The Science of Email Conversion

Two Formulas, One Goal

“I don’t get it,” Jessica from ACME Inc. stared at her screen, frustrated. “Our open rates are decent. Our emails look great. Why aren’t we seeing better results?”

The answer was sitting right there in her inbox. ACME’s latest email campaign was a perfect example of why good-looking emails often fail to convert.

Subject: 🔥 HUGE ANNOUNCEMENT! Multiple Exciting Updates Inside! 🔥

The email itself was beautifully designed. Professional images. Perfect branding. Multiple calls to action for different types of customers. They’d followed all the “best practices” they could find online.

Yet their conversion rates were abysmal.

The Hidden Pattern of Success

Here’s what ACME Inc. didn’t understand: Email conversion isn’t one process – it’s two distinct psychological events happening in sequence.

[First diagram showing email to landing page flow]

Think of it like a relay race. Your email isn’t the finish line – it’s just the first runner. It needs to pass the baton cleanly to your landing page to complete the race.

This is where MECLABS’ research becomes fascinating. After studying thousands of email campaigns, they discovered two formulas that, when used together, can dramatically improve your results.

The First Runner: Your Email

Here’s the first formula:

eme = rv (of + i) - (f + a)

Let’s break this down:

  • eme is your email’s effectiveness
  • rv is relevance to the recipient
  • of is the value of your offer
  • i is their incentive to act
  • f is friction in the process
  • a is anxiety about taking action
flowchart LR
    A[Email Message] --> B{Relevance rv}
    B -->|Multiplies| C[Offer of + Incentive i]
    B -->|Impacts| D[Click Decision]
    C --> D
    E[Friction f] -->|Reduces| D
    F[Anxiety a] -->|Reduces| D
    D -->|Success| G[Landing Page]
    D -->|Failure| H[No Action]

Notice something crucial here: Relevance (rv) multiplies everything positive. You could have the best offer in the world with the strongest incentive, but if it’s not relevant to the recipient, those elements might as well be zero.

This explains why ACME’s “everything for everyone” approach fails. When you try to be relevant to everyone, you end up being truly relevant to no one.

The Second Runner: Your Landing Page

Here’s where it gets really interesting. Your landing page has its own formula:

C = 4m + 3v + 2(i-f) - 2a

Where:

a is anxiety about taking action

C is probability of conversion

m is visitor motivation

v is clarity of value proposition

i is incentive to take action

f is friction elements

flowchart TB
    subgraph Conversion Formula
        M[Motivation 4m] --> |Strongest Impact| C{Conversion}
        V[Value Prop 3v] --> |Strong Impact| C
        I[Incentive 2i] --> |Medium Impact| C
        F[Friction 2f] --> |Reduces| C
        A[Anxiety 2a] --> |Reduces| C
    end
    
    style M fill:#4CAF50,stroke:#333,stroke-width:2px
    style V fill:#8BC34A,stroke:#333,stroke-width:2px
    style I fill:#CDDC39,stroke:#333,stroke-width:2px
    style F fill:#FF9800,stroke:#333,stroke-width:2px
    style A fill:#F44336,stroke:#333,stroke-width:2px
    style C fill:#2196F3,stroke:#333,stroke-width:2px

Let’s also look at a version that shows how different elements might manifest on an actual landing page:

flowchart TB
    subgraph Landing Page
        H[Header: Problem Statement] --> |4m| M[Motivation]
        VP[Clear Value Proposition] --> |3v| V[Value]
        CTA[Call to Action] --> |2i| I[Incentive]
        
        subgraph Reducing Elements
            F1[Form Fields] --> |2f| FR[Friction]
            F2[Loading Time] --> |2f| FR
            A1[Trust Signals] --> |2a| AN[Anxiety]
            A2[Social Proof] --> |2a| AN
        end
        
        M --> C{Conversion Probability}
        V --> C
        I --> C
        FR --> |Reduces| C
        AN --> |Reduces| C
    end

Making the Formulas Work Together

flowchart TB
    subgraph Email Formula
        R[Relevance rv] --> O[Offer of]
        R --> I1[Incentive i]
        O --> E[Email Success]
        I1 --> E
        F1[Friction f] --> |Reduces| E
        A1[Anxiety a] --> |Reduces| E
    end
    
    subgraph Landing Page Formula
        M[Motivation 4m] --> C[Conversion]
        V[Value 3v] --> C
        I2[Incentive 2i] --> C
        F2[Friction 2f] --> |Reduces| C
        A2[Anxiety 2a] --> |Reduces| C
    end
    
    E --> |Feeds Into| M
    O --> |Aligns With| V
    I1 --> |Continues In| I2

Here’s how to apply these formulas in practice:

  1. Start with Relevance
    • Who is this person?
    • What do they care about right now?
    • How does your message connect to their current needs?
  2. Build Value Through Alignment
    • Email offer sets expectation
    • Landing page delivers on that promise
    • Each step builds on the previous
  3. Maintain Momentum
    • Email creates specific motivation
    • Landing page addresses that specific motivation
    • No surprises or disconnects
  4. Reduce Barriers Throughout
    • Keep email focused on one action
    • Make landing page continuation obvious
    • Address concerns at each step

The Real-World Application

Remember Jessica’s frustration at ACME Inc.? Let’s see how these formulas would fix their announcement email:

Instead of “HUGE ANNOUNCEMENT! Multiple Exciting Updates Inside! 🔥”

They could segment their list and send:

  • To feature requesters: “That [feature] you asked for? It’s ready”
  • To active users: “New: Finish [common task] 2x faster”
  • To trial users: “The upgrade that matters for [their use case]”

Each version would lead to a landing page specifically designed to continue that conversation.

The Practical Framework

When creating any email campaign, map out:

  1. The specific relevance for each segment
  2. The clear value proposition
  3. The natural incentive to act
  4. The potential friction points
  5. The likely anxiety elements

Then ensure your landing page continues this thread while building motivation toward conversion.

Because at the end of the day, email marketing isn’t about sending emails – it’s about creating conversions. Understanding and applying these formulas helps ensure every element works together toward that goal.

Next, we’ll look at how to define the specific point of each email to make these formulas work in practice…

Next chapter: Defining Your Email’s Point

Nem Puhalo Circle

Nem Puhalo

Marketer