Profiles, events, search logs, catalog/content, CRM/support—only with consent and least-privilege access.
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Personalization engines connect signals from web/app, search, carts, and support to decide what each user should see next. We unify profile, context, and content into a decision layer that serves the right message, offer, or help at the right time—across site, mobile, email, and service channels.
We blend rules, models, and retrieval: feature pipelines, vector search over governed content (RAG), and ranking tuned to your KPIs. Feature flags, experiments, and guardrails keep outputs safe and on-brand. We integrate with your CDP/ESP and CMS, enabling updates to ship quickly.
A decisioning playbook with policies, segments, and triggers; content models and templates; recommendation feeds; and an experiment backlog with success metrics. Dashboards track lift—conversion, AOV, activation, retention—so wins scale with evidence.
Privacy and brand safety are built in: consented data only, data minimization, access controls, and audit logs. We validate tone, claims, accessibility (WCAG), and bias before content goes live; explainability and holdouts confirm incremental value.
Profiles, events, search logs, catalog/content, CRM/support—only with consent and least-privilege access.
Yes. We start with your current data layer and add adapters; we'll integrate a CDP later if needed.
Templates, tone/claims checks, approval flows, and policy-as-code guardrails are in place before anything goes live.
First insights in two weeks; a thin-slice personalization pilot typically ships within 8–12 weeks.
Both. We choose cloud, edge, or on-device models based on latency, privacy, and cost.
A/Bs and sequential tests tied to KPIs—conversion rate, AOV, activation, retention, and CSAT—with dashboards and alerts.
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