Deepflow NPD

7 Out of 10 New Products Disappear
Within Their First Year After Launch

Intuition-Driven Planning

Planning Driven by Experience and Intuition

“I think this will work.”
New product planning without supporting data

High Costs

Slow and Expensive Market Research

Surveys that take months to complete, from questionnaire design and panel recruitment to final reporting

Post-Launch Analysis

Identifying Failure Factors Only After Launch

Understanding the reasons behind product failure only after sales results become available

Solution Overview

Discover a New Product Development Process That Reduces Failure Risk

품목별 수요예측 결과 제공

향후 6~12개월 수요를 그래프로 한눈에 확인

LLM Agent-Based Preference Research

Conduct preference research using LLM agents based on target customer personas, and generate analytical reports from the results.

Data-Driven Idea Generation

Discover high-potential new product ideas using data such as trends, target audiences, and product attributes.

First-Quarter Sales Forecasting for New Products

AI predicts first-quarter sales performance in advance based on new product planning scenarios.

Market & Consumer Analysis

Validate Consumer Reactions Before Launch with AI Agents

Consumer Preference Forecasting

LLM-Based Consumer Preference Prediction Powered by Customer Personas

AI agents automate market surveys based on target customer personas.

Analytical Report Generation

Analyze Response Data and
Generate Reports

Generate analytical reports based on AI agent response data that can be immediately applied to new product planning.

FAQ

Q. How do LLM-based virtual consumer surveys actually work?

Using generative AI, virtual consumer personas are created and surveyed through questionnaires containing up to 50 questions. The solution is primarily used in the early planning stage to quickly validate product concepts and strategic direction.

Q. How does NPD forecast sales for new products?

NPD comprehensively analyzes product attributes of new and comparable existing products, historical sales patterns at launch, market growth potential, seasonality, pricing, and channel strategies. By combining these factors with the product’s concept and positioning, NPD forecasts initial sales performance as well as long-term growth potential.

Q. Which categories can benefit from NPD?

NPD is particularly effective in categories with frequent product launches and accumulated consumer response data, including F&B, beauty, household goods, fashion, and healthcare. The solution can also be applied across various industries where relevant data and comparable reference cases are available.

Q. What data is required for forecasting?

Core inputs include market data, product information, and consumer response data. This may include category size, comparable product sales data, pricing, packaging, reviews, and search trends. Companies can begin with the level of data currently available and expand over time.

Q. Why is pre-consulting important?

Because product concepts and key value propositions vary significantly by industry and company, NPD is currently delivered as a customized solution for each client. Through pre-consulting, Deepflow identifies the client’s specific needs and tailors the service accordingly.

Q. Are there any real-world use cases?

NPD is currently operated as a closed beta service with a strong focus on the F&B domain. Deepflow is validating market potential through collaborations with selected clients and plans to expand the service to a broader customer base in the future.