Avinash Kaushik

GA's paradigm is based on the Acquisition/Behavior/Conversion model championed by Avinash Kashik. His blog and Google's own courses are great starting points. https://www.kaushik.net/avinash/ https://www.kaushik.net/avinash/digital-marketing-and-measurement-mode… https://analytics.google.com/analytics/academy/

I appreciate you sharing your information as it came across as an honest attempt to be helpful, however I think you might find it helpful to read this post by Avinash Kaushik [1] and then reread my post. I do digital advertising for a living, and that post is what I recommend to all who are new to the concept of cross-channel attribution as it is a very complex topic from both a data, math, and business standpoint. Easily one of the biggest opportunities and problems in the ad industry at the moment (and has been for some time). [1] http://www.kaushik.net/avinash/multi-channel-attribution-modeling-good…

The point is that numbers in themselves means nothing to most people and are actually not actionable. The purpose of a dashboard is to give instant feedback on something that requires it. (Driving a car, airplane, nuclear reactor, space station, server load) i.e. if something is wrong you should be able to see it right away so you can take action. The dashboards we see today are more like vanity boards which feed our need for new information but doesn't really serve any other purpose. A really good read on the subject is this one http://www.kaushik.net/avinash/smart-analytics-dashboard-modules-insig…

I recommend two resources on creating dashboards, both from very experienced practitioners: 1) http://www.kaushik.net/avinash/digital-dashboards-strategic-tactical-b… 2) Information Dashboard Design by Stephen Few - http://www.amazon.ca/Information-Dashboard-Design-Effective-Communicat…

It really depends who you talk to. At Groupon EU, Japan, Korea and USA we called customer life time value "LTV". Also, Avinash Kaushik, author of one of the best books on Web Analytic and previous Google Evangelist, uses LTV as well. http://www.kaushik.net/avinash/analytics-tip-calculate-ltv-customer-li…

You might want to follow Avinash Kaushik (hopefully I wrote it right), his blog is quite popular and for very good reasons: http://www.kaushik.net/avinash/ His book, Web Analytics 2.0, is an eye opener in terms of defining your own goals and processes, highly suggested.

Avinash Kaushik's blog is pretty fantastic (http://www.kaushik.net/avinash/). Pretty much every post is packed with actionable information.

Avinash Kaushik's stuff is great - http://www.kaushik.net/avinash/ And his books are also excellent - he's written "web analytics 2.0" and "web analytics - an hour a day"

The best way imho to do this is to ignore the individual variables and think about what your business goals and objectives are. When you have a firm grasp of what those are you can then shape the metrics you are looking at to give you insight into how they effect your overarching goal. Here's a fantastic piece by the ever amazing Avinash Kaushik that highlights this: http://www.kaushik.net/avinash/2010/11/web-analytics-maturity-structur…

I highly recommend Avinash Kaushik's blog - http://www.kaushik.net/avinash/ and mixergy interview - http://mixergy.com/analytics-avinash-kaushik-interview/. A key point he made in his interview was that tools should just be 10% of the cost of your analytics, the people should be 90%. He might help you make a more informed decision.

http://www.kaushik.net/avinash/ People I trust have told me his books are great reads. I'm self-taught on analytics and blog about it, but it is probably scattered over the last couple of years of posts. I wouldn't recommend it for an entry to the discipline.

There are two great books for you: 1. Web Analytics 2.0, by Avinash Kaushik. He's the Analytics evangelist at Google and his book is very easy to read. Start here. He also keeps a blog: http://www.kaushik.net/avinash/ . The archives are a gem of a resource. 2. Advanced Web Metrics with Google Analytics by Brian Clifton. A much drier read (the guy has a PhD in Chemistry and writes with the dry academic style) but an excellent resource. There is a blog with much lower volume of posting: http://www.advanced-web-metrics.com/blog/ .

This is a post about tracking the increase of active blog readers. I think it can be taken as a broad parallel to active users. http://www.kaushik.net/avinash/2007/11/blog-metrics-six-recommendation… By measuring well you may find some insight that'll help. The jist of the examples is that readers (apply to users) are acquired one at a time. Digg, stumble & such are not going to give you a massive spike in users. Nothing probably will. Its about momentum. Anyway, maybe you will find some answers in analytics.

As a product manager I face this dilemma as well. I work on side projects but I'm not a great coder and not a great designer. The following areas have helped me become more 'active' in the early development process: -Learn an analytics engine (I like Google Analytics) like the back of your hand. Help engineers build great testing tools that work well w/ your analytics engine, then segment + comb the data for patterns that shape the direction of the company. (see: http://www.kaushik.net/avinash/ and buy "Web Analytics 2.0" from Amazon for more info) -Become very familiar with A/B split testing and other forms of automated online testing. Try to gain an understanding of adwords as well so you can send targetted users to your offerings and help developers make informed decisions about whether or not the product will have interested users that are cheap to acquire off the bat. (see: http://visualwebsiteoptimizer.com/split-testing-blog/ for expertise/more info) -Buy Silverback (http://silverbackapp.com/) and conduct user tests CONSTANTLY as in every day. Continously analyze the product, summarize user input, and pass that info off to development. -Buy Balsamiq Mockups (http://www.balsamiq.com/products/mockups) and start prototyping pages with improvements or new features for existing apps. This can filter into User Experience/Information Architecture and I find that it's the best way for a 'product manager' to bridge the gap between design and development. Sorry I know that…

Federated protocols are decentralized, though; there's no central point of control. This graphic has been done to death at this point but it's relevant here: https://www.kaushik.net/avinash/wp-content/uploads/2009/12/centralized…

edit: for lesser known, I would say: - Whitney Johnson's blog on disrupting yourself: http://whitneyjohnson.com - Occam's Razor on data driven marketing: http://www.kaushik.net/avinash/ - Copyblogger (probably in the well known bucket but still really good): http://www.copyblogger.com/blog/

I would start first and foremost with mastering analytics. All other strategies will fall into place when you have accurate data to measure your impact. If there is only one website you ever visit to learn marketing it should be Occams Razor by Avinash Kaushik. http://www.kaushik.net/avinash/ If you want the fundamentals, read some of Dan Kennedy's books like The Ultimate Marketing Plan. Good Luck.

See also: http://www.kaushik.net/avinash/2010/09/end-dumb-tables-web-analytics-t…

There are lots of companies with more than 127,104 employees that manage just fine. Boing across the street for instance. The reason for the cuts is two fold. First, Microsoft acquired Nokia and they're going to let go of all of most of the non-engineering staff, as well as a lot of the management. Second, Microsoft just restructured itself. It used to run like a conglomerate with VP essentially running their individual business like a fifedom ala the organizational chart comic (http://www.kaushik.net/avinash/wp-content/uploads/2012/08/org_structur… Over the last 3 years there's been a series of high profile executives let go with the intent of increasing cooperation between the divisions, then last year the company restructured going from 9(?) divisions down to 4. As a result there's a lot of redundant people and teams. This house cleaning is in part a result of that.