Marketing Intelligence

AI Tools Built for Performance Marketers

Off-the-shelf marketing analytics tools show you what happened. Our custom AI tools show you what's going to happen — and give you the levers to change it. Vora builds predictive attribution models, creative scoring engines, ROAS forecasting dashboards, and marketing intelligence platforms from the ground up, trained on your data.

AI Tools We Build

Custom Marketing Intelligence, Not Generic Dashboards

Every marketing AI tool we build solves a specific performance problem — improving ROAS prediction accuracy, reducing attribution blind spots, or accelerating creative testing velocity. We don't build generic dashboards.

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Predictive Attribution Models

Custom multi-touch attribution models trained on your conversion paths — accounting for cross-device journeys, view-through windows, and the true contribution of each channel to revenue. More accurate than last-click by 35%+ in most client datasets.

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ROAS Forecasting Engines

ML models that predict ROAS outcomes for budget changes, new audience segments, or channel expansion scenarios — giving you data-backed confidence before you commit spend. Typically accurate within 12% of actual outcomes.

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Creative Performance Scoring

AI models trained on your historical ad creative performance that predict new creative assets' likely CVR before launch. Reduces wasted creative spend and accelerates finding winning ad concepts by 2–3x.

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Audience Intelligence Platform

Proprietary audience analysis tools that identify the behavioral and demographic signals most correlated with high-LTV customers — enabling more precise targeting on all paid channels and reducing CAC by 20–35%.

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LTV Prediction Models

Predict customer lifetime value at acquisition — segmenting new customers by predicted LTV before the first 30-day window closes. Enables margin-aware bidding and smarter cohort analysis for paid media.

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Media Mix Modeling

Statistical models that quantify the revenue contribution of each marketing channel, including offline and non-trackable touchpoints. Essential for brands managing $500K+/month in blended marketing spend.

Development Process

From Data to Deployed AI in 6–12 Weeks

Week 1–2

Data Audit & Scoping

We assess your existing data quality, API availability, and technical infrastructure. We define the model architecture, success metrics, and integration requirements before any code is written.

Week 3–6

Model Development & Testing

We build, train, and validate the core AI model using your historical data. Bi-weekly review sessions with your team ensure the outputs match real-world business logic and edge cases.

Week 7–10

Integration & UI Build

We connect the model to your marketing stack via APIs, build the user interface or dashboard, and set up monitoring alerts for model drift and data quality failures.

Week 11–12+

Deployment & Optimization

Production deployment with a 2-week hypercare period. Model performance is monitored against validation benchmarks, and quarterly retraining keeps accuracy high as your data evolves.

FAQ

AI Development Questions Answered

What kinds of AI marketing tools does Vora build?
We build predictive attribution models, creative performance scoring engines, audience intelligence platforms, ROAS forecasting dashboards, LTV prediction models, media mix modeling tools, and custom reporting layers that synthesize cross-platform marketing data into unified performance intelligence. Each engagement starts with scoping to identify the highest-impact AI investment for your specific situation.
How long does custom AI tool development take?
MVP versions of most marketing AI tools can be delivered in 6–10 weeks. Full production-grade systems with integrations, monitoring infrastructure, and user interfaces typically take 12–20 weeks. We use agile delivery with bi-weekly milestone reviews so you see measurable progress throughout the build, not just at the end.
Do you use off-the-shelf AI or build custom models?
We use a combination. We leverage established LLM APIs (GPT-4, Claude) for language-based tasks like ad copy generation and creative briefing. We build custom machine learning models trained on your proprietary data for prediction tasks like LTV forecasting, lead scoring, and ROAS prediction. Custom models are more accurate for your specific data patterns — off-the-shelf models are faster to deploy for generative tasks.
Who owns the AI tools you build?
You own 100% of the custom tools we build for you — all code, trained models, and intellectual property. We retain no rights to client-specific builds. For tools that leverage our internal infrastructure or proprietary datasets, we offer SaaS licensing arrangements that maintain your full access while sharing infrastructure costs.
Can AI tools integrate with our existing marketing stack?
Yes. We build API integrations with Google Ads, Meta Ads, GA4, HubSpot, Salesforce, Klaviyo, Shopify, and most major marketing platforms. Where native APIs don't exist or have rate limitations, we build custom data connectors or webhook-based integrations. We conduct a full API compatibility assessment during scoping to identify any technical risks before development begins.

Build the Marketing Intelligence Your Competitors Don't Have

Tell us your biggest attribution gap or forecasting challenge. We'll scope a custom AI solution and give you a build estimate within a week.

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