Solarplexus - Hyper Personalized Marketing Collateral Generation

Solarplexus – Hyper Personalized Marketing Collateral Generation

Business Problem

Marketers face challenges in creating personalized and effective marketing collateral for segmented target audiences.
Traditional marketing asset generation methods are often time-consuming, lack personalization, and may not align with specific audience preferences.
Conventional methods lack the sophistication required to meet the dynamic demands of the modern marketing landscape.
SolarPlexus aimed to solve these challenges by introducing hyper-personalization into mass marketing, achieving double-digit conversion rates and 60% higher ROI on marketing campaign

About Solarplexus

SolarPlexus is a Sweden-based SaaS Marketing solutions provider. Their product helps customers 10X their marketing outreach conversion by building real-time, hyper-personalized marketing content, leveraging underlying user persona & intelligence.

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Solution

With the advent of Generative AI and its capabilities to generate real-time, customized content, goML’s Gen AI consulting team collaborated with the client to develop a product vision. This solution enables SolarPlexus clients to create hyper-personalized communications based on real-time user personas, resulting in a 10X increase in conversion rates. The approach followed three key steps:

1.

Automated Branding for Collateral Standardization (Claude-v2)
Leveraged Claude-v2 to extract branding guidelines from complex brand documents, including logos, fonts, and brand colors.
Standardized content and formatting for marketing collateral.

2.

ML-Powered User Classification & Segmentation: Real-Time Personalization
User Classification with ML Models: Implemented machine learning models to classify and segment users in real time based on various parameters such as demographics, purchasing behavior, and marketing engagement.
Clustering Analysis for Precision Targeting: Applied clustering algorithms to segment user data effectively, ensuring tailored marketing efforts for each group.
Dynamic Cluster Naming: Named each cluster based on segmentation criteria to facilitate analysis and easy reference.
Enhanced Accuracy Assurance: Optimized segmentation techniques to improve precision and effectiveness in personalized marketing.
Real-Time Adjustments: The AI model dynamically adapts marketing content based on updated user preferences and engagement patterns.

3.

Hyper-Personalization with Stable Diffusion
Leveraged segmented user data to generate real-time marketing collateral using Stable Diffusion.
Created image and text-based assets tailored to each user’s unique profile.
Enabled personalized recommendations for marketing teams to refine outreach strategies dynamically

Architecture

Data Ingestion & Preprocessing
Extracts customer data from CRM.
Cleanses and transforms data using AWS Glue.
Stores processed data in Amazon S3 for scalable access.
ML-Powered User Segmentation
Amazon SageMaker trains a hierarchical clustering model to classify users based on demographics, behavior, and engagement.
The trained model segments users dynamically, enabling hyper-personalized outreach.
Real-Time Inference & Integration
API Gateway & AWS Lambda process incoming user data and trigger ML inference.
SageMaker Endpoint predicts user segments in real-time.
Results are stored in Amazon RDS for further analytics.
Continuous Model Monitoring & Retraining
SageMaker Monitoring evaluates model accuracy.
AWS Glue automates data extraction for model retraining.
The system continuously adapts, improving segmentation over time.

Solarplexus - Hyper Personalized Marketing Collateral Generation

Outcomes