Frequently asked questions

Quantellix.AI is an AI purchase-intent prediction and ecommerce conversion optimization platform. Its core product, DXI (Digital Experience Index), scores every website visitor's likelihood to buy on a 0-100 scale, so ecommerce, travel and payments teams can lift conversion 20-80%.

DXI is an explainable, 0-100 AI score built from four sub-scores — Visual, Behavior, Transactional and KPI — that predicts how likely a specific visitor is to buy. See the full DXI definition and breakdown.

LNM-AI (Large Numerical Model) is Quantellix.AI's model that reads every click, scroll, search and session on a website and turns that behavior into structured data for scoring.

SXI++ is the engine inside LNM-AI that compresses every behavioral signal into one explainable engagement index — the number that becomes a visitor's DXI score.

Score visitors individually with a purchase-intent model, identify which stage (visual, behavioral, transactional) is losing the most value, and fix that stage first. See the full ecommerce CRO guide.

AI improves ecommerce sales by predicting which visitors are close to buying in real time and prioritizing personalization or retargeting toward them. See AI conversion optimization.

AI personalization scores a visitor's purchase intent from their behavior, then adapts messaging, offers or retargeting priority for that specific visitor rather than treating all visitors identically.

Separate high-intent visitors who hit friction from low-intent browsers using a visitor-level score, then fix the specific friction (pricing clarity, checkout flow, fees) rather than only adding a discount. See cart abandonment analytics.

Average order value improves when pricing, bundling and promotions are matched to a visitor's purchase-intent segment instead of applying the same offer to everyone.

A purchase-intent prediction system analyzes visitor behavior — clicks, scrolls, searches, transactions — and outputs a single score describing how likely that visitor is to buy. See purchase-intent prediction.

Customer behavior analytics studies how visitors move, scroll and search on a website to understand and predict buying behavior. See customer behavior analytics.

In Quantellix.AI's benchmark testing across real ecommerce case studies, DXI-based scoring reached 98-99.8% accuracy on visitor-conversion and pricing-efficiency metrics, ahead of general-purpose LLM and AutoML baselines tested on the same data.

Quantellix.AI is built for ecommerce, travel and payments companies that want to understand and act on why visitors do or don't buy, rather than only measuring traffic and sales after the fact.