AI-Powered Campaign Targeting for Cross-Sell and Retention

Quick Summary

Challenge

A financial services firm wanted to build a customer targeting system to power attrition prevention, upselling, and cross-selling campaigns.

Solution

Tatras Data developed an intelligent targeting platform combining AutoML for model training and GenAI for feature engineering and campaign content generation.

Result

Improved accuracy, engagement, and team efficiency across multiple campaign types.

Tech Stack

AI: OpenAI + open-source LLMs | Prompt-based content generation | ML: AutoML model training Customer classification | Data & Retrieval: Transaction history Investment data CRM attributes | Dev: PyTorch LangChain Scikit-learn LlamaIndex | Viz: Segment-level reporting and campaign dashboards | Security: Role-based access Internal-only training infrastructure

The Challenge

Targeted marketing in financial services is both an art and a science. This company needed to run campaigns for customer retention, upselling, and cross-selling, but lacked the infrastructure to automatically process customer data or personalize messaging at scale. Their marketing teams spent excessive time wrangling datasets, manually crafting segments, and generating content that didn’t always resonate with recipients. They needed a single system to:

Process and enrich customer data
Train and apply predictive models
Generate tailored messaging
Launch intelligent campaigns with minimal lift

A Day in the Life: Before Our Solution

A marketer prepares a cross-sell campaign for premium credit cards. They manually segment customers using spreadsheet filters, then create one-size-fits-all messaging for an email blast. The results: Low engagement. Missed upsell opportunities. And no way to quickly iterate or personalize based on customer behavior or history.

Pain Points:

Manual segmentation slowed campaign setup
Data cleaning and feature engineering were inconsistent
One-size-fits-all content lacked engagement
Marketing teams couldn’t scale testing or personalization
Existing tooling lacked intelligence and automation

Solution

1. Core Innovation

Tatras delivered a full-stack customer targeting engine that connects raw data to precise messaging, all via GenAI and AutoML.

GenAI-Powered Feature Engineering: The system enhances uploaded customer data by identifying hidden patterns and new variables that improve prediction accuracy.
AutoML Model Training: Using this enriched dataset, AutoML builds tailored models for each campaign type — attrition, upsell, cross-sell, etc.
Customer Classification + Targeting: Each customer is scored and segmented by likelihood to convert, attrite, or engage.
Campaign Content Generation via LLMsOnce segments are defined, GenAI generates personalized copy for each group.

2. Key Features

AutoML Customer Scoring: Models predict likelihood of engagement for each campaign type
GenAI Feature Engineering: Finds additional insights from existing data
LLM-Powered Content Creation: Generates campaign messages tailored to each customer segment
Quick Launch Interface: Upload data, choose campaign type, and deploy; all in one platform
Segment Reporting: Insight into campaign performance by segment and prediction confidence

3. Workflow Integration

Marketers now upload customer data directly into the platform, select a campaign objective, and receive segmented targets along with AI-generated messaging. Campaigns are launched faster, targeted better, and produce measurable lift in engagement and ROI, without needing data science or creative teams at every step.

Outcomes

✅ Significant increase in campaign speed

🎯 Personalized messages improve engagement across segments

🔍 AutoML models improve prediction accuracy using GenAI-enhanced features

💡 A single platform handles multiple use cases: upsell, cross-sell, attrition

🚀 Marketers now focus on strategy