Cart Upsell that feels helpful, not pushy

Increase order value with add-ons and bundles that make sense for each shopper, at the right moment in checkout.

Solutions for every platform

Intent-aware
Use cart contents, history, and context to suggest what actually helps.

Margin-smart
Respect inventory, margin, and promo constraints automatically.

Frictionless
Inline UI patterns for cart and checkout that don’t slow users down.

Scale without limits
Keep recommendations fast, relevant, and cost-efficient as your goals grow, no re-engineering required.

Get started this week

Day 1
1
Define
Bundles
Pick target categories and attach goals.

Days 2-3
2
3
Connect Catalog & Events
Sync products, prices, and cart events.

Days 4-5
4
5
Tune & Preview
Balance margin, UX, and relevance.

Days 6-7
6
7
Go Live
Monitor AOV & attach; iterate weekly.

Plugs into your workflow

Integrate via API or batch. Keep your current analytics and experimentation setup, or use Shaped’s built-in tools for end-to-end measurement.

Engineered for production

Low-latency APIs, SDKs in your language, and enterprise-grade SLAs, documented and ready for engineering teams.

Build in-house with Shaped

Time to first experiment
6–12 months to build infra before testing ideas
~7 days to run your first experiment

Iteration speed
Slow — pipeline changes, retraining, and deployment cycles
Rapid — deploy and measure new experiments instantly

Team required
ML engineers, infra engineers, product, data science
1 engineer to integrate

Upfront cost
$500k–$1M+ in salaries & infra
Subscription pricing

Maintenance
Continuous tuning, scaling, bug fixes
Fully managed by Shaped

Cold start
Weeks or months to gather enough data
Solved from day one

Cross-surface learning
Siloed models per surface
One model that learns from every signal

Faster experimentation, proven KPI lift, and no infra burden, so your team can focus on what matters: shipping product, not pipelines.

Ship Cart Upsell in one sprint

  • Step 1: Connect your data
    All you need are user interactions and (optionally) item metadata. No complex data pipelines or feature engineering required.

  • Step 2: Configure your feed
    Define your feed in minutes with a simple config—no custom ML models or tuning cycles. Shaped handles the hard parts for you.

  • Step 3: Deploy automatically
    Shaped trains, schedules, and scales your feed to production. Your team ships in weeks, not months—without adding infra or ML hires.

More Use Cases:

  • Baselines
    Explore rule-based models like Popular, Trending, and Chronological rankings.

  • Boosting
    Learn how to promote specific items intelligently within personalized rankings.

  • Cart Upsell & Cross-Sell
    Boost AOV with intelligent upsell and cross-sell recommendations in the shopping cart.

  • Conversational Recommenders
    Building personalized conversational AI assistant experiences.

  • "For You" Feeds
    Build dynamic, personalized feeds like TikTok or Instagram Reels.

  • Grid Ranking
    Create personalized grids like Netflix with ranked rows and columns.

  • Item Cold Start
    Handle new items intelligently with attribute-aware ranking models.

  • Who to Follow
    Suggest relevant users to follow on social platforms or marketplaces.

  • Category Pages
    Re-rank items within categories based on user preferences.

  • Email
    Deliver personalized recommendations in email campaigns.

  • Notifications
    Send relevant, personalized notifications to engage users.

  • Product Detail Pages
    Show similar items on PDPs to keep users engaged.

  • Product Recs
    Build personalized product recommendations for e-commerce.

  • Related Content
    Keep users engaged with relevant related content suggestions.

  • Item Reranking
    Re-rank pre-selected items (e.g. from search) based on user preferences.

  • Hybrid Search
    Combine keyword search with personalized ranking for better results.

  • Similar Users & Items
    Find similar items or users for personalized recommendations.

  • User Cold Start
    Provide relevant recommendations for new or anonymous users.

  • User Interest Ranking
    Rank items based on user attributes, stated interests and session context.

  • User & Item Embeddings
    Leverage embeddings for advanced recommendation strategies.

  • Watch Next Carousels
    Suggest the perfect next video to keep users engaged.

Ready to hit your growth goals?

Get a tailored walkthrough with your KPIs.