20 things I learned from reading Hiten Shah’s new book “5 Habits to Building Better Products Faster”

buildingbetterproducts

Here are the 20 things I learned from reading Hiten Shah’s new (free) book 5 Habits to Building Better Products Faster:

  1. Figure out what your customers need, instead of what you think they need.
  2. The early stages of product development aren’t at all about your constraints or your resources. They’re about focusing on what’s important: the customer.
  3. Work backwards like Amazon. New initiatives start out by writing an internal press release. More details here. Take the example of the press release for Amazon AWS (now a $9.6 billion run rate business):
    AmazonAWSpressrelease
    Writing this took the current head of AWS, Andy Jassy, 31 drafts before he took this to Jeff Bezos
  4. The jobs-to-be-done formula is:
    When_______, I want to _______, so I can ______.
    Check out what Intercom has written about the JTBD framework.
    Intercom’s example: When I talk to customers, I want to start conversations with the right customers at the right time, so I can get quality customer feedback.
    JTBD makes the customer the compass that drives the direction of your product development.
  5. Employee motivation should be aligned with happy customers” – Chris Savage, Wistia CEO
  6. Complex ideas are almost always a sign of muddled thinking or a made up problem.”—Sam Altman, Y Combinator
  7. One of the most important habits for continuous learning and improvement: writing stuff down.
    Documentation is often more a medium of self-discipline than a way to communicate information. -> better quality thinking
    Documentation is a reusable asset, and one that accrues in value and in quantity over time

    But I'm wondering... isn't there such a thing as death by documentation? Documentation overload? Too much documentation, so that the workplace becomes a big swamp, where it's impossible to move fast because you gotta wade through all that documentation?
  8. “The simple and familiar hold the secrets of the complex and unknown. The depth with which you master the basics influences how well you understand everything after that.” —Edward Burger and Michael Starbird, 5 Elements of Effective Thinking
    Start by thinking deeply about the basics, instead of everything that you’re hoping to achieve.
    Thinking deeply isn’t about increasing complexity. It’s about breaking problems down to their most basic form. Reduce the number of steps.
  9. Tony Fadell, who led Apple’s iPod team, spent six weeks in stealth mode looking at the competition.
  10. Otellini’s decision [to say no to Steve Jobs when asked to build a new processor for the first iPhone] was completely logical and also completely wrong.
    Without context and a larger vision for the future, data means nothing.
  11. Summarize findings into a single sentence. This forces you to look away from the numbers, and into what they actually mean for your product.
  12. Before you get started on an initiative, answer the following question: What would success look like?
  13. goodbadexample
  14. Use data to constantly challenge your assumptions, to validate hypotheses, and to solve urgent problems.
  15. The only advantage a startup has over larger companies is the ability to move quickly.
    Your competitive advantage comes from your ability to attack one problem at a time. Why?
  16. Former HubSpot VP of Growth, Brian Balfour, gives a 4-step process for building focus:

    1. Identify one long-term meaningful goal: This might mean boosting the single metric we discussed in the last chapter. The alternative to focusing on one goal that matters is to spread yourself thin on short-term optimizations in order to hedge your bets.

    2. Distill the most important thing to make progress toward that goal. Say that tour goal is to increase inside sales revenue by 40%. Using data has shown you that users integrating other services increases free trial conversions by 3x. You could then focus on getting these trial users on a call with a sales rep.

    3. Create a timeline for making progress long enough to gather data. All product initiatives need to have a clear goal, a measuring stick for what success looks like, and enough time to measure. For small teams, this should range from 30-60 days. Sticking to a timeline ensures that you don’t sink too many resources into a product goal that you can’t achieve. It allows you to move on and focus on the next thing.

    4. Editing your longer-term goal according to data. The fourth step is why it’s so important to set a single measurable goal in the rst place. It’s what allows you to gure out what you’re doing right and wrong, and improve. Making mistakes is forgivable and inevitable in product, but failing to learn from them is wasteful. Startups operate under conditions of extreme uncertainty, and it’s tempting to

  17. Focus + Sequence = Speed
  18. Project management spreadsheet Hiten loves: click here
  19. A small improvement to a high-impact feature is far more important than a large improvement to a low-impact feature.
  20. Every day, ask yourself one question: “Am I working on the right thing, right now?”

I’d highly recommend you get yourself a free copy of the book and study it. Plus, you can even get a free consultation from him, which is freaking insane.

Google Analytics crash course – Reporting overview

I’m currently taking a free course from the Google Analytics Academy on anaytics fundamentals, and this video is super valuable if you want to get a very quick overview of Google Analytic’s reporting features that you can use to poke the data you’ve got in there a bit:

It’s super basic, but a great starting point. Some of the things it covers:

  • how to change date ranges for your reports (and compare to other date ranges)
  • how to change the granularity of the visual time graph (by day, week or month)
  • how to add annotations to specific dates (super useful, I use this all the time as it gives a lot of useful context to historical data when you’ll look at it in the future)
  • how to choose a default metrics for each view (and add a secondary metric to overlay that and be able to compare it)
  • a quick overview over data tables
    It’s useful to know the name of these, just so you’ve got the basic terminology of GA down.
    Data tables break down your data by a single dimension (most of the time). Each table row shows the data for a different value of the dimension
    GoogleAnalyticsDataTable
  • In data tables, you can not only change the primary dimension and add a secondary dimension, but also choose which sets of metrics will be displayed for each dimension. The most common set of metrics is probably the Site Usage set which will show things like number of visits, pages per visit, time on page, bounce rate, and so on.
  • How to filter the data in data tables using simple search queries
  • How to filter the data in data tables by using advanced filters, which allow you for example to show only data where the minimum amount of Visits is above 200, or where the average time on sit is at least 1 minute, or whatever filter will best match your needs.
  • How to change the way data is visualized using the view options (by default, most reports show the data view. But there’s also a percentage view that shows a pie chart, and you can choose which metric to be showed as a pie chart. There’s also a performance view, a comparison view and a pivot view
  • how to plot multiple rows of data
    This was a super useful feature that I wasn’t even aware of until recently, but it’s now one of my favorite features that I use quite often!

Let’s expand a bit on plotting multiple rows of data.

You probably are familiar with this common view of a graph in GA, which plots the number of sessions over a given date range:

GoogleAnalytics-standardgraph

What you can do now is to select additional rows from the data table to be plotted in that graph, in this case, it’s the number of sessions plus various traffic sources which you can see plotted in other colors:

GoogleAnalytics-PlottingRows

I never paid much attention to this, because for me, the term “Plot Rows” wasn’t clear.

But if you look at the meaning, it becomes pretty obvious:

to plot: make a curve by marketing out a number of points on a graph

rows: refers to the rows you select in the data table

Shortcuts in GA

Another cool thing you can learn from this video is how to quickly access custom views that you want to use repeatedly. You can just save them as a shortcut in GA!

Simply click on “Shortcut”, give this shortcut a name, and you’ll be able to access it with just the click of a mouse button.

The shortcuts are available to you in the menubar on the left.

What are Channels in Google Analytics?

First of all, we should start out by saying that Google’s support documentation has the best, most in-depth explanation of this if you’ve got the time to really dig deep.

I’m gonna give you a quick, easy-to-understand high-level overview here.

Channels in Google Analytics are there to group data from various acquisition sources in a way that’s useful to you, the marketer looking at your analytics data.

Google gives you a bunch of Channels right out of the box, called Default Channel Groupings.

Here they are:

defaultchannelgroupings

But you can customize Channels in Google Analytics to better match them for your own needs.