Personalization Algorithms
That Lift Conversion 20-50%.
ML-powered personalization across web, email, mobile. 35% revenue lift. Different homepage per visitor. Emails that feel handwritten. Products they'll actually buy.
Every touchpoint, tailored.
Dynamic Homepage
Different hero, products, banners per visitor segment
Personalized Emails
Subject lines, products, send times per person
Product Recs
"You might also love" driven by behavior ML
Dynamic Pricing
Segment-based pricing, demand-responsive offers
Push Notifications
Right message, right time, right channel
Personalized Search
Search results ranked by user intent + history
“Personalization drove 35% revenue lift in 90 days. Homepage conversion up 22%, email CTR up 67%, AOV up 22%. The same traffic made dramatically more money.”
Real personalization, not rule-based segmentation.
Traditional personalization = 5 customer segments getting 5 variations. Real personalization = every visitor getting a unique experience. We build ML-driven personalization that lifts CVR 20-50%.
Data + model design
Week 1-2Event data audit, user-representation design, model selection (collaborative filtering + content-based + deep learning hybrids), ML platform choice.
Model training + serving
Week 3-6Feature engineering, training pipeline, offline eval, online A/B infrastructure, real-time serving with <100ms latency.
Integration + rollout
Week 7-8Personalized content blocks integrated into site / product, cohort-based rollout, statistical-significance validation, production monitoring.
Retrain + expand
Month 3+Weekly retraining on new data, new use cases added, cold-start improvements, cross-channel personalization (email, push, SMS).
End-to-end personalization ML system.
Data pipelines, model training, serving infrastructure, and A/B measurement — all in one engagement.
Personalization ML system
Hybrid recommender (collaborative + content-based + deep learning), cold-start handling, real-time serving via TorchServe / Modal / custom infra. <100ms latency typical.
Feature engineering pipeline
User embeddings, content embeddings, interaction features, time-decay weighting, negative-feedback handling. All computed on rolling basis.
A/B testing infrastructure
Experiment framework supporting multi-armed-bandit + fixed-allocation tests, stat-significance discipline, holdout groups, attribution cleanliness.
Dashboards + monitoring
Real-time personalization lift dashboards, model-performance monitoring, data-drift alerts, user-feedback capture for active learning.
Built for high-traffic, data-rich sites.
Personalization ML needs interaction data. Under 10K daily users, simpler segmentation-based personalization is more pragmatic. Above 100K daily users, ML-driven personalization drives massive revenue.
Ecommerce at Scale
Product recommendations, personalized collections + homepage, search result personalization, email content. Typical 20-40% revenue lift.
Media + Streaming
Content recommendations, personalized feeds, watch-time optimization. Netflix + Spotify patterns applied to your content library.
Apps + Social Products
Feed personalization, notification targeting, onboarding flow personalization, engagement + retention lifts.
Education + Content Platforms
Course recommendations, learning-path personalization, difficulty-adaptive content. Platforms like Duolingo pattern applied to vertical education.
Model-agnostic, infra-rich, eval-first.
We run production AI on a deliberately diversified stack — so switching models or providers is a config change, not a rewrite.
WE SERVE YOUR INDUSTRY
Select Your Industry — Get a Custom Strategy
Click your industry below to start your free application — we'll tailor everything to your market.
Financial Services & Insurance
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Healthcare & Life Sciences
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Technology, Software & IT
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Retail & Ecommerce
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Real Estate & Construction
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Hospitality & Travel
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Automotive
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Manufacturing & Industrial
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Education & E-Learning
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Entertainment & Media
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Non-Profit & Government
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Logistics & Transportation
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One-size-fits-all is dead.
35% revenue lift from personalization. Every visitor, their own experience.
Personalization pricing.
Starter
1-week setup · Basic ML
Advanced
6-week build · Full stack
Enterprise
Custom ML models
Personalization algorithms, answered honestly.
Off-the-shelf vs. custom personalization?
Off-the-shelf (Klaviyo, Mutiny, Dynamic Yield) for starting out — solid results with minimal effort. Custom personalization pays off when (a) you're above $10M/year, (b) have unique content or product catalog, or (c) need integration off-the-shelf can't deliver.
How much data do I need?
10K+ users + 100K+ interactions for meaningful collaborative filtering. Content-based personalization works from day 1 via embeddings. Hybrid approaches balance both for production quality.
What's the typical lift?
20-50% CVR lift on personalized surfaces. Homepages + landing pages often see highest lifts. Email personalization typically 30-60% open + click rate improvements vs generic segmentation.
Cold-start problem?
New users + new products are handled via content-based similarity + demographic priors. Pure collaborative filtering fails cold-start; good hybrid systems don't.
Privacy + GDPR?
User embeddings computed locally + anonymously. No PII sent to models. GDPR data-subject-erasure honored in training pipeline. CCPA opt-out respected via consent frameworks.
Three ways to get started
Pick the path that fits you best — a quick form, a detailed brief, or a live call. Selected service: AI & Automation.
Prefer phone? Call (480) 650-9911 — Mon–Fri · 9am–6pm MST