Growth Hacking Strategies

Data driven approaches to rapid, sustainable business growth

Onboarding and Habit Formation: The Science of Making Products Stick

A comprehensive deep dive into the psychology and mechanics of user onboarding and habit formation. From finding your product's Aha moment through cohort analysis to Nir Eyal's Hook model, James Clear's habit stacking, the Zeigarnik effect, endowed progress effect, and goal gradient effect. Includes Chamath Palihapitiya's Facebook growth team methodology, research data, Python code for measuring activation, and practical implementation strategies.

Conversion and UX Psychology: The Science of Why Users Click or Bounce

A comprehensive deep dive into the psychological laws that govern user behaviour and conversion. From Hick's law and Fitts's law to the peak-end rule, serial position effect, Miller's law, cognitive load theory, friction frameworks, and attribute framing. Includes research data, Python code for measuring UX impact, and practical implementation strategies backed by Baymard Institute research.

Behavioural Economics Frameworks: The Science of How Customers Actually Decide

A comprehensive deep dive into the behavioural economics frameworks that shape consumer decisions. From Kahneman's dual process theory to Thaler's choice architecture, cognitive biases, hyperbolic discounting, mental accounting, choice overload, and status quo bias. Includes when each framework applies, how to design for real human behaviour, and Python code for measuring effectiveness.

Referral and Viral Mechanics: Engineering Exponential Growth

A comprehensive deep dive into the mathematics and psychology of referral programmes and viral growth. From K-factor calculations to viral cycle time, two-sided incentives, network effects versus viral effects, referral psychology, Jonah Berger's STEPPS framework, and NPS as a growth predictor. Includes Python code for modelling viral growth and measuring programme effectiveness.

Social Proof and Trust: The Psychology of Why We Follow the Crowd

A comprehensive deep dive into the psychology of social proof and trust in marketing and product design. From the six types of social proof to review psychology, authority signals, trust stacking, reciprocity, and herd behaviour. Includes when each strategy works (and when it backfires), research from Spiegel and Baymard Institute, and Python code for measuring effectiveness.

Vibe Coding: The Hidden Cost of AI Built Architectures

A deep dive into the fundamental architectural flaws that emerge when systems are built with AI assistance but without proper planning. Covers database architecture failures, scaling bottlenecks, framework selection mistakes, and the real limitations of popular Python frameworks (Django, Flask, Streamlit, Gradio, Plotly Dash, FastAPI, Reflex) when projects grow. Includes analysis of rapid development frameworks, language selection criteria, and why certain technical choices create insurmountable problems at scale. Real examples of where architectural debt catches up with you.

Scarcity, Urgency, and Loss Aversion: The Psychology of Now or Never

A comprehensive deep dive into the psychology of scarcity, urgency, and loss aversion in marketing and product design. From Cialdini's scarcity principle to the endowment effect and IKEA effect. Includes when each strategy works (and when it destroys trust), how to measure effectiveness with data science, and Python code for experimentation.

Less Well Known but Battle Tested: The Hidden Psychology That Actually Converts

A comprehensive deep dive into 18 lesser-known but highly effective psychology principles for conversion and retention. From goal-gradient acceleration and temporal landmarks to identity-based marketing, implementation intentions, foot-in-the-door, labour illusion, operational transparency, defaults as nudges, status games, sunk cost retention, social comparison, reactance, and risk reversal. Includes research data, Python code for measuring impact, and practical implementation strategies backed by academic literature.

The Math Behind It All: Growth Marketing Mathematics Explained

A comprehensive deep dive into the mathematics that powers growth marketing and data-driven decision making. From LTV:CAC ratio and payback period to cohort analysis, survival analysis with Kaplan-Meier curves, Bayesian A/B testing, multi-armed bandits with Thompson sampling, marketing mix modelling vs attribution, power law distributions, price elasticity with Van Westendorp's price sensitivity meter, and the compounding math of retention. Includes LaTeX formulas, Python code, visual explanations, and practical implementation guidance for both beginners and advanced practitioners.

Pricing Psychology: The Science of Making Your Prices Irresistible

A comprehensive deep dive into the psychology of pricing. From anchoring to prospect theory, learn the cognitive biases that shape how customers perceive value. Includes when each strategy works (and when it backfires), how to measure effectiveness with data science, and Python code for A/B testing your pricing experiments.

TDD and BDD for APIs: When Your Web Apps Need to Talk to Each Other

A deep dive into test driven and behaviour driven development for APIs that connect separate web applications. Covering the unique challenges of distributed systems, contract testing, consumer driven contracts, and how proper testing becomes your most reliable documentation. With detailed comparisons of testing tools for Ruby on Rails and Django.

Why Rapid Development Frameworks Destroy PHP In The Long Run

A brutally honest deep dive into why Ruby on Rails and Django absolutely demolish PHP and other legacy frameworks over time. Covering security, scalability, and most importantly the testing ecosystem that makes bug free releases actually possible. Featuring TDD, BDD, Minitest, RSpec, and Cucumber with real world examples.

Dynamic Pricing With AI: A Growth Hacker's Guide

The dynamic pricing software market is projected to grow from $6.16 billion in 2025 to $41.43 billion by 2033, and 55% of retailers plan to implement AI pricing in 2026. Amazon changes prices 2.5 million times a day. You don't need to be Amazon. This post breaks down how ML-driven dynamic pricing actually works - price elasticity estimation, demand signals, competitor monitoring, and margin guardrails - with practical Solidus/Rails code and Python scripts you can run today.

How Generative AI is Changing Product Discovery

Traffic from AI sources like ChatGPT, Perplexity, and Gemini to ecommerce sites went up 3,300% year-over-year on Prime Day 2025. During the holiday season, AI referrals to retail sites jumped 693%. And here's the kicker - those AI-referred shoppers converted 31% more than visitors from other sources, spent 45% more time on site, and viewed 13% more pages. This isn't a novelty. It's a new discovery channel. This post covers what it means for SEO, product feeds, and how retailers like New Look and Selfridges need to adapt their product data strategy.

Privacy-First Growth Hacking: How to Personalise Without Being Creepy

Third-party cookies are dead, browser tracking is gutted, and regulators are fining companies hundreds of millions for getting consent wrong. But personalisation still works - it just needs a different foundation. This post covers consent-based personalisation, server-side tracking architecture, first-party and zero-party data strategies that actually perform, and the practical Rails code to make it all work across the DACH market. Real examples from four products serving Austrian, German, and Swiss users, with jurisdiction-aware consent handling built in.

Why I Left the Google Ads Partner Programme and Why You Might Want to as Well

For years, I was a certified Google Ads Partner. Not because I wanted the badge, but because I thought it gave my clients confidence. After all, the label implied expertise, accountability, and a seal of quality from the biggest name in digital advertising. But recently, I let the certificate expire. Not due to a lack of ad spend. Not due to a lack of expertise. But because remaining a Google Ads Partner increasingly comes at a cost, one paid by the client.

Why I Moved from Growth Hacking to Data Driven Ecommerce Growth

In this blog post, I explain why I moved away from growth hacking informational websites to focus on transactional websites, such as ecommerce stores and subscription based apps. I delve into the role of data science in overcoming growth challenges and automating marketing campaigns, ultimately leading to more efficient and measurable growth strategies.