Individual sends, not batch sends
No manually designed segments: every email is built for a single recipient — purchases, habits, timing. On a list of 10,000 contacts, that means 10,000 different emails.
How it works
A personal shopper
for every one of your customers.
We rethought email marketing around AI. A traditional email platform sends the same email to everyone; EmailGenius works like a personal shopper: it knows each customer, follows their interests and lifecycle, and shows up at the right moment with the right product.
64% of customers open
25× purchases per open
13 dedicated algorithms
60 sec to activate
Key strengths
Thirteen reasons, with the numbers beside them.
Not an old email platform with AI glued on top: a system built from scratch for individual communication. Every number is measured on our clients’ campaigns or cited from a public source.
Templates to design
Standard, repeatable structures that AI fills with different content for every customer. You do the design work once — or never.
Algorithms that do the heavy lifting
Behavior, product selection, timing, subject line, frequency, translation — plus 2 transversal engines always active. And around 25 new algorithms on the roadmap.
Follows the customer lifecycle
New, active, cooling down, dormant: the model follows each customer’s interest and lifecycle stage, and adapts content and frequency to keep them alive — before they stop reading.
More customers opening
In the fashion e-commerce case: 61–64% of customers open compared to 7% with the old mass send, on the same lists. In B2B, in the best campaigns, up to 44×.
More product clicks
Clicks per customer rise from 1.7% to 7–11% in B2C. And those who open buy up to 25 times more often: 6.8–10.3% purchases per open versus 0.4%.
The catalog truly explored
Clicks are distributed across 450+ distinct SKUs in B2B and 49 in B2C fashion — including niche items no newsletter would ever showcase. That is the signature of real personalization.
Revenue you can actually see
1,721 orders and €293,000 attributed across two B2B promotional rounds. In B2C: +560 orders and +€74,000 in incremental revenue across the campaign cycle.
The logic of the big marketplaces
For Amazon, personalized recommendations account for about 35% of revenue. EmailGenius brings that logic into your e-commerce business, through email.
Cold contacts that come back to life
The Push-In module works on prospects and dormant contacts: over 4 out of 10 non-customers start opening again. Recovered attention is the first step toward an order.
Unsubscribes cut in half
Never too many emails, never too few: AI calculates the right frequency for every contact. The result: about half the unsubscribes compared to mass sends, and growing loyalty.
Bounce, where others lose 15–19%
It sends through Amazon SES, Amazon’s sending infrastructure. On large lists we keep bounce at 2–4%, where traditional broadcasts were losing 15–19% of sends.
Live immediately, compliant immediately
Connect your store — Shopify, WooCommerce — and the engine starts: no implementation, no technician. It updates itself. GDPR: data in Europe, consent handled automatically.
57% vs 7%opens, same list, no discount
7.7% vs 1.9%clicks per send
3.6% vs 0.3%conversion per send
half the discountand still double the orders (B2B)
Under the hood
For those who want the technical details.
If you know email marketing, these are the mechanisms you will want to see. We will show you the rest in the demo, on your own data.
Two modules, two jobs
Multicluster works on the customer base: history, product affinity, purchase propensity. Push-In works on prospects and cold contacts with dedicated reactivation logic. Every list is broken down and treated for what it is.
Anti-Parrot and Time Optimizer
Anti-Parrot prevents a customer from always seeing the same products and messages. Time Optimizer learns the time each contact actually opens and schedules the send there. They monitor every campaign, always.
Reminders that recover 1 open out of 3
Anyone who does not open receives a second touch 1–3 days later, rebuilt rather than resent: in measured campaigns the reminder recovered 33% additional opens from non-openers.
Variant-level tracking
Not “how many clicks did the campaign get”: which product, which size, which color each customer clicked. That is the data that feeds the recommender every time.
57% where the top 10% gets 54%
The industry top declares 54.2% opens by sending to the top 5% most active part of the list. EmailGenius: 57% with no discount, across the entire customer base.
All of this, with 2 algorithms out of 13
The published case studies use a fraction of the engine, without extended automatic A/B testing. The numbers you see are the starting point, not the ceiling.
Data measured in-platform on client campaigns, May 2026. Full methodology available in the demo.
The real secret
It is not in the algorithms.
It is in the satisfied customer.
You have already paid the cost of acquiring a customer. If you then serve them badly, they do not buy again — and all that value ends there. Every customer is different: if each email brings them something that matters — the product they were looking for, at the moment they were looking for it — they read you more, interact more, trust you more. And they buy again. That is how customer lifetime value and profitability grow over time: not by always finding new customers, but by serving the ones you already have well. That is what the algorithms are for. Everything else is a consequence.