I will spare you a paragraph on why you should read more, the wiser have elaborated on this. I consider reading as a shortcut in one’s life and career. I have benefited greatly from it.

Unlike engineers and scientists, marketers don’t have a set list of books we read (although there are a few I personally think are). Maybe that is why I’ve come across many marketers asking for book recommendations. So I thought it would be helpful to share my personal library, and only those I think are great, with anyone that is interested.

This Notion list covers books…

Visualization

“You cannot manage what you cannot measure. “

— Peter F. Drucker

Analysts spend a good chunk of time building dashboards. The goal is to make basic insights discovery as self-serving and as automated as possible to avoid too many ad-hoc analysis. However, while the impact of other parts of the job (e.g. experimentation, modeling, strategic recommendations, etc.) can be easily shown afterward; the success of dashboards is often harder to measure. There are just so many questions to ask when considering if a dashboard works or not, so often people don’t ask them at all.

But the danger of…

D3.js

When I was learning D3, although there are a lot of great resources to learn from, I can rarely find detailed code explanations for me to fully understand how everything works, making it difficult to recreate a chart on my own without additional searches.

So I want to fill this whitespace with a series of D3 (v4) line-by-line code explanations for each chart I create, sharing with you what I’ve figured out. Comment if you want me to create a video series!

Let’s kick off this series by building a tree chart like the one below.

If you are completely…

Analytics

I will spare you an entire post on why running controlled experiments is the gold standard for data-driven decision making or how to run them (so many books and posts on this). If you are reading this, you would already know that controlled experiments (or A/B testing, multivariate testing) are one of the most effective ways to make causal inferences, to scientifically validate most ideas.

In the early stage of a business, it is okay to base decisions on HiPPO (Highest paid person’s opinion) and past experiences, given the lack of data. …

If you found yourself doing repetitive work, automate it. This is a case I came across more than once recently — thought it’s worth sharing with who might have a similar problem.

The problem: Your output (name+ranking) is sorted by the namecolumn alphabetically. Your stakeholder needs the data frame to be sorted by the order of the key column specified by them.

The solution

1. Transform the sort_key and the original output into data frames.

import pandas as pd sort_key=['Apple','Alphabet','Microsoft','Samsung','Huawei','IBM','Facebook','Cisco Systems','HP Inc.','Intel','Dell','Xiaomi','Oracle','SAP','Hitachi','Salesforce','Uber']data=['Apple','Alphabet','Cisco Systems','Dell','Facebook','Hitachi','HP Inc.','Huawei','IBM','Intel','Microsoft','Oracle','Salesforce','Samsung','SAP','Uber','Xiaomi']ranking=[2,1,12,20,10,29,15,6,8,19,4,25,35,5,27,37,24]df_key=pd.DataFrame({'key':sort_key})df=pd.DataFrame({'name':data,'ranking':ranking})

2. Do an outer join using pd.merge

I’ve been getting so many content ideas from Reddit. Reddit is so underrated on so many levels — another post for another time (follow me on Reddit).

Many people there ask about how to do YoY comparisons in Tableau. Understandably so, it’s one of the most common ways to benchmark KPIs. In many industries like e-commerce, day of week (DOW) also needs to be matched year over year to do a fair comparison. And this is actually really easy to do it in Tableau.

1. We use the formula below to adjust the previous year’s dates to this years with DOW…

Ahh. Where do I begin! It answers a lot of questions I have around growing my site (goodmarketing.club) right now.

The part about understanding your dream customers and find out where they hang out is super helpful. I now understand why my posts in sub reddits where marketing/analytics people are brought me a lot of organic traffic and subscribers. And I need to do more work on understanding my dream customers.

Hook, story, offer (having a better offer if no ones takes the current one) and owning your traffic also resonates with me a lot.

This actually might be one of the best marketing practice books I've read ever :)

The best lies are half-lies and half-truth. The same applies to April Fools’ Day campaigns.

But things can easily go south depends on what you decide to lie about. Note that sending your customers a fake €400 bill is not funny.

I cannot help but wonder, with the risk of making a fool of themselves and their customers, why should brands do April Fools’ Day campaigns? Well, it depends on what you want to achieve with this campaign.

1. To make some buzz and build brand awareness

2. Engage…