Recommend the right product to every customer.

A fully customizable quiz on your store that learns each visitor's goals, health, lifestyle, and diet — then matches them to the right products in your catalog through a deterministic scoring algorithm. Not a decision tree, not persona-based. The algorithm is the differentiator.

Supplements and over-the-counter health is the live vertical — that's where the scoring engine has the deepest content layer (nutrient gaps, RDIs, ingredient interactions, dosing). Beauty and food are on the roadmap. The scoring architecture is portable across categories; the category-specific content layer is what we build out per vertical. If you're not in supplements yet, talk to us about timing.

It scores every product in your catalog against the customer using more than 30 product attributes (ingredients, dosing, interactions, evidence, contraindications, synergies) and more than 20 user signals (goals, sub-goals, conditions, lifestyle, and nutrient gaps inferred from a food-frequency questionnaire). Each pick comes with the specific reasons that produced it — not just an answer-to-tag match. See the methodology →

Those tools match products to multiple-choice answers — tag in, products out. Persona-based quizzes and decision trees don't actually personalize; they segment. Blend computes a numeric, deterministic score per product per customer, factoring in ingredient interactions, upper-limit safety, synergies, and inferred nutrient gaps. Same input always produces the same output — auditable, defensible, and shippable to brands in regulated categories. Every recommendation carries the reasons that produced it.

Upload your catalog through our webapp. Shopify is supported with automatic sync, plus CSV and manual upload for any other source today. WooCommerce, BigCommerce, and other platforms are coming. Our team can help if your catalog has anything unusual.

The engine includes a safety layer that runs on every recommendation: supplement–supplement interaction checks, medication conflict screens, upper-limit gating against tolerable intakes, and synergy pairing. Every flagged interaction or limit is traceable to a source rule — important if you operate in a regulated category.

Completely. Your brand, your colors, your domain. No “Powered by Blend” anywhere — as if you had a team of devs build it for you. See the white-label options →

15-day free trial on every plan. Starter from $49/month, Pro from $299/month, Enterprise from $599/month. Plans scale by quiz responses and catalog size. See pricing →

English today. Multi-language support — French and other major languages — is coming soon. The quiz text (questions, labels, CTAs) is fully customizable per brand, so when new languages land you can run a localized quiz per market.

Blend is fully GDPR-compliant under UK/EU regulations and the major US state privacy laws (CCPA, etc.). Brands can run quizzes globally — the platform serves customers in any country. Data residency requirements (EU, US, UK) are covered; talk to us during onboarding if you have specific compliance needs.

Pro and Enterprise plans include four analytics surfaces:

• User Analytics — who's taking your quiz: demographics, goals, conditions reported, diet, and more.
• Quiz Analytics — completion rates, drop-off points, common answer paths, conversion, and more.
• Product Analytics — which products get recommended most, basket composition, signals on AOV and conversion.
• Market Analytics (coming soon) — category-level trends across your customer base: what your audience cares about, where the gaps are.

Every view is brand-scoped. Cross-brand aggregates are anonymized and never expose individual customer data.

Yes. Most brands switch over in days, not weeks: we map your existing quiz logic into Blend's scoring engine, ingest your catalog, and you keep your existing embed slot. Your old persona/tag rules become inputs to the algorithm.

Yes. You can adjust scoring weights, exclude product attributes, prioritize specific goal-to-product mappings, and configure brand-specific overrides during onboarding. The deterministic core stays — your tuning is layered on top.