martech

predictive models

Data-Informed Foresight

If you want to bet on the future while making an informed decision based on data, a predictive model is what you are looking for.

Predictive models run on patterns from past data. Whether it is to anticipate when clients will churn, product demand, or the best time to send a push notification and a message, a predictive model will give an informed look into patterns of behavior. So, you can decide your next move.

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Predicting the next step,
one pattern at a time

Most teams still make one-size-fits-all, after-the-fact decisions, wasting budget and missing revenue. Predictive models turn your data into forward-looking scores so you act before churn, stockouts, or fraud hits—and spend where it actually returns.

Our Solutions

Solutions

Collect the right data

Turn data into features

Train & validate

How predictive models work

Deploy

Measure & improve

Collect the right data

01

Clean, governed data from transactions, behavior, catalog, and campaigns.

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Turn data into features

02

Convert raw stuff into useful clues (recency, frequency, seasonality, ratios).

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Train & validate

03

Fit algorithms on history, test on hold-out data, calibrate the odds.

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Deploy

04

Serve predictions in real time or batch via APIs/pipelines with clear business rules.

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Measure & improve

05

Monitor accuracy and drift, A/B test impact, retrain on new data—repeat.

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Solutions

Some of our predictive models:

Lifetime Value (LTV)

Focus spend on high-value segments to lift ROI and ROAS.

Demand Forecasting

Sync inventory with campaigns to capture every sale.

Owned Media Personalization

Tailor email, web, and app content to boost engagement.

Churn Prediction

Spot at-risk customers early to retain revenue and ease CAC pressure.

Cross-Selling

Serve next-best offers to grow AOV and repeat purchases.

Casually going to drop some impressive case studies here…

Trafilea Case Study | Demand Forecasting for E-Commerce

Science applied on Demand Planning Forecast reduces back orders, time between order and availability costs, optimizing the available supply.

Trafilea Case Study | Demand Forecasting for E-Commerce

Science applied on Demand Planning Forecast reduces back orders, time between order and availability costs, optimizing the available supply.

Increase in Mercado Libre’s ROAS

Decrease in Time Spent on Campaign Management

Mercado Libre Case Study | Enterprise Paid Media Operations

How to measure online marketing effectiveness

Increase in Mercado Libre’s ROAS

Decrease in Time Spent on Campaign Management

Mercado Libre Case Study | Enterprise Paid Media Operations

How to measure online marketing effectiveness

martech

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