Video: Successful Web Analytics Approaches by Avinash Kaushik

Again a great video, this time about Web Analytics by Avinash Kaushik. I just love his no-BS style.

  • Ask the metric: So what? Three times, if it don’t give an action it’s useless
  • Data should drive action
  • Give people the information they need – don’t send them everything => no death by data
  • Home pages of websites, are no longer the home page you want
    • Where do people come from?
    • What are they looking for?
  • Context matters: previous months, years, etc.
  • Relative numbers more important than absolute numbers
  • Compare different metrics, e.g. conversion rate and page views
  • non e-commerce sites:
    • averages hide truth effectively
    • How often do they visit?
    • How recent did they visit?
    • Depths of visit
    • => Understand the value: Loyalty
  • Segment people
  • Survey people: What do they think about the content?
  • Bounce rate: Came and left
    • Segment by source, entry-page, landing pages, etc.

Rules for Revolutionaries

  • 10/90 Rule: $10 Tools, $90 People: Understand Data & Business, Able to analyze => to extract value
  • Reporting is not analysis: Reporting -> provide data; Analysis -> prove insights
  • Data Quality can be low, but is still better than other data
  • Faith-based initiative: e.g. magazine ad without tracking
  • Make decisions, don’t argue about the quality of the data
  • Over time understand why quality is different -> confidence will get better


  • Decision making is a journey, not a destination
  • => Put some level of process in place, mostly for tasks, e.g. what happens to implement a test, etc.
  • if HiPPo (highest paid person’s opinion) makes the most decisions
  • => make experiments
  • Learn to be wrong, quickly
  • => You probably don’t know what your customers want
  • => Experimentation

#13/111: Where Good Ideas Come From

What is it about?

Steve Johnson tries to find an inherit structure in innovation in nature and our life. He explains seven different characteristics of innovation and environments which supports innovation. However he remarks that not all these principles are necessary for innovation!

Key points?

Adjacent possible: Innovation is about widening the existing border of knowledge.

Slow hunch: Most innovation doesn’t happen immediately, rather it is carried out over a long time.

Error: Innovation has a high signal:nose ratio. Generate lots of ideas and fail fast.

Exaptation: Often ideas are useful in an other way, e.g. Gutenberg used wine presses for printing books.

Platforms / Liquid networks: Ideas want to be shared and combined. Create platforms for people and technology (e.g. the web)


One thing is really remarkable. He takes the story of Darwin’s voyage with the Beagle and tells it through the whole book. There are various other stories but this is central theme. This makes this book easy to read and actually exciting! These other stories fit well into his chapters. Although the conclusion wasn’t that good. He tried to support his theory and became too fuzzy.

In conclusion, he has observed the world of innovation doubtlessly well but without execution ideas are nearly worthless.