Personalization beyond {{first_name}} — what actually works

Personalization with {{first_name}} in the subject line increases your open rate by roughly 10-14%. That’s fine. But it’s the most basic form of personalization — and your competitors are already doing it. Real personalization means sending the right content to the right person at the right time. And that requires more than a merge tag.

Companies implementing advanced email personalization see an average increase in revenue per email of 122% according to Experian’s email marketing study. This guide shows you how to get there — from simple techniques you can implement today to advanced ones that require a bit more setup.

Level 1: Basic personalization (today)

You already have the data you need. Here’s what you can do with it.

First name — but done right

Yes, use the first name. But use it properly:

In the subject line: “{{first_name}}, here’s your weekly roundup” — effective because it resembles a personal message.

In the body: “Hi {{first_name}}” is standard. But consider the context. “{{first_name}}, you’ve been using our product for 30 days now” is more relevant than “Hi {{first_name}}, here’s our newsletter.”

Fallback values: Always have a fallback for contacts without a first name. “Hey there” works better than an empty field or a literal “Hi {{first_name}}.”

Signup data

Did you ask anything at signup? Use it.

• Industry: “Here are 3 email strategies that work in e-commerce” (for e-commerce contacts)
• Role: “As a CMO, you probably don’t have time to…” (for CMOs)
• Company size: Different recommendations for solopreneurs vs. enterprise
• Goals: “You told us you want to improve your open rate — here’s how”

The most underrated personalization is using the information people have already given you.

Location and time zones

Simple but effective:

• Send emails in the recipient’s local time zone instead of yours
• Reference local events, weather, or context
• Use local currency in offers
• Adapt language if you have contacts in multiple countries

Level 2: Behavioral personalization (this week)

Behavioral data is the most valuable data you have. It tells you what contacts are actually interested in — not what they say they’re interested in.

Email engagement personalization

Your email platform knows exactly what each contact has opened and clicked on. Use it:

Topic interest: If a contact clicks on all your segmentation articles but ignores your deliverability articles, send them more about segmentation. It sounds obvious, but almost nobody does this.

Engagement frequency: Contacts who open every email can handle higher frequency. Contacts who open every third one should get fewer but more targeted emails.

Click patterns: Do they always click links at the top or bottom of the email? Do they click on guides or case studies? That tells you about their reading habits and preferences.

Website behavior

If you track website visits (with consent), it opens a new dimension:

Product interest: A contact who has viewed your pricing page three times is ready for an offer. Someone who has read five blog posts is in the research phase.

Content interest: What categories do they browse? Use it to send relevant content.

Form interaction: A contact who started a signup but didn’t complete it needs a nudge — not a generic newsletter.

Purchase behavior

For e-commerce and SaaS, purchase data is gold:

Post-purchase recommendations: “Customers who bought X also bought Y” works because it’s based on real behavior. Amazon generates 35% of its revenue from recommendations, as reported by McKinsey’s research on personalization.

Purchase frequency: A customer who buys every 30 days should get a reminder on day 25. One who buys quarterly needs different timing.

Order value: High-value customers get VIP treatment. Low-value customers get upsell offers matching their budget.

Cart abandonment: A contact who added to cart but didn’t buy needs a specific email — not your weekly newsletter. Timing is critical here: send within 1 hour for best results.

Level 3: Dynamic content (this month)

Dynamic content means different recipients see different content in the same email. You send one campaign, but the content adapts to the individual recipient.

Dynamic product blocks

Instead of showing the same 3 products to everyone, show products based on:

• Browsing history (products they’ve viewed)
• Purchase history (complementary products)
• Category preferences (based on clicks)
• Price level (match their typical order value)

A concrete example: A clothing company sends a weekly newsletter. Instead of showing the same collection to everyone, they show:

• Menswear to contacts who primarily browse menswear
• Accessories to contacts who have purchased basics
• Sale items to price-sensitive contacts (based on primarily buying during sales)

Dynamic copy

The text itself can also be adapted:

CTA variations: A lead sees “Book a demo.” An existing customer sees “Check out the new feature.” Same email, different action.

Testimonials: Show testimonials from the same industry as the recipient. A SaaS contact sees a SaaS case study. An e-commerce contact sees an e-commerce case study.

Numbers and benchmarks: “Your industry has an average open rate of 24%. You’re at 31%.” Contextualized numbers are more persuasive than generic ones.

Conditional content blocks

Show or hide entire sections based on recipient data:

If: contact is trial user
  Show: "Upgrade to Pro and get 20% off"
If: contact is paying customer
  Show: "Here are 3 new features in this month's update"
If: contact is lead
  Show: "See how [customer in their industry] achieved 3x ROI"

One email. Three experiences. That’s real personalization.

Level 4: Predictive personalization (next quarter)

Predictive personalization uses data to anticipate what a contact needs — before they know it themselves.

Send time optimization

Not everyone opens emails at the same time. Send time optimization analyzes when each individual recipient typically opens and sends the email at the optimal moment.

The difference is real: 10-25% higher open rates compared to sending to everyone at the same time.

Churn prediction

By analyzing engagement patterns, you can identify contacts who are about to churn — before they do:

• Declining open rate over the last 4 weeks
• Fewer clicks than usual
• Longer time between visits
• No interaction with the last 5 emails

These contacts get a proactive re-engagement email instead of waiting until they’re completely gone.

Content recommendation

AI-based content recommendations analyze all contacts’ behavior to find patterns:

“Contacts who read article A and B typically also read article C.”

It’s the Netflix model applied to email marketing. You send the content most likely to engage the specific recipient.

Engagement scoring

Engagement scoring gives each contact a score based on their activity:

The score determines what the contact receives and when. High score = sales-ready. Low score = nurture content.

Personalization that backfires (avoid this)

Personalization can feel creepy if it’s too aggressive or based on data the recipient doesn’t know you have.

Too personal, too fast

“Hi Jake, we noticed you looked at our pricing page at 10:14 PM last night” — that’s stalking, not personalization. Use behavioral data to deliver relevant content without revealing exactly what you’re tracking.

Better: “Hi Jake, many people compare our Standard and Pro plans. Here’s a side-by-side that makes it easy.”

Wrong data

There’s no faster path to unsubscribe than wrong personalization. “Hi {{first_name}}”, emails to a customer who already purchased saying “Try our product for the first time”, or testimonials from the wrong industry.

Always check:

• That your merge tags have fallback values
• That your dynamic blocks show the right content for each segment
• That you’re not sending offers for things customers already bought

Over-segmentation

You can segment and personalize so much that you end up sending 15 variants of an email to segments of 50 contacts. That’s not scalable, it’s hard to test, and error rates go up.

Keep it simple: 3-5 variants is almost always enough. More than that gives diminishing returns.

Personalization and GDPR

Personalization requires data, and data requires compliance:

• First-party data (given directly by the contact) is generally safe to use
• Behavioral data (email opens, clicks) is typically covered by your consent
• Third-party data requires explicit consent and a clear privacy policy
• Profile-based personalization falls under GDPR’s rules on automated decision-making

Always give recipients control over their preferences. A preference center where they can choose topics and frequency is good practice — and good for your numbers.

Implementation: A four-week plan

Week 1: Audit your current personalization. Are you using first names? Signup data? Engagement data? Identify what you already have but aren’t using.

Week 2: Implement behavior-based segmentation. Split your list based on engagement and send tailored content to each segment.

Week 3: Add dynamic content blocks to your primary email template. Start with one variable block (e.g., CTA or product recommendation).

Week 4: Measure results. Compare open rate, click-through rate, and conversion with your pre-personalization numbers. Document what works.

After that: Gradually add more personalization layers based on what the data shows.

The most important takeaway

Personalization isn’t about technology. It’s about relevance. The best personalization makes recipients think “this was written for me” — not “they know too much about me.”

Start simple. Use the data you have. Send the right content to the right person. That’s the whole secret.