Business DNA turns your merchandising logic into rules your store understands — automatically enforced across every product, slot, and placement.
Chosen by fast-scaling startups to established global brands across diverse platforms
The algorithm doesn't
understand your brand.
Most platforms only provide recommendations at a basic level — not built to understand how a specific brand operates.
Out-of-stock products keep showing up
Shoppers click and find nothing to buy — you lose the sale without even knowing it happened.
Your store doesn't understand your brand
Entry-level products beside flagship items. Winter stock promoted during summer. The algorithm optimises for data, not for your brand.
Recommendation slots stuck on repeat
3 of 4 slots show the same collection. New arrivals and high-margin products are completely ignored.
You can't teach the system your logic
You don't need to be a developer to know the answer — you need a way to encode what you already know into the system.
You set the rules. The system runs them.
Business DNA is where you encode your brand logic — three rule types that cover every scenario your store faces.
Prevent the wrong products from appearing — by season, stock, price, or tier. Runs automatically on every impression.
Surface proven bundles, same-tier products, and the collections you want to push — always first.
Cap products from one collection per slot — more variety, more cross-sell surface, less repetition.
See Business DNA in action — in 2 minutes.
From writing your first rule to watching your store run exactly as intended — no code, no waiting.
Eight rules. One brand brain.
Each rule closes the gap between how your store behaves by default and how it should.
Auto-hide and show products by month — no manual updates, never forgotten.
Real-time inventory sync — out-of-stock products removed instantly.
Limit same-collection products for broader catalog coverage.
Set separate price thresholds per placement — PDP, cart, thank-you page.
Classify products by tier to protect brand positioning in recommendations.
Build bundles from real data — proven product pairs are always shown first.
Only show actively converting products — new arrivals get a grace period.
When the anchor is full price, heavily discounted items are excluded.