mega bytes of Excel and PowerPoint files. Yet no actionable insights, no innate awareness of what is really going on through the clutter of site clickstream data.

Through my humble experience in this field I have developed a rule to fix this problem and achieve Magnificent Success. I call it the 10 / 90 rule. Here it what it says……..

  • Our Goal: Highest value from Web Analytics implementation.
  • Cost of analytics tool & vendor professional services: $ 10.
  • Required investment in "intelligent resources/analysts": $ 90.
  • Bottom-line for Magnificent Success: Its the people.

The rule works quite simply. If you are paying your web analytics vendor (Omniture, WebTrends, ClickTracks, CoreMetrics, HBX, etc) $25,000 for a annual contract you need to invest $225,000 in people to extract value from that data. If you are actually paying Omniture, WebTrends, HBX etc $225,000 each year then…. well you can do the math.

Most people reading this post probably think this is way overblown or silly or just plain stupid. I can understand that. Here are some of the reasons I have come to formulate this rule:

  1. If your website has more than 100 pages and you get more than 10k visitors a month you can imagine the complexity of the interactions that are happening with your website. Drop in marketing campaigns, a dynamic site, SEM, more pages, more traffic, promotions and offers and you have a very tough situation to understand.
  2. Most web analytics tools will spew out data like there is no tomorrow. We seem to be a rat race, one vendor says I can do 100 reports, the next says 250 and the one after that says I can measure the eye color of people who look at your web pages and on an on. Bottom line is that it will take a lot of intelligence to figure out what is real in all this data and what is fake and what, if anything in the canned reports, is meaningful in all this.
  3. It is a given that if you open most web analytics tools that they show the exact same metrics, almost all of them measured and computed differently! You are going to have to sort this out.
  4. Finally actionable Web Insights (or as I have now copywrited: KIA's, key insights analysis) does not come simply from ClickStream, you are going to have to have people who are smart and have business acumen who can tie clickstream behavior to other sources of data / information / company happenings.

A part time person, or your admin, providing access to your favourite expensive analytics tool can't help your management make actionable decisions.

So if you think your company is not following the 10 / 90 Rule then here is my humble recommendation for you to consider:

  1. Apply for a free Google Analytics account at GA Sign Up Page
  2. Once you get the code implement Google Analytics on your website in parallel with your favorite expensive analytics tool
  3. Get a comfort level for delta between the two sets of key numbers (you know visitors, conversions, page views etc etc) and create a multiplier (my tool shows visitors 10% higher and page views 10% lower than Google). You will use this multiplier in future to compare year over year trends if you want to.
  4. Cancel the contract with your favorite expensive analytics vendor and take that $50k or $100k or $200k and: 1) Hire a smart analyst for between $50k to whatever maybe your areas great salary 2) Put the rest of the money in your pocket.
  5. Your smart analyst will be able to extract just as much value from GA than your old tool, in fact my prediction is that it will be a lot more.
  6. As the level of savvy in your org grows, as the level of sophistication of supporting processes increased, perhaps in two years you might be ready to plunk down $200k on a web analytics tool and then be ready to extract a corresponding amount of value from it.

The cool thing about the recommendation above is that even if you get to Step 3 you can walk away, no harm no fuss and you would have learned something. But I hope that you will go through all the steps and provide folks like me with employment and add strategic value to your companies by providing actionable insights rather than reports.

Agree? Disagree? Feel like I am posting from la la land? Please share your feedback via comments.

Comments

  1. 1
    Andy Beal says:

    Totally agree. There is so much data contained in GA reports alone, that any company serious about their business should assign/hire someone to analyze all this precious data.

  2. 2
    Andrew Hood says:

    It would be rude of me not to start with a bias confession: we sell and market a web analytics tool.

    That aside, in many ways I agree with the notion of a 10/90 split (regardless of the tool), but I'm not convinced that "analyst" covers the real role of the 90 for most organisations.

    "Actionable Insights" are great, but at the risk of stating the completely obvious, even more important is actually taking some action.

    So, for every insight generated, you need human resource with the time to modify the campaign, change the buying process, fix the call to action, provide more customer support information, adjust the pricing — whatever. There's at least $90 there for every $10 spent on a tool.

    A dedicated analyst can add amazing value from a strategic sense (Avinash — what you have achieved at Intuit is testament to that), but if ALL metrics must be channeled through an analyst this only reinforces a sometimes misplaced mystique about what the numbers mean and puts a block in the feedback loop (test, measure, evaluate… hang on … wait a minute…)

    That sets the challenge for the tools to show far less information and make that information highly relevant to specific audiences so they can spot the insights relative to their particular function and take action.

    Incidentally, I wonder if some of the high-end vendors are already approaching a 10/90 split between the base tool and consultancy services…

  3. 3
    Chad Parizman says:

    I heard you talk about this rule at E-Metrics and thought it was brilliant. Great to hear you discuss it more in depth here.

    Do you think that $90 should also be applied to the people actually implementing the ideas? I seem to hear more that the insights are there, but there's no one to actually run the tests or make the changes because the rest of the staff (editors, IT, designers, etc.) are too busy doing their day to day jobs.

  4. 4

    Excellent information and I agree with the problem of under-spending on analysts. I, too, heard you speak at Emetrics 2006 in Santa Barbara. Tools are important – without them the 90 would be useless, but all-to-often people do over-invest in the technology and not the people to make sense of it.

    Even with a right balance between analytics and analysis you still have to take action, as other readers here have commented. Often, I see organizations get too ambitious with actionable insights and overwhelm the already overworked IT and creative staff.

    Internal politics often present the greatest barriers to increased performance, not tools, analytics, or actionable insights.

    My recommendation to the smart analyst is to bite off small pieces of the problem. Yes, it will take longer, but in the end you will get things accomplished. Start with benchmarks, make a report that can be easily shared throughout the organization. Host a meeting to talk about it, then pick one area to take action on that will show some real results and give the credit to the people who actually made the changes (the IT, developers, designers, etc…). That will get them excited, get management excited, and break down barriers to getting more accomplished. Do this and you'll soon win buy-in from others in the organization for a faster pace of change.

  5. 5

    Well, I work for IBM and while I agree that people are more important than the web analytics package – IBM has millions of pages – and can't see Google Analytics cutting it.

    As you might know, Coremetrics just bought IBM Surfaid and frankly, that was a good thing. While there's mountains of data we have to ream though the problem is more profound than that.

    In large organizations the distribution of data repositories has to be done with great care. It's possible to create a comprehensive view of the organization OR…create hive view of the organization. For analytics – it's a nightmare trying to pull data as in the Hive view, there are dozens of data repositories many with operlapping data but different numbers and different url tagging rules.

    I can not over state how much of a nightmare this is. It's not so much the amount of data that's collected, it's the inability of the web tools to properly catagorize the data.

    So the 90/10 rule could work for a smaller organization but absolutely would not work at any large corporation.

  6. 6

    Webmetricsguru: Thanks for your comment.

    Well, I work for IBM and while I agree that people are more important than the web analytics package – IBM has millions of pages – and can’t see Google Analytics cutting it.

    Perhaps I failed in clearly delivering the core message: Web Analytics and web interactions (between our customers and our businesses) are both inherently complex and to get maximum value, independent of tool, we need to invest at a massively higher level in brains. Dumping the in house tool for GA is a suggested solution to find money for brains. That’s it. You might be right about how much load GA can handle (though Brett might disagree).

    Speaking of IBM, I might have a contrary view. Given the size and scale you describe I think the 10/90 rule applies even more to IBM than others. In fact it might be more like 5/95. You keep the tool you have need even more brains (nice bright shiny brains) to make any sense (recommend actionable insights) to your business leaders.

    Trust me I don’t underestimate your challenge. Hopefully you can take a copy of my blog post to your boss and demand the raise you have always deserved. :)

  7. 7

    Caleb Whitmore: Couple quick thoughts……

    Often, I see organizations get too ambitious with actionable insights and overwhelm the already overworked IT and creative staff.

    You are right about this but my observation is that true “actionable insights” are really hard and they are truly insights, and not something the “Top Exit Pages” reports shows then it will throttle work because of the delightful challenge the word of real Analytics is.

    Internal politics often present the greatest barriers to increased performance, not tools, analytics, or actionable insights.

    Amen!!! :) I would also add the entrenched “traditional web analytics” / reporting mindsets to politics as a massive challenge that should not be underestimated.

    My recommendation to the smart analyst is to bite off small pieces….

    If anyone is reading this comment and you have not read Caleb’s comment above please scroll above and read them, pure gold there.

  8. 8

    Chad Parizman: I appreciate your kind words about the emetrics presentation. Thank you.

    Do you think that $90 should also be applied to the people actually implementing the ideas? I seem to hear more that the insights are there, but there’s no one to actually run the tests or make the changes because the rest of the staff (editors, IT, designers, etc.) are too busy doing their day to day jobs.

    Hmmm… this is an interesting one. In my mind I was simply reallocating the $$$$ that were going to a “tool” to be redirected to “brains”. Even exchange. My assumption was that the people who exist to “IT” the site or design or do creative are still there and now thanks to Web Insights actually have great work to do.

    The point you bring up is excellent. If a company does not have supporting Processes and People then actionable insights will stay on the powerpoint slide or excel file and won’t add any value. I would do two things, if there are No supporting resources then fund that first, if there are Some supporting resources than that recommendation to put money into your pocket can go to do incremental add. Does this make sense?

  9. 9

    Andrew Hood: We won’t hold it against you that you sell a analytics tool !!
    On the topic of having someone to take action, please see my comment to Chad above.

    but I’m not convinced that “analyst” covers the real role of the 90 for most organisations.
    [SNIP]
    A dedicated analyst can add amazing value from a strategic sense, but if ALL metrics must be channeled through an analyst this only reinforces a sometimes misplaced mystique about what the numbers mean and puts a block in the feedback loop

    The perspective on the analyst/’s is that it is not just someone who cranks out reports but someone who actually is plugged into the business and strategy and aware of multiple things to start driving real actionable bottom-line impacting value by herself/himself first. But what I have observed happens is that once people taste that proverbial “blood” they start wanting to do more themselves and there my recommendation is to have a Web Analytics tool that balances simplicity with encouraging analysis. ClickTracks is such a tool IMHO (see Disclaimers & Disclosures). There are others as well.

    Summary: get a good gal/guy to show the massive value, then start giving the simple yet analytical tool to your core users that allows them to do analysis (not just reporting like most packages out there) and make decisions, your gal/guy moves up the food chain of analysis (for example migrating from simple analysis to complex multivariate or statistics). Would you agree with this? Too naïve?

  10. 10
    Jim Sterne says:

    Thanks Avinash – I've just added a new slide to my ever-growing PowerPoint stockpile:

    Data: petabytes
    Reports: terabytes
    Excel files: gigabytes
    PowerPoint files: megabytes
    One business decision based on actual data: Priceless

  11. 13
    Matt Bailey says:

    I absolutely agree. Analytics is always a stumbling block to web managers, as they believe reports will provide a "golden key" to understanding what people are doing on the site. What they fail to realize is that we have to extract data from a machine – a machine that does not "see" the website as we do.

    The key is in asking questions to extract data – something only a human can do.

  12. 14
    mike barker says:

    What are your thoughts on outsourcing the $90 part ?
    ie, instead of going out looking for a web analyst, you look for a person with good knowledge of "people on the web looking for, or with an interest in, a particular product" This knowlwdge would be gained from SEO research, practical experience with similar websites, etc

    FYI, going back a few years ….

    “ The human skills needed to bring true value to an enterprise from Web analytics are scarce, but they are more important than the technology involved. “
    Frank Buytendijk & Astrid Van Dorst, Gartner Group, April 2001

  13. 15

    Mike: I was not aware of the Gartner quote, thanks for sharing.

    What are your thoughts on outsourcing the $90 part ? ie, instead of going out looking for a web analyst, you look for a person with good knowledge

    I have to admit I am biased. I work for a large company and that clouds my point of view:

    Initially it is quite ok to go out and outsource (get someone from your vendor, get a consultant) to bring the expertise to the table and help. But long term this is not a good strategy but the vendor professional services people or consultants will never be in a position to get your business and truly understand it. That will limit the value they can add.

    Let me say that that is not becuase they are not competent, they are hugely. But only someone in the company truly plugged into the day to day and strategy and decisions can get the reality and then use the tools to ask the right kind of questions.

  14. 16

    MI completely agree with the 10/90 rule. A high percentage of the people part will come from outsourcing still, but that's OK for the SMB market. GA is the product, but for those companies that don't trust Google to collect their data, or simply want to buy a lisenced product for comfort feeling, Google has to hurry bringing Urchin 6 (the licensed GA version) to market

  15. 17

    Erik, Thanks for visiting my blog and sharing your comment.

    GA is the product, but for those companies that don’t trust Google to collect their data, or simply want to buy a lisenced product for comfort feeling

    My core recommendation is not so much that you should go out and buy Google but that you should spend a disproportionately high number on brains rather than the tool. GA is just a example I used, folks have many choices in the industry of tools that are quite cost efficient which would allow you to spend $90 on brains.

  16. 18
    BlackBerry says:

    I found your your article very very interesting to read. I totally agree with you. I do SEO for my company and I refuse to spend the $$$ on tools that I can do the work without it. At the end of the day i am there to cut costs and not make up different ways of spending it.

    :) cool article..

  17. 19
    Raj says:

    Avinash: Thanks for your article. I only recently discovered your site, which in turn led me to the other analytics sites. I have been crowing the importance of web analytics since I was the webmaster of one of the very first search engines on the Internet.

    But damned if I could ever get anyone to listen. No one I worked for (contract/ salary) ever cared or even understood the value of web analytics. Except one person, who recently asked me to write an eBook on Google Analytics. Except that ROI Revolution's site (and free webinar) made me realize how much there is to know about that tool.

    Even today, I skirt around the fact that one of my blogs is about web analytics. I dance around the topics because I'm worried that people will be scared off. It hinders my writing, and I end up throwing away article ideas.

    The fact is, that Gartner Group quote is exactly right. Unfortunately, there are not many people who even understand the potential value, let alone are able to extract value.

    I'm glad to now see you and all the other analytics bloggers.

  18. 20
    Daniel says:

    at my company we're literally at 10/90. The staff of our two FTEs is paid for in one month of the vendor's costs. our workaround to this is creatively using designated superusers, wiki's and other forms of distributed responsibility to manage. it works ok and it forces the analytics closest to the individual business units. but the planning, support, training, pressures on the central pair are intense.

  19. 21
    pere rovira says:

    To me, you're talking more about a philosohpy, rather than a rule. It's important to have a good analyst(s), it's essential, but you can't just convert that into the 10/90 rule for magnificent web analytics success. Web analytics does not end at analysis: making the most out of analysis is the hardest part, maybe. Do you have resources to actually implement the insights from the analyst? Do the decision makers "believe" in those insights, and even if they do so, is it going to be the rationale behind their decisions, or there might be political issues in between?
    Of course, you're likely to be much more successful in an organization that is willing to spend 90% of the resources into human rather than technological capital… but still it's just the beggining of the story… now the fun part begins :)
    Thanks for your blog, by the way… I am a begginer myself in the world of web analytics blogging, writing modestly from Spain.

  20. 22
    Jaume Clotet says:

    Dear Avinash,

    First of all forgive me for my english, from Girona (Spain)

    I am in the analytics business from 1999 first as user (webtrends, hitbox,…) after as a consultant in Spain (hbx, sitecatalyst,…) and now as a manufacturer (benchmarking online service http://www.netsuus.com).

    In my opinion, I see analytics beeing used for everybody in the online team instead of concentrate the efforts in one specialist. I see analytics as a marketing technique used for every Internet profesional (design, advertising, sales, IT,…) as the email or the browser instead of going throught one person in the company. Then:

    a) What do you think about this vision?
    b) Do the 10/90 rule works with this vision?

    Thanks in advance,

    Jaume Clotet

  21. 23

    Jaume : I agree with you. I call it Data Democracy, and I touch on it at the start of this post:

    http://www.kaushik.net/avinash/2007/06/six-data-visualizations-that-rock.html

    In order for any company to gain maximum benefit from the data, they will have to create a environment (through training and empowerment) were maximum number of people (decision makers) have access to the data and can use it.

    For a small company having one expert works because there are fewer layers, but that starts to lose its attraction even for medium sized companies.

    With regards to question two, yes the 10/90 works with data democracy as well (in fact it is almost mandatory with your vision). That's because you can't buy a million dollar tool and expect it to magically create a democracy. You'll have to hire some folks (in different teams) or expand job responsibilities to dedicate time to use data and have budgets for training and …. and … and … more things.

    If I were to summarize: The goal is to empower as many people in the company to use data and make local decisions for themselves, you'll need a tool that allows that to happen, but you'll to invest in resources and skills that can understand the data and make decisions.

    Hope this helps.

    -Avinash.

    PS: Your English is great, you should not worry about it. :)

  22. 24

    Totally agree. I was going to employ a company to get me further up the search engines, but decided to go on a course to learn abit about it before doing so. I spent £300 on the course. The company who were promising page 1 rankings on Google wanted £600 per month with a guarantee of our website being on the first page within 3 months. Within 1 month I am on page 1 for certain keywords and for the others on page 5. Which I think is pretty impressive. If more companies take the time to understand the web and seo they will save money. I did.

  23. 25
    Tomi says:

    This is a great rule. In the end of the day, it is all about the analysis and for that we need a pair or pairs of hands and thinking. It is also question on putting the hours in and really doing the analysis part not just taking a climpse on reports.

    Simply could not agree more!

  24. 26
    Goran Web says:

    This is a great post. There is just too much information and possibilities for change that it actually blogs my mind.

    This information is pointless however without the input of a professional that understands the web, website, marketing and Analytics in order to give the right information.

    Spend the time on the people, that really makes sense.

    PS, I read your book, what a great read, recommend it to anyone who wants to truly know about their website.

  25. 27
    Investment Property Rumours says:

    All to often you see companies demanding data, data, data on a constant basis, the problem arises with the conflicts it creates. Human nature will always throw substantial anomolies, even in the largest of datasets. Keep it simple. Tracking every last window licker through your website will not make you a millionaire next week as a result of any changes you make. If your site is full of nothing but window lickers, change your site!

  26. 28
    Tommy says:

    We used to use Webtrends. $20k a year and almost a fulltime job just keeping it going. Now we're just jusing GA! Love it!

  27. 29
    Du Lam SEO says:

    This post is really useful for us, a start-up online biz. We'll think of web analytics a great tool to convert better values to end-users.

    Thanks.

  28. 30
    VIpin Wadhwa says:

    Excellent view using analytics as a services as Just software cannot seal the deal… You need the acumen of a full person involved with business and market.

  29. 31

    […]
    According to the Web Analytics 90/10 rule put forth by highly regarded web analytics strategist, educator and author Avinash Kaushik, 10% of web analytics expenditures ought to be spent on the technology. The remaining 90% are best spent on expert human analysts.
    […]

  30. 32
    Peter Schwartz says:

    This is brilliant. We just fell in to the same place when thinking about how to manage our soon-to-be "complex problem to solve with signficant incoming analytics". This just validated what we were beginning to realize.

  31. 33
    Düzce says:

    Excellent view using analytics as a services as Just software cannot seal the deal. You need the acumen of a full person involved with business and market.

  32. 34
    su bayileri says:

    We used to use Webtrends. $20k a year and almost a fulltime job just keeping it going. Now we're just jusing GA! Love it!

  33. 35
    su bayileri says:

    This is brilliant. We just fell in to the same place when thinking about how to manage our soon-to-be "complex problem to solve with signficant incoming analytics". This just validated what we were beginning to realize.

  34. 36

    Hi Avinash,

    What is the performance impact of having 2 parallel analytics solution? There will definitely be a hit due to multiple JS files. In your experience have you see anyone do it this way?

  35. 37

    Raghu: The most common implementations of web analytics javascript tags are as close to the /body tag as possible.

    In that case having two or ten tags won't have any impact on the customer experience as the page and all the content would have rendered before the analytics tags.

    With regards to what other issues might arise, please see this post:

    ~ 10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

    Refer to item #1: If you have more than one clickstream tool, you are going to fail.

    -Avinash.

  36. 38
    Mega says:

    I'm totally agree. But, in real world, I'm still have difficulty in finding "the valuable insights".

    Would you like to describe one by one insights that i can get in every metrics?

  37. 39

    Mega: Sure. Here's some guidance that can jump-start your efforts.

    If you don't know where you are going any road will take you there. Your first action should be to create your Web Analytics Measurement Model. It will deliver simplicity and focus.

    Then go read this blog post:

    ~ Beginner's Guide To Web Data Analysis: Ten Steps To Love & Success

    It teaches you exactly how to do analysis that helps you find valuable insights.

    You can buy a copy of Web Analytics 2.0 if you want to go even deeper / get even better.

    All the best!

    Avinash.

  38. 40

    Thanks for all the wonderful posts, Avinash!

    The information is concise, insightful, and gives hope for those seeking an understanding of new media and it's uses.

    -Kyle

  39. 41
    mersin emlak says:

    This is a great rule.

    In the end of the day, it is all about the analysis and for that we need a pair or pairs of hands and thinking. It is also question on putting the hours in and really doing the analysis part not just taking a climpse on reports.

  40. 42
    Raul says:

    Thanks so much for making this concept clear to me: "It’s the people, not the software, that determine social monitoring success."

    Sometimes we tend to think the opposite, that it is the software that you use what will make you succeed.

  41. 43
    Al Williams says:

    I guess it all depends on the set up and what you are trying to get out of the tools you are using. Some people just like to see that their website has not broken and is leaking traffic etc due to a technical failure, while others need to seriously look at the consumer journey and learn more about their customers.

    Both of these require different levels of investment on the tech and personnel side of analytics.

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  16. […] Some brand terms are obvious, name of the blog and my name. Other are not quite obvious, 90/10 is also considered a brand term because I had authored the 10/90 rule for magnificent web analytics success. […]

  17. […]
    When a vendor delegate comes up to me to ask me if I'm Aurelie Pols (yes, it's written on my badge, Matthew does a great job with that amongst many more things), if I'm the one downloading all the white-papers (no, that's somebody from my team being paid to download documents and make me look smart) and if I they actually read them, I'm … confused. If I download them, yes, I read them. I actually often donwload them at the end of the day and rarely straight after opening the email (metrics you could get with your wonderful solution). I even store them on my computer and annotate some bits of text that inspire me for some of my presentations. Yes, even your solution inspires me! It's when I left him to catch Avinash's presentation and he looked at me stunned "Avi..who" that my heart really shrunk. Poor guy! you're not selling a washing machine! It's getting quite complex and please, read about the sector you're working in so that you won't tell me stupid things over the phone next time and waste my time. No, WebTrends does not only do log files, thank you very much and next time, your mobile phone scotched colleague could also present himself, for the sake of good manners.

    Enough about that, no pun intended, please read Avinash's blog to familiarize yourself at least with the 10/90 rule.
    […]

  18. […] Ich möchte einmal kurz auf die 10/90-Regel der Webanalyse von Avinash eingehen, da genau dieses Thema auch der Tenor war als es auf der SES zu einer kleinen Diskussion zwischen WebTrends-Mitarbeitern und Kollegen von IndexTools kam. […]

  19. […] Avinash Kaushik describe en su blog su 10/90 rule for magnificent web analytics success. La regla es sencilla: por cada 10€ gastados en una herramienta de web analytics, deben gastarse 90€ en el personal que sepa sacarle partido. Estoy totalmente de acuerdo con la idea de fondo: sin analistas con talento que sepan aprovechar el potencial de una herramienta de web analytics, no sirve de nada implementar la mejor herramienta de web analytics. Da igual que sea Google Analytics, gratuita, o IndexTools o Web Trends o WebSideStory o Omniture. […]

  20. […] The 90/10 rule: no it's not Avinash's rule Michaël spoke about the importance of automation but also that it was important 'to allow some room for the particular cases'. So he advises to automate 90% of the tagging procedure, while allowing some specific cases (the exceptions). […]

  21. […] 4 dimensions of enterprise web analytics success Avinash came up with 2 necessary dimensions of web analytics in a 90/10 distribution: people and technology. This will remain true forever, I think, however, mainly for companies taking their first or second step in web analytics. Eric today expanded to 3 requirements of web analytics success: process, people and technology. I always found technology to be a key for overall success, once you have entered true strategic decision making on web analytics data and the need to segment on all possible, complex questions that pop up after each questions you answered in what I would call an iterative process of advanced web analytics. Tools delivering on this level again promote the need for completely new analysts, analysts who can understand, develop and drive this huge, iterative process leading to new questions, new answers and after a while to strategic decisions, tools that do not limit the analysts mind inside the possible segments and combinations provided typically. These new analysts would also need to be able to pull in any new dimension they need from key/value pairs, meta information on the page, and external sources in the organizations or inside prepared sets of data representing outside influences like weather, seasonality or political/social events. Understanding all this types of additional data and its relevance and interpretation is key to the new analyst. The analyst also needs to correlate the new data with every already known dimension without technology obstacles like reimporting, new cubes or even ROLAP limitations. […]

  22. […] Mitt svar är och förblir att det beror på. Analys görs av människor, och din största investering skall ligga där! Avinash Kaushik skrev en utmärkt artikel på sin blogg i maj 2006. För varje hundralapp du tänker investera på webbanalys skall 10 spänn läggas på leverantör (verktyg och konsulting!) och 90 bagis på din egen personal! En av mina kunder köpte analysverktyg för 700 000 USD och lade motsvarande 15 000 USD på konsulting och utbildning. De har fortfarande inte lagt ett cent på egen personal, och använder heller inte informationen de får ut aktivt. God ekonomi? […]

  23. […] Eines der interessantesten Blogs aus der Webanalyse-Szene ist das von Avinash Kaushik. Avinash ist Consultant für Google Analytics und hat unter anderem das Buch "Web Analytics – An Hour A Day" geschrieben, was vor wenigen Wochen erschienen ist und nun auch frisch auf meinem Tisch gelandet ist. Auch wenn man Avinash doch anmerkt, dass er sehr verliebt in Google Analytics ist, so zeichnen sich seine Beiträge doch in erster Line durch die konzeptionellen Inhalte aus. So hat Avinash unter anderem die 10/90-Regel der Webanalyse aufgestellt oder elementare Entscheidungsstrategien für die Auswahl eines Webanalyse-Tools gegeben. […]

  24. […] 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 (http://www.kaushik.net/avinash/2006/05/the-10-90-rule-for-magnificient-web-analytics-success.html) 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. […]

  25. […]
    Eller så känner ni er rätt nöjda. Har lyckats implementera Google Analytics, WebTrends On Demand, Instadia eller någon annan tjänst. Siffrorna rullar in och ingen frågar efter mer än förra veckans trafik och mest poppulära innehåll.

    Webbanalys är en utmaning, och den handlar om mer än verktyg. Mycket mer! Avinash Kaushik lanserade för länge sedan sin 10/90-regel som säger 10% verktyg och 90% analytiker. Det finns mer att säga än så.
    […]

  26. […] Obviously, there's no substitute for a talented web analyst (that's where you should be spending 90% of your budget) or a web analytics process. I've also found that context is a crucial element. Here are 4 simple ways to improve your web analysis. 1. Set a Target – Revenue went up 10%. Is that good? Is it expected or unexpected? The natural inclination for most people when they look at numbers is to want them to go up and to the right. Set expectations by establishing a target. The simplest way to do this is to use last year’s data plus some expectation of year over year improvement.[…]

  27. […] 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. […]

  28. […] On one hand, it is really encouraging to see that proactive efforts are being made to track and measure and to see how doing this can go some way towards providing quantitative evidence to demonstrate a point/back-up an argument (*or in this case, a rebuttal of charges of 'dumbing down')
    However, on the other hand though, I can help but find it slightly frustrating that whilst resources have clearly been spent out on paid-for web analytics tracking software, someone somewhere still doesn't know enough or understand enough about the basic concepts involved..ie, realise that 'hits' is not really the most reliable term to use at all.
    Ok; this might all just be a case of semantics, things getting lost in translation or just plain mis-reporting, but in some small sense I can't help but this goes to restate the 10/90 rule for magnificent web analytics success.
    Or as 80s Brit band Bananarama put it so succinctly: "It ain't what you do, it's the way that you do it" – ie, having a paid for solution in place is great, but if you don't 'get' the terminology used……then is it worth it? […]

  29. […] Avinash Kaushik har sin 10/90 regel som säger 10% teknik och 90% smarta människor. Eric har sin 10/20/70 regel som säger 10% av tid och kraft på att välja teknisk plattform, 20% av tid och kraft att anställa smarta människor och 70% av tid och kraft att skapa processer och att verkligen utföra webbanalys. […]

  30. […] If you've worked in web analytics for any period of time, you'll quickly realize that it's a murky field full of nuance and trial by fire. That's especially true if you're learning the ins-and-outs of a particular web analytics package, say Omniture. If you're investing 10's or 100's of thousands of dollars in a web analytics package, you should be investing an equal amount (some would say 90% of your budget) in your web analyst. A seasoned web analyst buys you a few things: […]

  31. […] With the multitude of possible metrics that analytics systems make available, it can be difficult to select the right ones for you and even more difficult to interpret the results. However, once the basics are in place you can start digging deeper – and the results can profoundly change the way your business works online. One final tip: If you’re starting out in analytics you could do a lot worse than take the advice of analytics guru Avinash Kaushik, spend 10% of your budget on the software, and 90% on your analyst. […]

  32. […] With the multitude of possible metrics that analytics systems make available, it can be difficult to select the right ones for you and even more difficult to interpret the results. However, once the basics are in place you can start digging deeper – and the results can profoundly change the way your business works online. One final tip: If you’re starting out in analytics you could do a lot worse than take the advice of analytics guru Avinash Kaushik, spend 10% of your budget on the software, and 90% on your analyst. […]

  33. […] This blog post is not encouraging shoddy data gathering or acceptance of amateur data analysis.  In fact, following Avinash Kaushik's idea of the 10/90 rule – 10% of your web analytics budget should be spent on the tool and 90% should be spent on the analysis.  Also from Kaushik, we know the data isn't perfect; get over it. […]

  34. […] You have the skilled analysts in-house needed maintain exhaustive keyword lists, push-out relevant ad copy, and to study the data six-ways to Sunday to make sure the bidding system is functioning a peak performance. Doing paid search well is really labor intensive, both in terms of building campaigns but also in terms of spending the time analyzing the marketing angles and optimizing strategy. (Recalling Avinash's 90/10 rule, a reminder that the full value of expensive technology is only obtain when you allocate sufficient payroll expense for smart people to drive it). […]

  35. […] 25, 2008 por clotet Aquí os apunto un comentario a un post de Avinash Kaushik sobre el acceso a los datos de analítica web dentro de una organización mediana […]

  36. […]
    Este es un punto en el que muchos coinciden: distinguir entre tecnología y disciplina, como me cuenta Pere Rovira de Web Analytics cuando afirma "El futuro de la analítica web no pasa por las herramientas, sino por las personas que las utilizan. Hoy en día, disponemos de herramientas capaces de obtener datos muy sofisticados acerca del comportamiento de los usuarios en nuestro sitio web. El siguiente paso es entender cómo utilizar estos datos para mejorar nuestros sitios web".

    Es decir aplicar la regla del 10/90 de Avinash, pero además pone el dedo en la llaga cuando explica la función que el analísta debe cumplir dentro de la irganización que para Pere ( y para mi también ) debe participar en todo proceso de toma de decisiones, ya sea a nivel individual, o bien idealmente integrado en equipos de trabajo más grandes dedicados al estudio del usuario mediante diversas técnicas, como por ejemplo: investigación analítica, estudios de mercado, testeo con usuarios, focus groups, encuestas, etc.
    […]

  37. […] This thought runs in parallel to the ’90-10’ rule regarding analytics software coined by Avinash Kaushik. If you spend 90% of your analytics budget on the right people who can make the right plans, and 10 percent on the technology to allow them to do their jobs, you will get the best possible results. […]

  38. […] La analítica web forma parte de un ecosistema en el que el usuario es el centro de análisis. De este ecosistema nos interesa saber QUÉ, DONDE, CUANDO… y PORQUÉ el usuario hace, actua o piensa con relación a nuestro negocio/web. En esta ocasión te quiero presentar 4Q de iperceptions desarrollado con la participación de Avinash Kaushik, una herramienta para que preguntes a tus usuarios, y escuches su opinión, además es GRATUITA. Piensa que el usuario (en general) desea dar su opinión, al fin y al cabo es tu cliente […]

  39. […] This happened at the Small Business Unleashed Conference this week, when I quoted Avinash Kaushik’s blog post about Analytics being 90% the person and 10% the software. What was twittered was, “Matt says analytics is 90% the person and 10% the program.” That type of attribution makes me shudder, as I quote people often, and I always try to include attribution in my PowerPoint slides or verbally. Neither the verbal nor the PowerPoint attribution didn’t make it into Twitter – maybe because of the character limitation. […]

  40. […] En otras herramientas, como ClickMap de Omniture se fija en el posicionamiento del enlace respecto a otros elementos del site para diferenciarlos, sin embargo son necesarios otros tipos de configuraciones. Una vez más, sale a relucir la impotancia de la regla del 10/90, muchas veces comentada en este blog. […]

  41. […] Avinash Kaushik of Occam’s Razor proposes a 10/90 rule in order to make web analytics work. Basically, it says that your budget should be divided as 10% for the analytics tool, and 90% for the actual living, breathing, thinking analyst(s). People and brain power trumps data gathering, and immensely important in making sense of all the gibberish. Take note that this is not a hard and fast rule. The point is that data interpretation should be the focus, because numbers themselves don’t talk. The 10/90 rule is also a reproach to companies who tend to spend too much on their web analytics service, sometimes amounting to tens of thousands of dollars, when the same metrics can be had with free tools such as Google Analytics. Avinash recommends the following steps to cut cost on tools and rededicate resources to the more vital task of analysis: […]

  42. […] This happened at the Small Business Unleashed Conference this week, when I quoted Avinash Kaushik’s blog post about Analytics being 90% the person and 10% the software. What was twittered was, “Matt says analytics is 90% the person and 10% the program.” That type of attribution makes me shudder, as I quote people often, and I always try to include attribution in my PowerPoint slides or verbally. Neither the verbal nor the PowerPoint attribution didn’t make it into Twitter – maybe because of the character limitation. […]

  43. […] punch. Take a look at his review and let me know what you think. A simple take away for me is that Avinash's 90/10 rule: "Spend 10% of the money on the tools and 90% on the people". By people I mean not […]

  44. […] This is a princely price for China, given that it reflects a monthly salary for a senior analyst / senior analytics consultant in the market. While I am excited about this opportunity, I am not sure how many companies can afford that kind of money in the current economic situation. I can only urge my readers to review Avinash's 90/10 rule. […]

  45. […] Getting a return from your Analytics data does take an investment. The most important investment to start with is making sure you or someone at your organization has the expertise and time to put your data to use. If at that point you still feel you need to pay more for a more complicated tool, that's OK, but remember that every dollar you spend on a tool takes away from money you could be spending on actually getting results, i.e. hiring or contracting a talented analyst (see the 90/10 Rule). […]

  46. […] My good friend, and web analytics guru, Avinash Kaushik once wrote: Cancel the contract with your favorite expensive analytics vendor and take that $50k or $100k or […]

  47. […]
    We are nowhere near the Avinash Kaushik rule of thumb which suggests that $90 should be spent on people power for every $10 spent on technology. But there has definitely been an improvement.
    […]

  48. […]
    Avinash writes about the 90/10 rule which simply suggests that for every $10 you spend on analytics software $90 should be spent on resources to interpret actions. Although this applies mainly to enterprise level analytics, there’s something for us to take away from that. Our currency is the learning curve which translates to time, patience and human bandwidth capabilities.
    […]

  49. […] The true potential for optimizing E2.0 investments is to focus on lowering transaction costs, with technology, by design (the proportion of people-focused design investment — including changes to facilitate adaptation and continuity — to hard technology investment should be at least a 9 to 1 ratio). […]

  50. […]
    A quote from Avinash Kaushik (Occam’s Razor and @avinashkaushik) to start this post.
    I have a 10/90 rule . If your budget is $100 then spend $10 on tools and professional services to implement them, and spend $90 on hiring people to analyze data you collect on your website.
    […]

  51. […]
    Companies are recognizing that analysts drive insights, not the analytics tool itself. According to the study, "sixty percent of decision-makers agree that investments in web analytics people are more valuable than investments in web analytics technology." This is in-line with Avinash Kaushik's 10/90 rule for web analytics success: invest 10% of your analytics budget on the actual technology and 90% of your budget in the people who deliver actionable insight, whether in-house analysts, agencies, or vendor partners. It's the people that matter.
    […]

  52. […]
    If you’re spending more on technology than interpretation, you’re probably overwhelmed with data and underwhelmed with insight. The problem of data overload is particularly common in organizations that have over-purchased analytics technology. Carrying large analytics license fees typically means less money for analytics services and human resources. It’s a tough place to be: lots of data, but nobody to make sense of it. Analytics evangelist Avinash Kaushik recommends the 10/90 rule: for every $10 spent on analytics tools, spend $90 on “intelligent resources/analysts.”
    […]

  53. […] 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 […]

  54. […]
    The center cannot hold; the system breaks down, the levees crack and we are drowned in meaningless information. My friend works as a web analyst at the major canadian telco. In a perverse twist on Avinash’s famous 10/90 rule, he spends about 10% of his time surfacing insights and 90% of his time wrestling with a convoluted array of reports, charts, and dashboards from myriad suppliers. How productive is that?
    […]

  55. […]
    Despite all of these great new features, we will still be dependent on human beings to analyze and take action on the data. Even Google Analytics evangelist Avinash Kaushik has written about his 10/90 rule, which says that just 10% of web analytics relates to tools, while 90% of both cost and success has to do with humans who analyze data and make recommendations for change based on their insights.
    […]

  56. […]
    Một trường hợp nữa là nhân viên analytics cũng chẳng master về web analytics –> chả xoay được gì, công cụ càng mạnh thì càng chết. Lúc này thì dù giám đốc có giỏi, hiểu rõ web analytics quan trọng nhưng WA cũng chả có hiệu quả vì người thực hiện kém –> qui luật 10/90 trong khai thác Web Analytics : đầu tư 1 đồng cho công cụ thì phải đầu tư 9 đồng cho nhân sự!
    […]

  57. Google Analytics 发布智能引擎(Intelligence Engine),智能警报(Alerts) » 青石榴搜索营销SEM/搜索优化SEO says:

    […]
    虽然有如此之多的全新功能,我们还是需要依靠人去分析和整理数据。即便 Google Analytics 传教士 Avinash Kaushik 写了 10/90 法则,其中也只有 10% 的页面是关于工具的,90% 的付出和成功和分析数据、做决定的人有关。
    […]

  58. […]
    Ondanks al deze geweldige nieuwe functies zullen we nog steeds afhankelijk zijn van de mens om te analyseren en actie ondernemen op de gegevens. Zelfs Google Analytics evangelist Avinash Kaushik heeft geschreven over zijn 10/90 regel, die zegt dat slechts 10% van de web analytics betrekking heeft op de tools, terwijl 90% van zowel de kosten als het succes te maken heeft met mensen die de gegevens analyseren en aanbevelingen voor verandering maken op basis van op hun inzichten.
    […]

  59. […]
    Analytics industry experts across the spectrum have said it over and over, it’s not just about technology. Consider: people (in-house staff, consultants, professional services organizations), process, the organizational analytics maturity, among other factors. We are aware of Avinash’s 10/90 rule
    […]

  60. […]
    Wer Web Analyse ernsthaft betreiben möchte, muss also auf jeden Fall Geld in die Hand nehmen. Die Frage, die sich letztendlich stellt, ist wie man das Budget zwischen Software und Menschen verteilt. Hierzu gibt es radikale Ansätze wie die 10/90 Rule von Avinash Kaushik. Die Regel ist von Avinash eher als Denkanstoß gedacht. Im Kern besagt sie, dass man 10 % seines Budgets in das Tool und 90 % in die Menschen, die damit arbeiten, investieren sollte.
    […]

  61. […]
    The volume of data has overpowered our basic analytical capabilities. The center cannot hold; the system breaks down, the levees crack and we are drowned in meaningless information. My friend works as a web analyst at the major canadian telco. In a perverse twist on Avinash’s famous 10/90 rule, he spends about 10% of his time surfacing insights and 90% of his time wrestling with a convoluted array of reports, charts, and dashboards from myriad suppliers. How productive is that?
    […]

  62. […]
    Nonostante questo alcuni di noi l’hanno amato da subito, compreso il sottoscritto che in ufficio era abituato ad usare Webtrends: non mi sembrava vero di avere tutto sotto mano con così poco sforzo, e sebbene fossi conscio del fatto che – allora – i due sistemi non erano nemmeno lontanamente paragonabili, avevo iniziato a intuire la portata di quella che ormai quasi tutti conosciamo come la “regola 10/90″ di Avinash Kaushik: se hai 100 da spendere in web analytics, usa 10 per il software e investi 90 nelle persone che dovranno fare l’attività. Google Analytics, anche nella sua prima incarnazione, spostava l’ago esattamente in quella direzione: costo zero, installazione zero, configurazione limitata.
    […]

  63. […] 分析人员是非常重要的。后续我们会谈到,即使网站分析工具部署得很成功,但是报表中得到的只是数据,而将数据转化为结论再以此为依据提出创造性的见解,这才是网站分析中最重要的环节。Avinash的《The 10 / 90 Rule for Magnificent Web Analytics Success》中的规则指出,在分析方面的投入和购买分析工具的投入应该是9比1的关系,可见其重要性。而这部分工作就需要分析人员来完成。分析岗位可以是一个专门的岗位,也可以是由市场部门的人员兼任。这个岗位除了需要通过分析发现数据背后的真相,还需要熟悉网站本身的业务,熟悉网站的推广和运营,这样才可能得出符合网站实际的分析报告。 […]

  64. […] well known for the 10/90 rule. Why do you think it's more important to put the emphasis on people rather than technology? […]

  65. Mensuração online: Homem Vs. Máquina | InComMetrics says:

    […] segue a propsota de Avinash Kaushik que diz para as empresas investirem 10% do seu orçamento de Analytics em tecnologia e 90% em […]

  66. […] 您以10/90法则而著称,为什么你觉得关注人比关注技术更重要? 要关注到一个什么样的程度?你如何设置一个合适的目标,并且知道是否能打到这个目标呢?还是就是认准了就往前冲,试试再说。 […]

  67. […]
    Kedua saya juga ingin mewanti-wanti bahwa secanggih apapun tool yang kamu punya, itu hanyalah sebuah tool. Seberapa hebatnya web analytics kamu tergantung dari siapa yang melakukannya. Jangan pernah berinvestasi berlebihan untuk tools, investasikan lebih kepada para praktisionernya. Ini bukan karena saya adalah dan membela praktisioner web analytics pada umumnya. Ini sama seperti sebuah pesawat tempur yang hanyalah sebuah alat untuk terbang. Yang bisa menjadikannya alat tempur yang hebat adalah pilotnya.

    “10/90 rules! Smart people with crappy tools can move mountains,…”

    – Avinash Kaushik, web analytics practitioner & evangelist

    Tiga tahun lalu, Avinash sudah menulis artikel 10/90 rule yang menjabarkan bahwa untuk mendapatkan hasil web analytics yang terbaik, proporsi / ratio seberapa pentingnya tool ketimbang praktisioner adalah 10 banding 90.
    […]

  68. […]
    Veel bedrijven en organisaties hebben Google Analytics op hun website geïnstalleerd. Of zijn van plan iets te gaan doen met Google Analytics. Beginnen met Google Analytics is een prima start. Investeer liever in mensen die de webstatistieken kunnen vertalen naar concrete acties dan te kiezen voor een duur webanalytics pakket. Of zoals Google evangelist Avinash Kaushik zegt: investeer 10% in de tools en 90% in mensen. Dit artikel helpt met het maken van een goede start. Geen diepgaande of ingewikkelde tips. Geen artikel voor de freaks. Maar praktische tips en richtlijnen voor iedereen die Google Analytics wil gebruiken om van zijn website een verkoop- en leadgenerator te maken.
    […]

  69. […]
    Same thing for AB and MVT testing. You can see for yourself with the handy Google Website Optimizer calculator. Assuming a 2% baseline conversion rate, a 20% expected conversion rate improvement and the only change is the number of visitors who see your experiment page. If 1000 visitors see it a day, the expected experiment duration is 17 days, but if only 100 people see it per day it is 175 days! Ouch…

    Add in the fact that web analysis is likely done on an ad-hoc basis without dedicated people (thereby violating Avinash Kaushik’s 10/90 rule), what’s a busy small retailer to do?
    […]

  70. […]
    В самом крайнем случае (тьфу- тьфу- тьфу), можно будет просто перейти на другие инструменты, например ту же Яндекс.Метрику (кстати, если вам интересен обзорный пост о сравнении GA и Я.Метрики, то дайте знать в комментариях). Опытные веб-аналитики знают, что инструмент не так важен. Помните правило 10/90 от Авинаша?
    […]

  71. […]
    The 10 / 90 Rule for Magnificent Web Analytics Success | Occam’s …
    – [ این صفحه را ترجمه کن ]
    Numerous studies have pointed out that while almost all Fortune 500 companies have great investments in Web Analytics they still struggle to make any.
    http://www.kaushik.net/…/the-10-90-rule-for-magnificient-web-analytics-success.html – ذخیره شده – مشابه
    […]

  72. […]
    Clearly, savvy media sites that are able to manage the complexities of calculating and optimizing user experiences and maintain positive net ROI can make this model work, however it takes a brilliant analytics ninja to implement the myriad of data required to make it truly sustainable. Avinash’s 90/10 rule might have to be magnified a bit… maybe 98/2 would work?
    […]

  73. […]
    These are people that have helped us gain tremendous knowledge in Google Analytics. – Avinash Kaushik- Thanks for the greatest methodologies, analytics views and brutally honest 10 / 90 rule.
    […]

  74. […]
    La Regla del 10/90 que plantea Avinash habla sobre la importancia que debe tener el enfoque al talento y al desarrollo de habilidades para convertirse en un excelente analista web, es decir…el 90%. Si yo no concordara con esta posición sería como darme balazos en los pies!

    Creo ciegamente en la educación y práctica constante para refinar las habilidades y experiencia en el mundo de la Analítica Web. De ahí que en el próximo post, me enfocaré a mencionar qué actividades/materiales creo son de gran ayuda para desarrollar ese 90% restante!
    […]

  75. […] знают, что инструмент не так важен. Помните правило 10/90 от […]

  76. […]
    Why pay for an individual qualification? Avinish Kaushik has an excellent post where he says for every $100 you invest in web analytics, you should spend $10 on tools and $90 on people with the brain power to think about the results from the tools. So for me, it made sense to test my brain power on a tool, but I realize that each site needs its own analyst behind it to choose the measurements and connect the site to the business.
    […]

  77. […]
    But remember, statistical significance from a piece of software cannot alert you to data that is inherently wrong or warn you that something else has influenced (and perhaps invalidated) a test, it only tells you that the results were unlikely to happen by chance. Omniture (interesting alert for segmented data) and Google Analytics (GA intelligence) have been dabbling in this area, but still require human interaction and do not cover all aspects for.

    So make sure that you perform your due diligence with tool setup, test design, and data analysis – because it is very easy to gain confidence in the wrong decision with bad data from a tool that says it is 95% confident. Again, it is so important for us to invest greatly in people along with tools. As Avinash Kaushik says, you should invest 10% in tools and 90% in people problems.”
    […]

  78. […]
    Avinash writes about the 90/10 rule which simply suggests that for every $10 you spend on analytics software $90 should be spent on resources to interpret actions. Although this applies mainly to enterprise level analytics, there’s something for us to take away from that. Our currency is the learning curve which translates to time, patience and human bandwidth capabilities.
    […]

  79. […]         
    网站分析最重要的是什么? 对于这个问题,Avinash就这个问题专门开了文章讨论,我跟他的感受是完全一样的。其实,这个问题还可以变为:“一切分析活动最重要的是什么?”显而易见的答案——是人。你可以说,技术很重要、工具很重要、数据很重要、模型很重要、经验很重要……但是,这一切都需要有聪明的头脑去组织去构造,然后才能利用合适的工具得到必要的数据,并采用合适的模型来分析这些数据,从而得到所谓的insight(见解或观点)。而工具、数据和模型不仅不可能直接给你insight,它们更不可能直接给你recommendation(建议)。不要跟我说什么Business Intelligence(商务智能)系统能做到,或者跟我说某个先进的模型能够洞悉一切——这些都是bullshit,没有人的大脑指挥它们,它们就会一钱不值。大家看了“少数派报告”吗?电影真相快要揭晓的时候大家恍然大悟——牛X的不是计算机,而是天赋异禀的人的大脑。同样,网站分析乃至一切分析真的也是这么回事。
    […]

  80. […]
    First of all, confirm what your company can afford to invest in analytics. Then apply the 10/90 rule from Analytics guru, Avinash Kaushik (10% of your budget for the Analytics tool and 90% of your budget for the analyst who needs to dissect the data). No matter how big and amazing your analytics tool is, it is useless if you don’t have an expert who can understand all this data and deliver true insights and recommendations on how to improve conversion on your site. Finally, come up with a list of what data your company really needs to determine success.
    […]

  81. […]
    A few years ago, Avinash Kaushik created the 10/90 rule for Web analytics.

    It is based on the idea that if you have a $100 budget to “make smarter decisions on the Web”, invest $10 in tools and vendor contracts, and $90 in people. It’s a rule that he learned first-hand after discovering that Web analytics tools became more valuable after hiring analysts to interpret what all the data meant.
    […]

  82. […]
    Alguns anos atrás, Avinash Kaushik criou a regra 10/90 para análise de sites. A regra é baseada na idéia de que se você tem um orçamento de $ 100 para “tomar decisões mais inteligentes na Web”, deve investir $ 10 em ferramentas e contratos com fornecedores, e $ 90 em pessoas. É uma regra que ele aprendeu em primeira mão, depois de descobrir que as ferramentas de Web Analytics se tornavam mais valiosas depois de contratar analistas para interpretar os dados que eram apresentados.

    Em muitos aspectos, a regra 10/90 pode ser aplicada às mídias sociais.
    […]

  83. […]
    O blogueiro e autor do livro Web Analytics, Avinash Kaushik tem uma teoria chamada regra 10/90 para análise de sites. A regra é fácil. Se você tem um orçamento de R$ 100 para “tomar decisões mais inteligentes na web”, você deve investir R$ 10 em ferramentas e contratos com fornecedores, e R$ 90 em pessoas.

    A teoria saiu depois do blogueiro perceber que as ferramentas de web analytics se tornavam mais valiosas depois da contratação de analistas que interpretam os dados apresentados.
    […]

  84. […]
    Como puedes ver, al igual que en el caso del Community Manager, la posición de Web Analytics Manager no podrá ser tomada por una persona junior, sino por una persona con suficiente experiencia en distintas áreas del negocio, buena comunicación y presencia dentro de una organización. Pero como dice Avinash Kaushik, evangelizador de Web Analytics de Google, cualquier proyecto exitoso de Web Analytics invierte el 10% del presupuesto en las herramientas y el 90% en la gente que usará esas herramientas.
    […]

  85. […]
    In today’s SaaS-driven world, it is easy and tempting to purchase every tool that comes along, without consideration for the 10/90 Rule: spend 10% of your budget on tools and 90% on the talent using them. That said, there are a plethora of tools that can optimize and streamline your marketing efforts, increase your inbound leads, and make your life easier.
    […]

  86. […]
    A raíz del post de Gemma Muñoz: “Si tu única herramienta es un martillo, tiendes a tratar cada problema como si fuera un clavo” en el que habla sobre la elección de herramientas para el desarrollo de análisis web así como la 10/90 Rule for Magnificent Web Analytics Sucess de Avinash, me he sacudido la pereza para compartir las herramientas que he encontrado relevantes en mi desempeño [es decir…mi 10%]
    […]

  87. […]
    Daten sind die Grundlage wichtiger Entscheidungen. Am Anfang sollte man sich jedoch die Frage stellen, wie viel Geld man investieren möchte. Ein fest angestellter Web-Analyst sollte ein Jahresgehalt von mindestens 40.000 Euro bekommen. Diese Zahl ist nicht aus der Luft gegriffen, sondern Teil der 10/90 Regel. Der Erfolg gibt ihr recht.

    Ein guter Analyst alleine reicht jedoch nicht. Er muss mit seiner Arbeit auch so in das Unternehmen eingebetettet werden, dass seine Erkennisse umgesetzt werden jkönnen. Also in einer beratenden Funktion des Top-Managements, als Teil der Controlling-Abteilung oder selbst als Entscheidungsträger.
    […]

  88. […]
    Below is a list that I have complied on tools and their metrics. I have to state that the list is not the end all be all and I welcome any reader to let me know what clever metric they have up their sleeve. I will however state that I agree with Avinash Kaushik 10/90 rule. Ok so here we go!
    […]

  89. […]   对于这个问题,Avinash就这个问题专门开了文章讨论,我跟他的感受是完全一样的。其实,这个问题还可以变为:“一切分析活动最重要的是什么?”显而易见的答案——是人。你可以说,技术很重要、工具很重要、数据很重要、模型很重要、经验很重要……但是,这一切都需要有聪明的头脑去组织去构造,然后才能利用合适的工具得到必要的数据,并采用合适的模型来分析这些数据,从而得到所谓的insight(见解或观点)。而工具、数据和模型不仅不可能直接给你insight,它们更不可能直接给你recommendation(建议)。不要跟我说什么Business Intelligence(商务智能)系统能做到,或者跟我说某个先进的模型能够洞悉一切——这些都是bullshit,没有人的大脑指挥它们,它们就会一钱不值。大家看了“少数派报告”吗?电影真相快要揭晓的时候大家恍然大悟——牛X的不是计算机,而是天赋异禀的人的大脑。同样,网站分析乃至一切分析真的也是这么回事。 […]

  90. […]
    Below is a list that I have compiled on tools and possible metrics. I have to state that the list is not the end all be all and I welcome any reader to let me know what clever metric they have up their sleeve. I will, however, state that I agree with Avinash Kaushik’s 10/90 rule. Ok so here we go!

    Web Analytics Tools
    I want to assume that you have a tool implemented on your website already, considering there are hundreds out there.
    […]

  91. […]
    Luego entonces, es necesario preparar una estrategia que nos permita tener campañas de calidad y así obtener mejores resultados por nuestra inversión. La Regla 90/10 de Avinash Kaushik aplica aquí también: es mejor invertir en agencias/profesionales capacitados, que aumentar a ciegas la inversión publicitaria.
    […]

  92. […]
    According to Avinash Kaushik, Web analytics guru for Google, “Numerous studies have pointed out that while almost all Fortune 500 companies have great investments in Web Analytics they still struggle to make any meaningful business decisions. Most people complain that there are tera bytes of data and giga bytes of reports and mega bytes of Excel and PowerPoint files. Yet no actionable insights, no innate awareness of what is really going on through the clutter of site clickstream data.” (from The 10 / 90 Rule for Magnificent Web Analytics Success)
    […]

  93. […]
    Il faut bien faire votre ratio entre ce que va vous coûter l’outil et ce que va vous coûter l’humain qui va travailler dessus. Traditionnellement on dit qu’il faut investir 10% du budget dans l’outil et 90% dans l’humain. (C’est Avinash Kaushik qui dit ça. Je rends à Avinash ce qui est à Avinash.). Bref, c’est une approche assez juste, pas la peine de dépenser 100K euros dans un outil pour mettre derrière un stagiaire qui va vous faire du reporting.
    […]

  94. […]
    Avinash Kaushik describe en su blog su 10/90 rule for magnificent web analytics success. La regla es sencilla: por cada 10€ gastados en una herramienta de web analytics, deben gastarse 90€ en el personal que sepa sacarle partido. Estoy totalmente de acuerdo con la idea de fondo: sin analistas con talento que sepan aprovechar el potencial de una herramienta de web analytics, no sirve de nada implementar la mejor herramienta de web analytics.
    […]

  95. […]
    With any web analytics software you must consider the 90-10 rule Google evangelist, Avinash Kaushik advises. For every $10 you spend in software $90 will be required for resources to sort through your data and find gold. Source
    […]

  96. […] 我一直在提倡互联网分析成功的 10/90 法则已经有五年了。人才是核心,找到合适的员工的确不容易,但我不相信有这么困难。 […]

  97. […] Google Analytics 传教士 Avinash Kaushik 写了 10/90 法则,其中也只有 10% 的页面是关于工具的,90% […]

  98. […] 您以10/90法则而著称,为什么你觉得关注人比关注技术更重要? 要关注到一个什么样的程度?你如何设置一个合适的目标,并且知道是否能打到这个目标呢?还是就是认准了就往前冲,试试再说。 […]

  99. […]
    Any tool is only as good as its implementation and the analysts using it (see Avinash’s 10/90 rule!). Some tools are much trickier to implement and maintain than others — that trickiness brings a lot of analytics flexibility, so the implementation challenges have an upside. In the end, I’ll take any tool properly implemented and maintained over a tool I get to choose that is going to be poorly implemented.
    […]

  100. […]
    Para terminar, ha hablado de las personas. Los datos han de contribuir al conocimiento, y la estructura de la empresa debe fomentar que este conocimiento se traduzca en acción. Pere ha puesto al día la regla del 10/90 de Avinash: el 90% no se debe invertir en “analistas” si no en “generar conocimiento”, ya sea en personas, herramientas, partners…
    […]

  101. […]
    Most Web users appear, curiously, okay with the first condition of payment. The second is trickier, enter: The 10/90 Rule "If you have a budget of $100 to make smarter decisions on the web, invest $10 in tools + vendor contracts and invest $90 in people (big human brains inside or outside the company to do analysis and the process of producing insights)." – the famed (well in the web-analytics realm) Avinash Kaushik 10/90 rule
    […]

  102. […]
    Bir diğer hata da yazarın daha önceden de öne sürdüğü 10/90 kuralını işletmemek olarak sayılıyor. Buna göre başarılı bir web sitesi sahibi olmak için web araçlarına bütçenin % 10’nu, insan kaynağına ise bütçenin % 90’nını kullanmak gerekiyor. Bu insan kaynağının içinde analistler, moderatörler gibi iş tanımları var. Bu noktalarda iyi profesyoneller ile çalışmak başarının gelmesinde önemli noktalardan biri olarak gözüküyor.
    […]

  103. […]
    One perspective I don't agree with is his well-known "10-90 Rule". Put simply, Avinash says that if a company has $100 to spend on analytics, they should spend $10 on the tools and $90 on the people to make sense of the data the tool spits out. The reason for this is that wen analytics tools (e.g., google analytics, ominture, core metrics, etc) puke out overwhelming amounts of data — far more than the average person can (or would want to) make sense of. Thus, the solution (according to the 10-90 rule) is to spend more money on more people to make sense of the data your tool (which you're already paying for) is generating. You can read the full post here.
    […]

  104. […] que es ese 10%! Bueno Avinash del que ya he comentado algunas cosas, "postuló" la Regla del 10/90 que en resumidas cuentas viene a ser: "Gasta el 10% en herramientas y el 90% el gente que […]

  105. […] i så mange år, så er det at mennesker betyr utrolig mye. I åtte år har jeg snakket om 10/90-regelen. Kort fortalt går den ut på at dersom du har 100 dollar å investere i webanalyse, så bør kun […]

  106. […]
    O Avinash Kaushik, profissional renomado no ramo do Web Analytics, tem uma lei que resume perfeitamente o que foi dito na mesa redonda, a lei 10/90. Em resumo, essa lei diz que apenas 10% de todo o seu budget deve ser investido em uma ferramenta, enquanto os outros 90% devem ser investidos em um recurso de inteligência, ou mais específico, em um profissional Analista.
    […]

  107. […]
    Failure to invest in the people to actually maintain the implementation and use the data (Avinash has been fretting about this issue publicly for over 5 years)
    […]

  108. […]
    Well, this is where Avinash Kaushik’s 10/90 rules comes into play, which states, that for every £10 you spend on a web analytics tool, you should be spending £90 on the people to analyse the numbers i.e. a company spending £50k on any paid solution, such as Adobe (Omniture) and Coremetrics, should be spending £450k on a team of web analysts to analyze and gain valuable insights, considering that a web analyst’s typical daily/weekly role is split into the following categories:
    […]

  109. […]
    Invertir en herramientas y no en la gente
    Avinash Kaushik lo deja muy claro en su regla 10/90 para obtener un valor alto en la implementación de web analytics se debe emplear el 10% en herramientas y el 90% se debe invertir en recursos/analistas inteligentes. Como el “Pecado” 3 lo dice, un análisis debe llamar a la acción, y una herramienta, por más reportes que pueda obtener, nunca va a proveer conclusiones que llamen a la acción y que estén alineadas con los objetivos de la empresa. Es la gente, con habilidades y conocimientos sólidos que podrá generar ese valor.
    […]

  110. […]
    The 10/90 rule of 10% spending in tools and services, and 90% spending in analysts to achieve effective insights from web analytics can at least be approached with a short investment of time to set up Google Analytics, but it is still surprising how many companies fail to take that step. Or even worse, consider companies whose web analytics data is such a closely guarded secret within organizational silos that those responsible for the growth of the business cannot even get access to the tools, let alone begin down the path toward quality analysis.
    […]

  111. […]
    La regla 10/90 la planteo Avinash Kaushik en el 2005, aunque hoy en día es plenamente vigente. Avinash es una persona de referencia en el mundo de la analítica web, y os recomiendo seguir su blog. En pocas palabras la regla nos explica que en un proyecto de analítica web hay que gastar el 10 % en la tecnología de analítica web y el 90 % en personas que manejen esa tecnología. Es decir, hay que centrarse en el análisis más que en la herramienta para obtener los datos. Lo maravilloso de esta regla es que podemos aplicarla al resto del marketing online.
    […]

  112. […]
    Ciddi yatırımlar ile elde edilen Premium bir web analiz yazılımına sahip bir çok firmada yaşanabilecek önemli bir sorun, bu yazılımı kullanabilecek insan kaynağına sahip olmamak. Yetlin bir analiz ekibinizin olması yatırımınızın doğru sonuçlanmasında birebir etken olacaktır.
    Avinash Kaushik şöyle diyor:
    […]

  113. […]
    People are prone to error, so your data entry systems have to proactively ensure you’re getting the best quality in. This might mean customized forms layered over databases, but it’s worth it. Don’t forget the output is equally human-sensitive. Follow Avinash’s rule of 9:1 spending on analysts to systems/tools and you’ll probably be ok.
    […]

  114. […]
    Avinash Kaushik is probably the most respected web analytics expert in the world. From his experience he has developed a simple rule that summarizes his thoughts on data analysis: For every $10 you spend on analytics tools, you should invest $90 in intelligent resources/analysts. Most analytics teams are drowning in data, so the trick isn’t getting the information, it’s finding smart people to get the right data and actually do something with it. Although he created this rule specifically for web analytics I believe it extends to almost all facets of big data.
    […]

  115. […]
    KNOW THE 10%/90% RULE: In Web Analytics; An Hour a Day, Avinash Kaushik describes the 10%/90% rule; that is, for every $10 invested in analytic software, $90 is required for an intelligent analyst. Bottom line: It’s the people, not the software, that determine social monitoring success.
    […]

  116. […]
    Number of thought leaders have emphasized on the need to invest in people, but none have spelled or tied it to success for the investment of the tool/technology. Analytics Evangelist at Google, and my good friend – Avinash Kaushik came up with the 10/90 rule. If you are investing $10 in tools/technology, invest $90 in people. This is a great start and an ideal goal for any organization in achieving the full value of their investments. Having talked to organizations of all sizes, I think there is more need for an 80/20 rule for enterprise level implementations. For organizations that rely on free tools, a 10/90 rule would be perfect – the investment is only on getting the technology/tool implemented correctly. For larger organizations, it is about implementation, scaling and availability in addition to deriving value from the investment. I tend to bundle adoption of the technology or embedding analysis from the analytics package within the decision making process as part of the investment.
    […]

  117. […]
    Aunque las herramientas son necesarias, lo más importante es la inversión realizada en recursos humanos destinados a la interpretación de todos los datos ofrecidos, algo que no siempre es tarea fácil, sobre todo, si se trata de un website con un amplio número de páginas. A esto se refiere el experto de referencia a nivel mundial Avinash Kaushik cuando enunció la conocida regla del 90/10 de la analítica web:
    […]

  118. […]
    GOLDEN RULE (COURTESY OF AVINASH KAUSHIK)
    Dedicate 10% of the money you spend on tools and 90% of the money you spend on the people who analyze the tools. Don’t rely on tools without first understanding why you have the tool in the first place. Sometimes tools will actually make you less efficient if you make a problem more complex than it needs to be.
    […]

  119. […]
    The next step after setting up KPIs is to analyze and interpret the obtained data by using benchmarks and goals. Avinash Kaushik explains in his videos how to read and use data from the Google Analytics dashboard and he recommends that for each KPI there should be one responsible person who needs to explain why the metric is (not) performing well and how it can be improved. In addition, Kaushik brings up the 10/90 rule, stating that only 10 per cent of the web analytics budget should be used for tools like Google Analytics, the rest should be spent on employees who can interpret the data and give meaning to it. For that, one has to fade out unnecessary data (“noise”) and focus on the relevant parts.
    […]

  120. […]
    Algunas consideraciones importantes son el presupuesto con el que se cuenta tanto para implementación como para el mantenimiento periódico, los recursos que dentro de la organización trabajarán con el sistema, el perfil de los mismos, qué funcionalidades son más importantes para el modelo de negocio etc. En este caso lo más importante es aplicar la regla del 10/90 de Avinash Kaushik: Coste de la herramienta & servicios: 10 €. Inversión en profesionales “analistas”: 90 €.
    […]

  121. […]
    Muitas empresas ainda pensam que a contratação de um analista de Web Analytics é um grande investimento. A maioria das empresas se esquece de que o papel de um Analista Digital é cada vez mais amplo e profundo, por muitas vezes até complexo. A regra do 10/90 de Avinash é uma das mais coerentes, em que 90% deve ser sobre pessoas / analista, e os 10% devem estar sobre as ferramentas.
    […]

  122. […]
    I can’t emphasize that enough. It beats “best practices” hands down. It’s more effective than any tool by any vendor. (And, I say that as a highly enthusiastic vendor in this space.) Because, as Avinash Kaushik so famously said in his 10/90 rule for investing more in talent than technology, modern marketing success is more about your people than anything else. Agile marketing is designed to unleash their full potential.
    […]

  123. […]
    Avinash Kaushik, the world’s leading expert in web analytics states “10% of budgets should be spent on tools and 90% on a smart analyst“. Even with limited resources, it’s easy to spend hours mining the data in Google Analytics, but an easy way to access the data is to set up scheduled reports.
    […]

  124. […]
    Ya en 2006 Avinash Kaushik postuló su regla 10/90 por la que el éxito de una implementación de analítica web no iba de la mano de las herramientas, sino de las personas, de manera que de un presupuesto de 100$ la inversión tenía que repartirse así:
    […]

  125. […]
    Avinash Kaushik hat mit der 10/90-Regel bereits 2006 einen Denkanstoß in diese Richtung gegeben. Die 10/90-Regel besagt, dass 10% des Budgets in das Web Analytics Tool fließen und 90% in das Personal, welches sich mit Web Analytics beschäftigt. Im konkreten Fall müssten bei Kosten von 25 000 € pro Jahr für ein Tool, 225 000 € in Personal investiert werden, um das volle Potenzial des Tools nutzen zu können. Nach Kaushik sollten Unternehmen zunächst ein kostenloses Tool implementieren und das dadurch gesparte Kapital in Personal investieren, um den Erfolg der Website steigern zu können.
    […]

  126. […]
    In 2006 Avinash Kaushik famously advised that a successful web analytics implementation depended on an investment ratio of 90% “intelligent resources” (people) to 10% technology. Although this rule was intended for web analytics, our experience is that there are few exceptions in marketing technology. But it’s a lot easier to pull the trigger on a piece of technology than on new employees. Likewise it’s not easy to casually reorient existing staff to become experts in a new technology.
    […]

  127. […]
    O Avinash Kaushik, profissional renomado no ramo do Web Analytics, tem uma lei que resume perfeitamente o que foi dito na mesa redonda, a lei 10/90. Em resumo, essa lei diz que apenas 10% de todo o seu budget deve ser investido em uma ferramenta, enquanto os outros 90% devem ser investidos em um recurso de inteligência, ou mais específico, em um profissional Analista.
    […]

  128. […]
    Avinash Kaushik is credited with coining the 90/10 Rule for Magnificent Web Analytics Success, which essentially states that 10% of your resources should be allocated to tools, but the other 90% should be dedicated to the people who will wield these tools. Our people, not our tools, interpret and act upon data – and the tools only serve to help them accomplish this goal.
    […]

  129. […]
    Pregunta 1. En el segundo capítulo del libro Avinash Kaushik hace se-mente de la normal del 10/90. Avinash tiene una entrada en su blog donde explica esta regla (www.kaushik.net/avinash/the-10-90-rule-for-magnificient-web-analytics-success/). Leída la entrada del blog y los comentarios de los diferentes lectores, explique de forma resumida (de 300 a 500 palabras) en que consiste la regla y vincule y comente alguna de las reflexiones hechas por los lectores del blog.
    […]

  130. […]
    Más tarde, Gustavo Saientz de Resultics expuso varias cuestiones interesantes en cuanto a medición. Dónde estamos parados y hacia donde debemos ir. La centralización de datos en una plataforma que facilite el análisis global, etc. Mencionó la ya conocida -pero nunca menospreciada- teoría de Avinash 10/90. El concepto es muy simple: Cada $10 que se inviertan en una herramienta de análisis se deben invertir $90 en los analistas. La data por sí sola no hace nada, requiere de personas para sufrir un análisis y luego convertirse en información provechosa para la compañía.
    […]

  131. […]
    Uma mensagem bem bacana que Avinash deixa em seu blog é que, mesmo que você vá somente até a 3a etapa, você terá aprendido alguma coisa. Mas que você cumpra todas etapas e como ele, possa agregar mais valor estratégico fornecendo mais Insights em vez de Apenas Relatórios. As informações deste post foram retiradas do blog de Avinash Kaushik. Post The 10 / 90 Rule for Magnificent Web Analytics Success.
    […]

  132. […]
    When the Gods of Web Analytics spake, they set forth a rule. You spend on people and process ahead of technology. 10/90 even. When talking about spending 90% on people… this isn’t what the Gods intended. Implementation is supposed to be included in the 10%. Compounding the problem, by defining requirements that impose on collection, and by not capturing data objectively, a level of bias is introduced the data being collected. This is where time should be set aside to consider what could be missing and how to bring it into the fold.
    […]

  133. […]
    (I shall ignore for the moment Avinash Kaushik’s often ignored assertion that 90% of your budget for technology – in his case, analytics – should be spent on the people rather than the technology itself. But it’s an interesting thought to keep in mind as you read through this post…)
    […]

  134. […]
    But now we have the benchmark and can see the gap, there is a strong case for considering what skills are really needed. And whilst brands need a robust tool set to pull the information, I am reminded of some sensible advice from Avinash Kaushik: for every $10 spend on a tool or technology, $90 should be spent on intelligent resources/analysts
    […]

  135. […]
    But now we have the benchmark and can see the gap, there is a strong case for considering what skills are really needed. And whilst brands need a robust tool set to pull the information, I am reminded of some sensible advice from Avinash Kaushik: for every $10 spend on a tool or technology, $90 should be spent on intelligent resources/analysts. Now is the time to invest in training, skills and building corporate knowledge in analytics!
    […]

  136. […]
    Avinash Kaushik has the 10/90 Rule when it comes to budgeting for analytics. The 10/90 Rule says that your budget should be divided as 10% for the analytics tools and software and 90% for the people doing the analysis, The point being people and brain power trump data gathering so software costs every time. This applies to any plan for social media listening.
    […]

  137. […]
    The 10/90 rule for magnificent data success still holds true. The 10/90 rule is a safest bet in making smart decisions that can be applied everywhere. Invest 10 per cent in the tools and vendor services but the other 90% should be on the people. It might seem ridiculous at first glance, but the best investment made has always been proven to be people and not on products, in this case artificial intelligence that isn’t quite developed.
    […]

  138. […]
    La buena noticia es que en la analítica web, estas limitaciones de presupuesto no deberían condicionar tu proyecto. Si necesitas mármol de Carrara, tendrás mármol de Carrara, aún a precio de ladrillo de adobe. Es sólo una cuestión de saber escarbar entre tus datos para obtener este valioso material (datamining). Esto es así debido a lo que el Sr. Kaushik denomina la “Regla del 10/90 para un exitoso análisis web“, que viene a ponderar la importancia del analista web, y su capacidad para separar el grano de la paja, sobre costosas herramientas.
    […]

  139. […]
    I was able to relay the information from the blog post http://www.kaushik.net/avinash/the-10-90-rule-for-magnificient-web-analytics-success/ into an info-graphic.
    […]

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