1. Introduction

A leading European market research firm, specializing in consumer surveys for targeted marketing, faced a challenge: their valuable data was not easily accessible or quickly analyzable for clients. They needed a solution to improve how clients interacted with this data.

2. The Problem

The client's comprehensive data was not stored in an easily queryable format. Brand managers and marketers struggled with a cumbersome process to extract insights. The goal was to create a system where users could ask marketing related questions and receive instant, data-driven answers through natural language queries.

3. The Solution

I developed an AI-powered assistant as an intelligent interface to the client's survey data, capable of understanding natural language queries about marketing strategies and providing informed responses.

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Key features:

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Natural language processing for query interpretation
Intelligent data search and analysis
AI-generated responses tailored to marketing contexts

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Tech Stack:

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Python backend, Next.js frontend
Anthropic Claude Sonnet 3.5 LLM
Neo4j database for complex, interconnected data

4. Development Process

The project was completed in an intensive 2-week sprint. Key challenges included:

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Data preparation: Transforming existing data for AI-driven analysis
Ensuring accuracy and relevance of AI responses to marketing queries

5. Technical Overview

The AI assistant operates through:

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Query Interpretation: NLP processes the user's marketing-related question
Data Search: Queries the Neo4j database using interpreted input
Response Generation: Claude Sonnet 3.5 analyzes retrieved data and generates a human-like response

6. Results and Impact

The new AI assistant improved client data interaction:

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Instant Access: Marketing insights available in seconds, not days
Improved Data Utilization: Natural language interface was accessible to a broader range of users
Enhanced Decision Making: Quick hypothesis testing and strategy exploration through simple questions

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AI-Powered Natural Language Interface for Marketing Insights

1. Introduction

2. The Problem

3. The Solution

4. Development Process

5. Technical Overview

6. Results and Impact

Like what you see? Start implementing agentic processes for greater efficiency today.

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Claim the future; start automating, integrating and accelerating across your entire value chain, while unlocking the full power of LLM-enabled processes.