Practical Growth Hacking for B2B & B2C - DAY 0
Welcome to the series of "Practical Growth Hacking"! In these set of articles we are going to explore all the crucial growth hacking, data and coding techniques for being a world-class growth hacker.
After spending 6 years on growth hacking and leading two teams that contributed to two unicorns, I thought it was time to share this knowledge.
Actually, it is not the first time I have done it. In 2019, I published the Data-Driven Growth Series, which was mainly about using practical data science models to solve real-world customer lifetime problems. Luckily, it ended up getting a great response from the community, and the overall series had 1M+ views.
But….
Building a series of articles is a tough and lengthy task. Like many writers, I took some shortcuts to get the articles out faster and keep readers engaged. These shortcuts included using datasets that fit exactly with the analytics I wanted to show. But in real life, things aren't so straightforward. You often have to sort out messy data or clean it a lot before analyzing it. Also, no one hands you a ready-made CSV file for building a data science model; you usually have to pull data from databases, and this requires basic skills in SQL, a computer language for managing data.
In this series, for B2C practices, we will start from the beginning; you will have a MYSQL database, learn SQL, practical data science skills, essential data-driven models for Growth Hacking, and even a few programming tricks.
In the B2B world, things look a bit different. There aren't many technical articles out there; most guides focus on general strategies, mainly for selling their own products eventually, rather than offering practical learning. We'll dive into various straightforward and effective methods that address everyday challenges, and yes, we'll be rolling up our sleeves to do some coding! 😊
Our initial roadmap for B2B and B2C will be separate and as follows (articles will be written simultaneously):
B2C:
- Coding Skills:
- Essential Growth Metrics & Models:
Customer Segmentation
Customer Activation Strategy
Customer Churn Prediction
Customer LTV Prediction
Booking/Transaction Prediction
AB Testing & Sample Selection
Recommendation Engine
Marketing Mix Model
Market Basket Analysis
B2B:
How to Define Your Potential Client Segments and Decision Makers with AI
Building Potential Client - Company Database
Building Potential Client - Contact Database
How to Write Cold Emails with AI
How to Validate Contact Emails
How to Automate Email Sequences
How to Generate Ad Creatives with AI
By the end of this journey, you will have many practical skills that you can apply and automate with coding. The rest will depend on your creativity :)
Let’s start…and happy hacking!