Email Marketing

Mastering Segmentation in email marketing

By Article Monster

November 27, 2025

22 min read

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

This is a simplified example, but it illustrates the basic concept of dynamic content. You can use more complex conditional logic to display different content based on a variety of factors, such as purchase history, browsing behavior, and email engagement. Remember to test your dynamic content thoroughly to ensure that it displays correctly for each segment.

Most email marketing platforms offer dynamic content features. The exact implementation will vary depending on the platform, but the general idea is to use conditional logic to display different content based on the subscriber’s segment.

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Example: Showing different Hero Images based on Location

You can use dynamic content to display different hero images based on the subscriber’s location. For example, if a subscriber is located in a cold climate, you can show them a hero image featuring winter clothing. If they are located in a warm climate, you can show them a hero image featuring summer clothing.

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

In this example, the subject line and the body of the email are personalized based on the subscriber’s browsing history. This makes the email much more relevant and engaging than a generic email blast.

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Dynamic content allows you to display different content within the same email based on the subscriber’s segment. This is a powerful way to create highly personalized emails without having to create separate emails for each segment.

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

For highly engaged subscribers, you can send exclusive content, early access to new features, or special offers. For inactive subscribers, you can create a re-engagement campaign to win them back. If they still don’t engage, you may need to remove them from your list to improve your deliverability.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Remember to tailor the content to each segment. Highly engaged subscribers might appreciate more advanced content or exclusive deals. Inactive subscribers might need a compelling reason to re-engage, such as a special discount or a summary of your best content.

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Creating effective behavioral segments is only half the battle. The real magic happens when you craft personalized email content that resonates with each segment’s unique needs and interests. Generic email blasts are a thing of the past; subscribers expect relevant and valuable content that addresses their specific pain points and desires. This section explores how to tailor your email messages for maximum impact, focusing on personalization techniques, dynamic content, and A/B testing.

Personalization Techniques: Beyond First Name

Personalizing your emails goes far beyond simply including the subscriber’s first name. While that can be a good starting point, true personalization involves tailoring the content to their specific behaviors, interests, and purchase history.

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

For VIP customers, you can offer exclusive discounts, early access to new products, or personalized recommendations. For one-time buyers, you can send a welcome email sequence with a special offer to encourage them to make another purchase.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

For example, if a subscriber has purchased several books in the “Science Fiction” category, you can send them an email featuring new releases and bestsellers in that genre. This type of personalized recommendation is much more likely to resonate with the subscriber than a generic email blast.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Explanation:

This PHP script listens for POST requests from Mailchimp webhooks.
It parses the JSON data sent by Mailchimp.
It checks if the event type is “unsubscribe”.
If it’s an unsubscribe event, it extracts the email address and updates the user’s status in your database.
It also logs the unsubscribe event for auditing purposes.
Importantly, it responds with an HTTP 200 status code to acknowledge receipt of the webhook, otherwise Mailchimp will retry the webhook.

You’ll need to configure the webhook URL in your Mailchimp account to point to this PHP script. This allows you to react to unsubscribe events in real-time and keep your subscriber data up-to-date. Similar webhook integrations can be set up for other email marketing platforms and other types of events (e.g., subscribe, profile update). Carefully handle sensitive data and ensure the security of your webhook endpoints.

Creating Effective Behavioral Segments: Segmentation Strategies

Once you have a system in place for tracking user behaviors, the next step is to create effective behavioral segments. This involves analyzing your data, identifying patterns, and defining criteria for grouping your subscribers. A well-defined segmentation strategy is the backbone of successful personalized email marketing.

Segmentation Based on Purchase Behavior

Segmenting based on purchase behavior is a powerful way to target subscribers with relevant product recommendations and offers.

Example: Segmenting based on Purchase Frequency

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Example: Using Webhooks for Real-time Data Transfer

For more advanced tracking and segmentation, you can use webhooks to receive real-time notifications about user actions. For example, when a user unsubscribes from your email list, Mailchimp can send a webhook notification to your server. You can then use this data to automatically update your subscriber segments and trigger other actions.

// Example PHP code to handle Mailchimp unsubscribe webhook
<?php
  $data = json_decode(file_get_contents('php://input'), true);

  if ($data['type'] == 'unsubscribe') {
    $email = $data['data']['email'];

    // Update user status in your database
    updateUserStatus($email, 'unsubscribed');

    // Log the unsubscribe event
    logEvent('unsubscribe', $email);

    // Optionally, trigger other actions, like removing the user from specific segments
    removeFromSegment($email, 'active_users');
  }

  function updateUserStatus($email, $status) {
    // Database connection details
    $servername = "localhost";
    $username = "your_username";
    $password = "your_password";
    $dbname = "your_database";

    // Create connection
    $conn = new mysqli($servername, $username, $password, $dbname);

    // Check connection
    if ($conn->connect_error) {
        die("Connection failed: " . $conn->connect_error);
    }

    $email = $conn->real_escape_string($email);
    $status = $conn->real_escape_string($status);

    $sql = "UPDATE users SET status = '$status' WHERE email = '$email'";

    if ($conn->query($sql) === TRUE) {
        echo "Record updated successfully";
    } else {
        echo "Error updating record: " . $conn->error;
    }

    $conn->close();

  }

  function logEvent($event_type, $email) {
      //Implementation for logging the event to a file or database
      //This could be writing to a log file or inserting a record in a table.
      file_put_contents('unsubscribe_log.txt', date('Y-m-d H:i:s') . " - Unsubscribe Event: Email: " . $email . "\n", FILE_APPEND);
  }

  function removeFromSegment($email, $segment_id){
     //Implementation to remove user from a segment in your email platform or database.
     //This may involve using the Mailchimp API or directly updating a database.
     error_log("Removing " . $email . " from segment " . $segment_id);
  }

  http_response_code(200); // Acknowledge receipt of the webhook
?>

Explanation:

This PHP script listens for POST requests from Mailchimp webhooks.
It parses the JSON data sent by Mailchimp.
It checks if the event type is “unsubscribe”.
If it’s an unsubscribe event, it extracts the email address and updates the user’s status in your database.
It also logs the unsubscribe event for auditing purposes.
Importantly, it responds with an HTTP 200 status code to acknowledge receipt of the webhook, otherwise Mailchimp will retry the webhook.

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmenting based on purchase behavior is a powerful way to target subscribers with relevant product recommendations and offers.

Example: Segmenting based on Purchase Frequency

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Mailchimp offers a built-in integration with Google Analytics. To enable it:

Log in to your Mailchimp account.
Navigate to Integrations.
Select Google Analytics.
Follow the prompts to connect your Google Analytics account to your Mailchimp account.

Once the integration is enabled, Mailchimp will automatically add Google Analytics tracking parameters to the links in your email campaigns. This allows you to track website visits originating from your emails in Google Analytics. You can then analyze which email campaigns are driving the most traffic and conversions.

Example: Using Webhooks for Real-time Data Transfer

// Example PHP code to handle Mailchimp unsubscribe webhook
<?php
  $data = json_decode(file_get_contents('php://input'), true);

  if ($data['type'] == 'unsubscribe') {
    $email = $data['data']['email'];

    // Update user status in your database
    updateUserStatus($email, 'unsubscribed');

    // Log the unsubscribe event
    logEvent('unsubscribe', $email);

    // Optionally, trigger other actions, like removing the user from specific segments
    removeFromSegment($email, 'active_users');
  }

  function updateUserStatus($email, $status) {
    // Database connection details
    $servername = "localhost";
    $username = "your_username";
    $password = "your_password";
    $dbname = "your_database";

    // Create connection
    $conn = new mysqli($servername, $username, $password, $dbname);

    // Check connection
    if ($conn->connect_error) {
        die("Connection failed: " . $conn->connect_error);
    }

    $email = $conn->real_escape_string($email);
    $status = $conn->real_escape_string($status);

    $sql = "UPDATE users SET status = '$status' WHERE email = '$email'";

    if ($conn->query($sql) === TRUE) {
        echo "Record updated successfully";
    } else {
        echo "Error updating record: " . $conn->error;
    }

    $conn->close();

  }

  function logEvent($event_type, $email) {
      //Implementation for logging the event to a file or database
      //This could be writing to a log file or inserting a record in a table.
      file_put_contents('unsubscribe_log.txt', date('Y-m-d H:i:s') . " - Unsubscribe Event: Email: " . $email . "\n", FILE_APPEND);
  }

  function removeFromSegment($email, $segment_id){
     //Implementation to remove user from a segment in your email platform or database.
     //This may involve using the Mailchimp API or directly updating a database.
     error_log("Removing " . $email . " from segment " . $segment_id);
  }

  http_response_code(200); // Acknowledge receipt of the webhook
?>

Explanation:

This PHP script listens for POST requests from Mailchimp webhooks.
It parses the JSON data sent by Mailchimp.
It checks if the event type is “unsubscribe”.
If it’s an unsubscribe event, it extracts the email address and updates the user’s status in your database.
It also logs the unsubscribe event for auditing purposes.
Importantly, it responds with an HTTP 200 status code to acknowledge receipt of the webhook, otherwise Mailchimp will retry the webhook.

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmenting based on purchase behavior is a powerful way to target subscribers with relevant product recommendations and offers.

Example: Segmenting based on Purchase Frequency

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Explanation:

`gtag(‘event’, ‘view_product’, …)`: This line sends an event to Google Analytics. `view_product` is the event name, which you’ll use to identify this specific event in your reports.
`’product_name’: productName`: This sets the `product_name` parameter for the event. Replace `productName` with the actual name of the product.
`’product_id’: productId`: This sets the `product_id` parameter. Replace `productId` with the unique identifier for the product. This is important for accurate tracking and segmentation.

You can similarly track other website behaviors like button clicks, form submissions, and video views using Google Analytics event tracking. Remember to define consistent event categories, actions, and labels for clear and organized reporting.

Integrating Email Marketing Platform with Tracking Tools

Your email marketing platform (e.g., Mailchimp, Klaviyo, Sendinblue) plays a crucial role in behavioral segmentation. You need to ensure that your platform can track email engagement metrics like opens, clicks, and unsubscribes. Furthermore, it’s essential to integrate your email marketing platform with your website tracking tools (like Google Analytics) to get a holistic view of your subscribers’ behavior.

Example: Integrating Mailchimp with Google Analytics

Mailchimp offers a built-in integration with Google Analytics. To enable it:

Log in to your Mailchimp account.
Navigate to Integrations.
Select Google Analytics.
Follow the prompts to connect your Google Analytics account to your Mailchimp account.

Example: Using Webhooks for Real-time Data Transfer

// Example PHP code to handle Mailchimp unsubscribe webhook
<?php
  $data = json_decode(file_get_contents('php://input'), true);

  if ($data['type'] == 'unsubscribe') {
    $email = $data['data']['email'];

    // Update user status in your database
    updateUserStatus($email, 'unsubscribed');

    // Log the unsubscribe event
    logEvent('unsubscribe', $email);

    // Optionally, trigger other actions, like removing the user from specific segments
    removeFromSegment($email, 'active_users');
  }

  function updateUserStatus($email, $status) {
    // Database connection details
    $servername = "localhost";
    $username = "your_username";
    $password = "your_password";
    $dbname = "your_database";

    // Create connection
    $conn = new mysqli($servername, $username, $password, $dbname);

    // Check connection
    if ($conn->connect_error) {
        die("Connection failed: " . $conn->connect_error);
    }

    $email = $conn->real_escape_string($email);
    $status = $conn->real_escape_string($status);

    $sql = "UPDATE users SET status = '$status' WHERE email = '$email'";

    if ($conn->query($sql) === TRUE) {
        echo "Record updated successfully";
    } else {
        echo "Error updating record: " . $conn->error;
    }

    $conn->close();

  }

  function logEvent($event_type, $email) {
      //Implementation for logging the event to a file or database
      //This could be writing to a log file or inserting a record in a table.
      file_put_contents('unsubscribe_log.txt', date('Y-m-d H:i:s') . " - Unsubscribe Event: Email: " . $email . "\n", FILE_APPEND);
  }

  function removeFromSegment($email, $segment_id){
     //Implementation to remove user from a segment in your email platform or database.
     //This may involve using the Mailchimp API or directly updating a database.
     error_log("Removing " . $email . " from segment " . $segment_id);
  }

  http_response_code(200); // Acknowledge receipt of the webhook
?>

Explanation:

This PHP script listens for POST requests from Mailchimp webhooks.
It parses the JSON data sent by Mailchimp.
It checks if the event type is “unsubscribe”.
If it’s an unsubscribe event, it extracts the email address and updates the user’s status in your database.
It also logs the unsubscribe event for auditing purposes.
Importantly, it responds with an HTTP 200 status code to acknowledge receipt of the webhook, otherwise Mailchimp will retry the webhook.

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmenting based on purchase behavior is a powerful way to target subscribers with relevant product recommendations and offers.

Example: Segmenting based on Purchase Frequency

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Unlocking Email Marketing Success: Behavioral Segmentation

Email marketing, when done right, is a powerful tool for connecting with your audience and driving conversions. But sending the same message to everyone on your list is a recipe for low engagement and high unsubscribe rates. This article dives deep into behavioral segmentation, a powerful technique that allows you to tailor your email campaigns based on your subscribers’ actions and interactions with your brand. We’ll explore how to track these behaviors, create effective segments, and craft personalized content that resonates with each group, ultimately boosting your email marketing ROI.

Understanding Behavioral Segmentation: Beyond Demographics

Traditional email segmentation often relies on demographic data such as age, gender, location, and job title. While this information can be useful, it paints only a partial picture of your subscribers. Behavioral segmentation, on the other hand, focuses on what your subscribers *do* – their actions, interactions, and engagement with your brand. It’s about understanding how they interact with your website, app, emails, and products. By tracking these behaviors, you can create highly targeted email campaigns that resonate with each subscriber’s unique interests and needs. This leads to increased engagement, higher click-through rates, and improved conversion rates compared to generic, one-size-fits-all email blasts. Behavioral segmentation acknowledges that not all subscribers are created equal; understanding their individual journeys is key to delivering relevant and valuable content.

Key Behavioral Metrics to Track

Identifying the right behavioral metrics is crucial for effective segmentation. Here are a few key metrics you should consider tracking:

Website Activity: Pages visited, products viewed, time spent on site, searches performed.
Purchase History: Products purchased, order frequency, average order value, recency of purchase.
Email Engagement: Opens, clicks, forwards, replies, unsubscribes.
App Usage: Features used, frequency of use, time spent in app, in-app purchases.
Content Consumption: Blog posts read, videos watched, downloads completed.
Lead Magnet Interactions: Downloaded specific ebooks, attended webinars, requested consultations.

By tracking these metrics, you can gain valuable insights into your subscribers’ interests, preferences, and buying habits.

Examples of Behavioral Segmentation in Action

Let’s look at some practical examples of how you can use behavioral segmentation to create more effective email campaigns:

Example 1: Abandoned Cart Recovery. Imagine a customer adds items to their shopping cart but leaves your website without completing the purchase. By tracking this “abandoned cart” behavior, you can automatically send them a follow-up email reminding them of their items and offering a discount or free shipping to encourage them to complete the purchase.

Subject: Did you forget something? Your cart is waiting!

Hi [Customer Name],

We noticed you left some items in your cart at [Website Name]. 

[Image of items in cart]

Click here to complete your purchase and get [Discount/Free Shipping].

[Link to cart]

Thanks,
The [Website Name] Team

Example 2: Targeted Product Recommendations. Based on a customer’s past purchases, you can send them personalized product recommendations that align with their interests. For example, if a customer recently purchased a camera, you could send them an email featuring related accessories like lenses, tripods, or camera bags.

Subject: We think you'll love these camera accessories!

Hi [Customer Name],

Since you recently purchased the [Camera Model], we thought you might be interested in these accessories to enhance your photography experience:

[Image of lens]
[Link to lens]

[Image of tripod]
[Link to tripod]

[Image of camera bag]
[Link to camera bag]

Happy shooting!
The [Website Name] Team

Example 3: Re-engagement Campaign. If a subscriber hasn’t opened or clicked on your emails in a while, they might be losing interest. By identifying these inactive subscribers, you can create a re-engagement campaign to win them back. This could involve offering a special discount, highlighting your latest products or services, or simply asking them if they still want to receive your emails.

Subject: We miss you! Come back and see what's new.

Hi [Subscriber Name],

It's been a while since we've heard from you. We wanted to reach out and see if you're still interested in receiving our emails.

Here's what you've been missing:

[Highlight of latest product/service]
[Link to product/service]

As a special thank you for being a loyal subscriber, we'd like to offer you a [Discount] on your next purchase.

[Link to website]

If you no longer wish to receive our emails, you can unsubscribe here: [Unsubscribe Link]

Thanks,
The [Website Name] Team

Example 4: Segmenting based on Content Download. If a user downloads a specific whitepaper from your site about “Email Marketing Automation,” add them to a segment interested in “Email Automation.” Then send them targeted emails about your Email Automation software or services.

Subject: Supercharge Your Email Marketing with Automation

Hi [Subscriber Name],

We noticed you recently downloaded our whitepaper on Email Marketing Automation. We hope you found it valuable!

Are you looking to implement automation in your email strategy?  Our platform helps you:

Automate email sequences
Segment your audience based on behavior
Track key metrics and optimize your campaigns


[Link to Email Automation Software]

Want to learn more? Schedule a demo today!

[Link to Demo Scheduling]

Best regards,

The [Company Name] Team

These are just a few examples of how you can use behavioral segmentation to create more targeted and effective email campaigns. By tracking your subscribers’ actions and interactions, you can gain a deeper understanding of their needs and preferences and deliver personalized content that resonates with them.

Implementing Behavioral Tracking: The Technical Setup

Implementing behavioral segmentation requires a robust tracking system to capture and analyze user actions. This involves integrating various tools and technologies to monitor website activity, email engagement, app usage, and other relevant interactions. Without proper tracking, segmentation becomes guesswork, negating its benefits. The technical setup is critical to ensure accurate data collection and reliable segmentation.

Setting Up Website Tracking with Google Analytics

Google Analytics is a powerful and widely used web analytics platform that allows you to track a wide range of user behaviors on your website. To effectively track behaviors for segmentation, you need to go beyond basic pageview tracking and implement event tracking.

Example: Tracking Product Views

To track when a user views a specific product page, you can use the following JavaScript code snippet:

<script>
  function trackProductView(productName, productId) {
    gtag('event', 'view_product', {
      'product_name': productName,
      'product_id': productId
    });
  }

  // Example usage: Call this function when a product page loads
  // For example, if using PHP:
  <?php
    $productName = "Awesome T-Shirt";
    $productId = "12345";
    echo "<script>trackProductView('" . $productName . "', '" . $productId . "');</script>";
  ?>
</script>

Explanation:

`gtag(‘event’, ‘view_product’, …)`: This line sends an event to Google Analytics. `view_product` is the event name, which you’ll use to identify this specific event in your reports.
`’product_name’: productName`: This sets the `product_name` parameter for the event. Replace `productName` with the actual name of the product.
`’product_id’: productId`: This sets the `product_id` parameter. Replace `productId` with the unique identifier for the product. This is important for accurate tracking and segmentation.

Integrating Email Marketing Platform with Tracking Tools

Example: Integrating Mailchimp with Google Analytics

Mailchimp offers a built-in integration with Google Analytics. To enable it:

Log in to your Mailchimp account.
Navigate to Integrations.
Select Google Analytics.
Follow the prompts to connect your Google Analytics account to your Mailchimp account.

Example: Using Webhooks for Real-time Data Transfer

// Example PHP code to handle Mailchimp unsubscribe webhook
<?php
  $data = json_decode(file_get_contents('php://input'), true);

  if ($data['type'] == 'unsubscribe') {
    $email = $data['data']['email'];

    // Update user status in your database
    updateUserStatus($email, 'unsubscribed');

    // Log the unsubscribe event
    logEvent('unsubscribe', $email);

    // Optionally, trigger other actions, like removing the user from specific segments
    removeFromSegment($email, 'active_users');
  }

  function updateUserStatus($email, $status) {
    // Database connection details
    $servername = "localhost";
    $username = "your_username";
    $password = "your_password";
    $dbname = "your_database";

    // Create connection
    $conn = new mysqli($servername, $username, $password, $dbname);

    // Check connection
    if ($conn->connect_error) {
        die("Connection failed: " . $conn->connect_error);
    }

    $email = $conn->real_escape_string($email);
    $status = $conn->real_escape_string($status);

    $sql = "UPDATE users SET status = '$status' WHERE email = '$email'";

    if ($conn->query($sql) === TRUE) {
        echo "Record updated successfully";
    } else {
        echo "Error updating record: " . $conn->error;
    }

    $conn->close();

  }

  function logEvent($event_type, $email) {
      //Implementation for logging the event to a file or database
      //This could be writing to a log file or inserting a record in a table.
      file_put_contents('unsubscribe_log.txt', date('Y-m-d H:i:s') . " - Unsubscribe Event: Email: " . $email . "\n", FILE_APPEND);
  }

  function removeFromSegment($email, $segment_id){
     //Implementation to remove user from a segment in your email platform or database.
     //This may involve using the Mailchimp API or directly updating a database.
     error_log("Removing " . $email . " from segment " . $segment_id);
  }

  http_response_code(200); // Acknowledge receipt of the webhook
?>

Explanation:

This PHP script listens for POST requests from Mailchimp webhooks.
It parses the JSON data sent by Mailchimp.
It checks if the event type is “unsubscribe”.
If it’s an unsubscribe event, it extracts the email address and updates the user’s status in your database.
It also logs the unsubscribe event for auditing purposes.
Importantly, it responds with an HTTP 200 status code to acknowledge receipt of the webhook, otherwise Mailchimp will retry the webhook.

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmenting based on purchase behavior is a powerful way to target subscribers with relevant product recommendations and offers.

Example: Segmenting based on Purchase Frequency

You can segment your subscribers based on how frequently they make purchases. This allows you to identify your most loyal customers and reward them accordingly.

VIP Customers: Subscribers who make purchases very frequently (e.g., at least once a month).
Regular Customers: Subscribers who make purchases occasionally (e.g., every few months).
One-Time Buyers: Subscribers who have only made one purchase in the past.

// Hypothetical SQL query to segment based on purchase frequency
SELECT
  customer_id,
  email,
  COUNT(order_id) AS order_count
FROM
  orders
WHERE
  order_date >= DATE('now', '-1 year') -- Consider only orders from the past year
GROUP BY
  customer_id, email
ORDER BY
  order_count DESC;

// After executing this query, you'd categorize customers:
// IF order_count >= 12: VIP Customer (at least one purchase a month)
// IF order_count >= 2 AND order_count < 12: Regular Customer
// IF order_count = 1: One-Time Buyer

Example: Segmenting based on Product Category

You can also segment your subscribers based on the types of products they have purchased in the past. This allows you to send them targeted recommendations for similar products.

//Hypothetical SQL query to segment based on product category

SELECT
  c.customer_id,
  c.email,
  p.category_id,
  cat.category_name
FROM
  customers c
JOIN
  orders o ON c.customer_id = o.customer_id
JOIN
  order_items oi ON o.order_id = oi.order_id
JOIN
  products p ON oi.product_id = p.product_id
JOIN
  categories cat ON p.category_id = cat.category_id
WHERE
  o.order_date >= DATE('now', '-6 months') -- Consider only orders from the past 6 months
GROUP BY
  c.customer_id, c.email, p.category_id, cat.category_name
ORDER BY
  c.customer_id, COUNT(o.order_id) DESC; -- Order by number of purchases in each category

//After executing, for each customer, the top category will give you their preferred product category.

Segmentation Based on Email Engagement

Segmenting based on email engagement is crucial for maintaining a healthy email list and improving deliverability.

Example: Segmenting based on Open Rate and Click-Through Rate

You can segment your subscribers based on their open rate and click-through rate to identify your most engaged subscribers and those who are losing interest.

Highly Engaged Subscribers: Subscribers who consistently open and click on your emails.
Moderately Engaged Subscribers: Subscribers who occasionally open and click on your emails.
Inactive Subscribers: Subscribers who rarely or never open or click on your emails.

// Hypothetical query to retrieve email engagement data (example using simplified data)
SELECT
  subscriber_id,
  email,
  SUM(CASE WHEN action = 'open' THEN 1 ELSE 0 END) AS opens,
  SUM(CASE WHEN action = 'click' THEN 1 ELSE 0 END) AS clicks,
  COUNT(*) AS total_emails_received
FROM
  email_events
WHERE
  date >= DATE('now', '-6 months') -- Data from the last 6 months
GROUP BY
  subscriber_id, email;

// After running this query, you calculate Open Rate and Click-Through Rate:

// Open Rate = (opens / total_emails_received)
// Click-Through Rate = (clicks / total_emails_received)

// Then, segment based on thresholds:

// Highly Engaged: Open Rate > 20% AND Click-Through Rate > 5%
// Moderately Engaged: Open Rate > 5% AND Click-Through Rate > 1%
// Inactive: Open Rate <= 5% OR Click-Through Rate <= 1%

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Example: Product Recommendations based on Browsing History

If a subscriber has been browsing a specific category of products on your website, you can send them an email featuring those products.

Subject: We think you'll love these [Category Name]!

Hi [Customer Name],

We noticed you've been browsing our collection of [Category Name] recently. We thought you might be interested in these items:

[Image of Product 1]
[Link to Product 1]

[Image of Product 2]
[Link to Product 2]

[Image of Product 3]
[Link to Product 3]

Shop the full collection here: [Link to Category Page]

Thanks,
The [Website Name] Team

Example: Personalized Offers based on Purchase History

If a subscriber has purchased a specific product in the past, you can send them a personalized offer for a related product or service.

Subject: Complete your setup with this special offer!

Hi [Customer Name],

Since you recently purchased the [Product Name], we thought you might be interested in [Related Product].

As a special offer for our valued customers, we're offering a [Discount] on [Related Product].

[Image of Related Product]
[Link to Related Product]

This offer is valid for a limited time only, so don't miss out!

Thanks,
The [Website Name] Team

This email is personalized based on the subscriber’s purchase history, making the offer much more relevant and appealing.

Dynamic Content: Displaying Different Content to Different Segments

Example: Showing different Hero Images based on Location

Example (Conceptual):

<!-- Hypothetical dynamic content code -->

<div>
  <!-- IF subscriber is in "Cold Climate" segment -->
  <?php if ($subscriber['segment'] == 'Cold Climate'): ?>
    <img src="winter_clothing.jpg" alt="Winter Clothing">
    <p>Stay warm with our new collection of winter clothing!</p>
  <?php else: ?>
    <!-- ELSE (subscriber is NOT in "Cold Climate" segment) -->
    <img src="summer_clothing.jpg" alt="Summer Clothing">
    <p>Get ready for summer with our new collection of swimwear!</p>
  <?php endif; ?>
</div>

Mastering Segmentation in email marketing

Dynamic Content: Displaying Different Content to Different Segments

Dynamic Content: Displaying Different Content to Different Segments

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Integrating Email Marketing Platform with Tracking Tools

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

Unlocking Email Marketing Success: Behavioral Segmentation

Table of Contents

Understanding Behavioral Segmentation: Beyond Demographics

Key Behavioral Metrics to Track

Examples of Behavioral Segmentation in Action

Implementing Behavioral Tracking: The Technical Setup

Setting Up Website Tracking with Google Analytics

Integrating Email Marketing Platform with Tracking Tools

Creating Effective Behavioral Segments: Segmentation Strategies

Segmentation Based on Purchase Behavior

Segmentation Based on Email Engagement

Crafting Personalized Email Content: Tailoring Messages for Each Segment

Personalization Techniques: Beyond First Name

Dynamic Content: Displaying Different Content to Different Segments

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