Most small businesses send the same email to everyone. The subject line changes, maybe the first name appears, but the product recommendations inside the email are identical for every recipient. A customer who only buys skincare sees the same new candle collection as someone who has never browsed that category.
AI changes this by generating dynamic content blocks inside a single email template. Each subscriber sees different product recommendations, different hero images, and different offer placements based on their behaviour, without you building a separate email for each segment.
This is not science fiction. It is available right now in most modern email platforms, and it takes less time to set up than a traditional segmented campaign.
What Dynamic Content Blocks Actually Do
Instead of creating 5 different email versions for 5 customer segments, you build one email with AI-powered blocks that change based on who is viewing. The email platform looks at each subscriber’s purchase history, browsing behaviour, and engagement patterns, then selects the right products to show in each block automatically.
For example:
- A customer who bought face serum 3 weeks ago sees a “time to reorder” block with that exact product and a complementary moisturiser
- A customer who browsed candles but never bought sees a “still thinking about these” block with the candles they viewed plus a bestseller from that category
- A customer who only opens emails about sales sees a “this week’s markdowns” block instead of new arrivals
- A customer who has not bought in 60 days sees a win-back offer block with products from their last purchase category
All of this happens inside one email. One template. One send.
How to Set It Up in Under 30 Minutes
Step 1: Enable AI Recommendations in Your Email Platform
If you use Klaviyo, Mailchimp, Omnisend, or Brevo, AI product recommendations are already available. Look for “product recommendations” or “dynamic blocks” in your email builder. The setup is usually a single toggle that connects the feature to your store’s product catalog and customer history.
If your platform does not have this built in, tools like Nosto, LimeSpot, or Wiser connect to your store and feed recommendation data into your email platform via integration.
Step 2: Choose Your Recommendation Logic
Most platforms offer several AI models. Pick the one that matches your goal:
- “Bought together” model: Shows products frequently purchased alongside items the customer already bought. Best for post-purchase emails and reorder reminders.
- “Viewed but not bought” model: Shows products the customer browsed but did not add to cart. Best for browse abandonment and win-back emails.
- “Trending in your category” model: Shows bestsellers from categories the customer has purchased from before. Best for newsletters and new arrival announcements.
- “Similar customers also bought” model: Shows products bought by customers with similar purchase histories. Best for cross-sell and discovery emails.
Start with one model. Do not stack all four at once. The “bought together” model is the easiest to implement and usually delivers the highest click-through rate.
Step 3: Place One Dynamic Block in Your Next Email
Do not redesign your entire email template. Take your next scheduled newsletter and replace one static product section with a dynamic recommendation block. Position it in the middle of the email, after your intro text and before your footer.
The block should show 3 product recommendations with images, titles, prices, and a “shop now” button. The AI fills in the right products for each subscriber. You write the surrounding copy once.
Step 4: Set a Fallback
Some subscribers will not have enough browsing or purchase history for the AI to generate recommendations. Set a fallback that shows your top 3 bestsellers for those recipients. This ensures the email never has an empty block.
Most platforms handle this automatically, but check your settings. A blank space in an email looks broken and kills click rates.
What to Measure
After sending your first email with a dynamic recommendation block, compare these metrics against your previous newsletter:
- Click-through rate on the recommendation block vs. your old static product section. Expect a 15 to 30% lift.
- Revenue per recipient for the email. Dynamic recommendations typically increase this by 20% or more because the products are relevant to each person.
- Unsubscribe rate. If the AI is working well, unsubscribes should stay flat or decrease because the content is more relevant.
If click-through rate does not improve after 2 sends, the issue is almost always the recommendation model. Try switching from “bought together” to “trending in your category” and test again.
Common Mistakes to Avoid
- Using too many dynamic blocks in one email. One or two is effective. Three or more makes the email feel fragmented and the AI has to work harder to fill each block, which can lead to irrelevant recommendations.
- Forgetting the fallback. New subscribers with no purchase history need to see something. Always set a bestseller fallback.
- Not checking the mobile render. Dynamic blocks with 3 product images can look cramped on mobile. Test with 2 products per row on mobile instead of 3.
- Letting the AI recommend out-of-stock products. Most platforms filter these out automatically, but verify. Recommending an out-of-stock product is worse than no recommendation at all.
The Bigger Picture
Dynamic content blocks are the lowest-effort, highest-impact AI feature available to small businesses right now. You do not need a data team. You do not need a developer. You need 30 minutes and one email send to see the difference.
The stores that adopt this will send fewer emails that each perform better. The stores that do not will keep sending the same generic newsletter to everyone and watching their open rates slowly decline.
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