Introduction: Death to "Dear Sir/Madam"

Check your spam folder. How many emails are there starting with "Dear Customer" offering you a loan you don't need or a discount on diapers when you don't even have a baby? The old "Spray and Pray" marketing (spray and pray someone clicks) is dead. In 2026, customers expect you to know them. To know what they like, when they buy, and what bothers them at 2:00 AM.

Until Amazon and Netflix, true personalization was reserved for luxury brands with a personal representative for each client. Today? AI turns every customer into a VIP. Welcome to the era of Hyper-Personalization.

The Shift from Segmentation to Individualization

In the past, marketing worked by segments. "Women aged 25-34 living in Tel Aviv." That's nice, but it's crude. Today, with Generative AI, we are moving to the individual level. The system doesn't write "Email to Group A," it writes "Email to Danny, who bought sneakers a month ago, likes the color blue, and usually opens emails on Tuesday morning."

The Tools Changing the Game

So how do you actually do it? Here are three key applications:

1. Dynamic Real-Time Campaigns

Instead of writing one copy and sending it to everyone, AI generates thousands of variations of the same message.

• For the frugal customer: "Save 20% on your next purchase."
• For the trendy customer: "The collection everyone is talking about."
• For the practical customer: "Shoes that will last for 5 years." The system learns what works for whom, and improves with every send.

2. Adaptive Landing Pages

Why should your homepage look the same to everyone? If I come from Google after searching for "Gaming Computer," the homepage should show me powerful hardware and insane graphics. If I searched for "Student Laptop," it should show me lightweight and affordable laptops. The AI builds the page on-the-fly based on the visitor's context.

3. Personalized Images and Video

This is the next level. Not just the text changes, but the visual too. A fashion company can show the same shirt on different models, in different backgrounds, according to the customer's taste. Like the beach? The shirt will be shown on the shore. Like urban? It will be shown on a Brooklyn street.

Field Example: Dizzying Success

A medium-sized E-commerce company I worked with implemented an LLM-based recommendation system. Instead of "Customers who bought this also bought...", the system wrote to the customer: "I saw you looked at the family tent. Here is a sleeping bag that fits perfectly for the temperatures in the North this season." The result? A 22% jump in Conversion Rate and a 40% drop in Unsubscribe Rate.

The Ethics of Personalization (The Fine Line Between "Cool" and "Creepy")

There is a fine line between excellent service and feeling like you're being stalked.

• Transparency: Don't hide that you are collecting data.
• Value: Give the customer something in return for their data. A good recommendation is value. Just "Happy Birthday" is nice, but a coupon is value.
• Control: Give the customer an easy option to say "Stop collecting data on me."

Conclusion

Personalization is no longer a "nice feature," it is the new standard. Brands that don't know how to speak personally to their customers will simply become background noise that customers learn to filter out.

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