The Website Conversion Code: Maximize Revenue From Every Visitor

Module 1.1: Foundations of Customer-Centric Optimization

Why customer-centricity matters in CRO

Common website conversion barriers

The business impact of customer-focused design

Module 1.2: Customer Research Fundamentals

Qualitative vs. quantitative research methods

Voice of Customer (VOC) data collection

Understanding customer pain points

Module 1.3: Creating Effective Customer Personas

Building data-driven personas

Understanding customer motivations

Using personas in optimization

Module 1.4: Customer Journey Mapping

Mapping the conversion funnel

Identifying key touchpoints

Understanding micro-conversions

Module 1.5: The LIFT Model in Practice

Value proposition optimization

Reducing friction points

Addressing anxiety elements

Adding urgency appropriately

Module 1.6: Strategic CRO Planning

Creating a structured optimization roadmap

Resource allocation

Setting realistic timelines

Measuring progress

Module 1.7: Advanced Customer-Centric Strategies

Personalization fundamentals

Segmentation strategies

Multi-device optimization

Module 2.1: Understanding Consumer Psychology

Basic psychological principles

Decision-making frameworks

Cognitive biases in online behavior

Module 2.2: Emotional vs. Rational Decision-Making

The role of emotions in conversions

Balancing logical and emotional appeals

Creating emotional resonance

Module 2.3: The Psychology of Trust

Building credibility online

Trust signals and social proof

Overcoming skepticism

Module 2.4: Persuasion Architecture Basics

Cialdini's principles in CRO

Creating compelling narratives

Effective call-to-action design

Module 2.5: The PIE Prioritization Framework

Potential impact assessment

Implementation difficulty

Experiment importance

Module 2.6: Advanced Persuasion Techniques

Loss aversion in practice

Scarcity and urgency

Social validation

Module 2.7: Psychology-Based Testing Strategy

Creating psychology-informed hypotheses

Measuring psychological impact

Long-term vs. short-term effects

Module 3.1: Introduction to Scientific Testing

Why scientific testing matters

Common testing myths

The cost of untested changes

Module 3.2: A/B Testing Fundamentals

Basic statistical concepts

Test design principles

Control vs. variation groups

Module 3.3: Sample Size and Statistical Power

Calculating required sample size

Understanding statistical power

Duration planning

Module 3.4: Validity in Testing

Internal validity threats

External validity considerations

Preventing contamination

Module 3.5: Advanced Testing Methods

Multivariate testing

Sequential testing

Factorial designs

Module 3.6: Results Analysis

Statistical significance

Practical significance

Confidence intervals

Module 3.7: Common Testing Pitfalls

Multiple testing problems

Simpson's paradox

Interaction effects

Module 4.1: Foundations of Experimentation Culture

How successful organizations embrace experimentation

Moving from individual testing to organizational capability

Creating psychological safety for testing and learning

Module 4.2: Building Your Optimization Team

Essential roles and responsibilities

Hiring and training for experimentation

Cross-functional collaboration models

Team structure and reporting lines

Module 4.3: Experimentation Processes & Systems

Creating reliable experimentation workflows

Documentation and knowledge sharing

Tools and technology stack

Quality assurance processes

Module 4.4: Scaling Optimization Programs

Moving from single tests to program management

Resource allocation and prioritization

Managing multiple testing streams

Cross-product experimentation

Module 4.5: Data-Driven Decision Making

Embedding testing in business decisions

Balancing speed and rigor

Managing stakeholder expectations

Using data to drive organizational change

Module 4.6: Managing Organizational Politics

Handling resistance to testing

Building executive support

Managing competing priorities

Communicating test results effectively

Module 4.7: Measuring Program Success

Program KPIs beyond test results

Velocity and impact metrics

ROI of experimentation programs

Long-term success indicators

Module B.1: The Psychology of Small Business Websites

Understanding how visitors make decisions on small business websites, focusing on trust-building and credibility when competing with larger brands.

Module B.2: Smart Research Methods for Limited Traffic

Mastering alternative validation techniques that work with small visitor numbers, from customer interviews to behavior analysis.

Module B.3: Heatmaps, Recordings, and User Feedback

Leveraging qualitative tools to understand visitor behavior and identify optimization opportunities without needing large traffic volumes.

Module B.4: High-Impact Optimization Techniques

Implementing proven psychological principles that improve conversion rates regardless of traffic levels, focusing on immediate impact changes.

Module B.5: Measuring Success Beyond Split Tests

Using alternative metrics and measurement approaches to validate optimization efforts when A/B testing isn't viable.