Email ROI Metrics: Advanced Calculation Methods

Accurately measuring and optimizing email marketing ROI is critical for driving business growth. However, calculating true ROI goes beyond simple open and click rates. In this comprehensive guide, we'll dive into advanced methods for calculating email ROI, including multi-touch attribution models, customer lifetime value (LTV) calculations, and cohort analysis. We'll also explore best practices for tracking key metrics, attribution across the full customer journey, and strategies for optimizing campaigns based on ROI insights. By the end, you'll have a robust framework for quantifying the true business impact and profitability of your email marketing efforts.

Understanding Email Marketing Metrics

Before diving into advanced ROI calculation methods, it's important to have a solid grasp of the key metrics involved. Let's review the primary email marketing KPIs:

• Open Rate: The percentage of recipients who opened your email
• Click-Through Rate (CTR): The percentage of recipients who clicked on a link within your email
• Conversion Rate: The percentage of recipients who completed a desired action (e.g. made a purchase) after clicking through your email
• Revenue Per Email: The average revenue generated per email sent
• Return on Investment (ROI): The overall profitability of your email campaigns, calculated as (Revenue - Cost) / Cost

While these metrics provide a good starting point, they don't always tell the full story of an email campaign's impact. Open and click rates, for example, don't account for the quality or value of the actions taken. A campaign with a lower CTR but higher conversion rate and average order value may actually be more profitable.

The following diagram illustrates how these basic email metrics fit into the larger customer journey and purchasing funnel:

Attribution Models for Email Marketing

One of the key challenges in calculating email ROI is properly attributing conversions and revenue to the right campaigns. A customer may receive multiple emails before making a purchase, so which ones get credit? Attribution models help solve this by defining rules for assigning conversion value across touchpoints.

First-Touch Attribution

In this model, 100% of the conversion value is attributed to the first email campaign the customer interacted with. This is a simple method, but doesn't account for the influence of subsequent messages.

Last-Touch Attribution

Conversely, last-touch attribution gives all the credit to the final email campaign the customer engaged with before converting. This tends to overvalue bottom-of-funnel campaigns while ignoring the impact of earlier touches.

Linear Attribution

Linear attribution assigns equal weight to each email touch point along the customer journey. So if a customer received and engaged with three emails before converting, each campaign would receive 33.33% of the conversion value.

Time-Decay Attribution

This model gives more credit to touchpoints closer in time to the conversion event. The exact weighting is determined by a half-life decay formula, but generally, more recent campaigns will receive a larger share of the attribution.

Here's a visualization comparing how conversion value is distributed among four email touchpoints under different attribution models:

Custom or Algorithmic Attribution

For maximum control and accuracy, many advanced marketing teams create their own custom attribution models. These often leverage machine learning algorithms to calculate the true impact of each touchpoint based on large-scale data analysis.

Custom models can incorporate factors like:

• Email engagement rates
• Time between touches
• Customer attributes or segments
• Position in the buying cycle
• Other marketing channel interactions

Incorporating LTV into Email ROI Calculations

Customer lifetime value is a critical, but often overlooked, factor in email marketing ROI. Acquiring a new customer is 5-25X more expensive than retaining an existing one, so driving repeat purchases through email can significantly boost profitability.

There are a few main methods for calculating LTV:

LTV = Average Revenue per User (ARPU) x Average Customer Lifespan

Once you have an LTV benchmark, either for your overall customer base or specific segments, you can calculate the ROI of retention-focused email campaigns with more accuracy.

So instead of just evaluating a campaign on immediate revenue, you could measure it based on the LTV impact. For example, a campaign targeting recent first-time buyers with a discount for a second purchase could be evaluated on the downstream revenue it helped drive over those customers' lifetimes.

Here's a simplified visual comparing how ROI looks for a winback campaign when evaluating on first purchase only vs. incorporation LTV:

Cohort Analysis for Email Campaigns

Grouping customers into cohorts based on acquisition date or campaign engagement is another powerful way to measure long-term email ROI. Cohort analysis lets you monitor how different groups of customers engage and convert over time.

Cohort data is typically visualized in a table like this:

Some key metrics to track and compare across cohorts include:

• Conversion rates over time
• Revenue per user
• Purchase frequency
• Average order values
• Churn or retention rates

For example, you might find that customers acquired through a specific lead magnet or promotion have higher-than-average purchase activity in their first 30 days, but then drop off sharply. Armed with that insight, you could develop an onboarding email flow to encourage second and third purchases in that crucial period.

This visual illustrates how revenues and retention change over time for different monthly signup cohorts:

Email Experimentation & Optimization

Advanced data analysis and ROI calculations aren't just academic exercises. The true power comes from leveraging those insights to optimize your email strategy.

Campaign and email-level experimentation is crucial. By running A/B tests and measuring results, you can zero in on the strategies that drive the greatest response rates, engagement, and revenue for your business.

Elements to test include:

• Subject lines & preview text
• Calls to action (CTAs)
• Creative, like hero images or GIFs
• Send day and time
• Email length and content type
• Offer or promotion
• Audience segments or personalization

Optimizing Key Email Flows

Triggered email automations, like welcome series, cart abandonment, and post-purchase flows, tend to drive a disproportionate amount of email revenue. Optimizing these critical campaigns can have a massive impact on overall ROI.

Some best practices and experiments to try:

Closely monitoring the revenue per email, conversion rate, and long-term impact of these core automation flows will help you identify optimization levers.

Conclusion & Key Takeaways

Mastering advanced methods for email ROI calculation is critical for ecommerce brands looking to scale efficiently and profitably. Remember, open rates and clickthroughs only tell one part of the story.

To truly measure and maximize email marketing ROI, you need to:

1. Implement multi-touch attribution models to properly assign revenue across the full customer journey ATTRIBUTION
2. Incorporate customer lifetime value (LTV) into ROI equations for key retention and winback campaigns LTV
3. Leverage cohort analysis to understand how customer value and engagement evolves over time for different segments COHORT ANALYSIS
4. Double down on email automations with the highest long-term impact like welcome series, cart recovery, and post-purchase AUTOMATION
5. Continuously experiment and optimize every aspect of your email program TEST & OPTIMIZE

Here's a final graphic summarizing the key components of a profit-driven email marketing machine:

Additional Email Marketing Resources:

• The Ultimate Guide to Email List Hygiene
• 10 Proven Strategies for Reducing Email Unsubscribes
• How to Create High-Converting Landing Pages for Email Campaigns
• The Ecommerce Marketer's Playbook for Browse Abandonment Emails