Build Predictive AI Models to Improve Conversion (and Leave No Money on the Table)
In e-commerce, timing is everything. A moment of hesitation can mean a lost sale. Moveo One enables your team to predict with high precision whether a user will convert—before the decision happens—so you can act in real time.
Whether it’s detecting checkout abandonment, cart hesitation, or payment drop-off, Moveo One gives you tools to intervene when it matters most.
Detect When a User Will Abandon — Before They Do
Moveo One models are designed to detect outcomes like:
- Will this user complete checkout?
- Will they drop off at payment?
- Are they ready to buy—or just browsing?
In one deployment, Moveo One was able to detect—with over 80% precision—whether a user with items in their cart would complete the purchase or abandon it, at the moment they landed on the checkout screen.
This enables product teams to:
- Trigger tailored incentives
- Notify customer support
- Adjust UX friction in real time
Zero ML Expertise Required: Just Select the Event and Click Build
Creating a predictive model in Moveo One doesn’t require data science skills. You simply:
- Choose a target event, like checkout_completed
- Add a condition, like cart_contains_items
- Optionally set A/B split to compare uplift
- Add credits (used for model training + monitoring)
- Click “Build”
That’s it. The model trains on your historical user behavior and deploys automatically—returning a real-time probability score for every user session that meets your criteria.
High Precision, Actionable Outputs
Unlike generic ML platforms, Moveo One is designed for precision at the decision point.
- The system returns confidence-ranked predictions you can act on immediately.
- Models are optimized not just for recall, but for precision—so when the model says “this user will convert,” it’s right 8 times out of 10.
- This ensures minimal false positives, making it safe to use predictions to trigger discounts, support, or UI changes.
You define the behavior you care about—Moveo One tells you when it’s about to happen (or not).
Monitor, Adjust, Improve — All in One Place
Each model comes with a live dashboard showing:
- Model accuracy over time
- Conversion lift in A/B groups
- Feature contribution breakdown (what influenced the prediction)
- Confidence intervals and thresholds
You can retrain, tune, or deprecate models with one click—no redeploys, no downtime, no MLOps overhead.
Built for Developers and Realtime Systems
Moveo One integrates via API or SDK into your backend or frontend logic. Predictions can be queried in real time and used to:
- Show or hide discounts
- Send reminders or nudges
- Trigger LLM agents or automated workflows
- Update personalization logic instantly
Everything is built to fit into modern dev stacks—with latency under 100ms.
Works Seamlessly With AI Agents
In today’s LLM-driven world, predictive signals are fuel for automation. Moveo One models can:
- Be queried by agents (“Will user ID 5834 complete checkout?”)
- Trigger workflow branches inside AI copilots
- Feed intent signals into support agents or voice interfaces
We design each model’s output to be semantically clear and structured, so it works well inside agentic systems.
Summary
- 🎯 Predict checkout abandonment before it happens
- ⚡️ Real-time scores you can act on instantly
- 🧠 Precision-focused: over 80% confidence in critical flows
- 🔧 No ML setup: just select event → build
- 📈 Monitor and tune from a single dashboard
- 🤖 Built for developers, fits into agent and automation ecosystems
Ready to Predict Conversion Outcomes in Real Time?
Ask Moveo One:
- “Which users are hesitating at checkout?”
- “Should I trigger an incentive now?”
- “How sure are we this user will pay?”
And get answers. Not later—now.
