Can You Forecast Demand for New Products with Limited Data?

Traditional Demand Forecasting vs. New Product Demand Forecasting

Launching new products in 2025 means navigating a complex environment characterized by hyper-competition, hyper-personalization, and rapidly evolving technology. Traditional demand forecasting relies on at least 24 months of historical sales data to predict the future. For existing products, accumulated sales history and market response data enable fairly accurate predictions using statistical and time-series models.

However, new product demand forecasting requires a fundamentally different approach. Without any historical data, conventional forecasting models simply cannot be applied as-is. Even sophisticated software like GMDH Streamline cautions that with less than 24 months of data, only rudimentary trend analysis is feasible.

This data scarcity creates direct financial risks for business operations. Underestimating demand leads to stockouts, resulting in lost sales and customer dissatisfaction. Overestimating demand creates excess inventory, tying up working capital and causing cash flow problems. New product demand forecasting must go beyond generating numbers—it requires a comprehensive approach that systematically manages uncertainty.

‍

Proposed Methods for New Product Demand Forecasting

Analogy-Based Forecasting Using Similar Products

For new products with no sales history, the first approach involves leveraging data from similar existing products through 'analogy forecasting.' Rather than seeking perfect matches, the goal is to identify products that experienced comparable market conditions at launch, establishing a solid reference point.

First, identify internal products—previously launched items that share similar price points, target customer segments, primary use cases, and distribution channels with the new product. For competitor products, analyze those in direct competition or with similar market positioning to gauge market potential.

Based on this analysis, you can examine similar products' initial market response speed and intensity, seasonal factors, and marketing campaign effectiveness to infer expected demand patterns for the new product. However, this method alone cannot fully capture the unique characteristics of the new product or account for market changes.

Expert Knowledge-Based Qualitative Methodologies

To complement quantitative data limitations, qualitative methodologies that systematically harness expert knowledge and experience are essential. The Delphi Method involves conducting iterative surveys with anonymous expert panels to reach consensus-based future predictions, effectively minimizing subjective bias.

Market research through surveys and interviews directly captures potential consumers' preferences, purchase intentions, and expectations for new products. However, traditional market research is time-intensive and can cost tens of millions of won, with the added challenge that survey responses may diverge from actual purchasing behavior.

Advanced Quantitative Models and Technology Integration

Traditional mathematical models like the Bass Diffusion Model explain the market diffusion process through the influence of innovators and imitators, helping estimate adoption rates and market penetration levels. Recent advances include Bayesian extension models that quantify uncertainty and present predictions as probability distributions for more effective risk management.

With advances in AI and machine learning, it's now possible to analyze diverse external signals in real-time—social media data, search trends, competitor activities—and incorporate them into forecasting models. However, these individual methods alone cannot fully address the complexity and uncertainty of new product demand forecasting.

‍

ImpactiveAI's Approach to New Product Demand Forecasting

Intelligent Forecasting System Leveraging Similar Products

ImpactiveAI's Deepflow systematically analyzes new product features and attributes, quantifying relationships with similar products based on the degree of differentiation for each attribute. Rather than judging similarity solely by product category or price range, it conducts multidimensional analysis of core functions, target customers, usage purposes, and technical characteristics.

Deepflow predicts sales volume by comprehensively considering various variables including launch timing, seasonal factors, regional characteristics, and macroeconomic indicators. It automatically collects and analyzes over 600,000 external price data points and more than 5 million external market environment data points, enabling sophisticated forecasts that even account for market environment changes at the time of new product launch.

The AI model learns past sales patterns of similar products to predict initial market response for new products and simulates demand changes over time. Using Time2Vec technology to comprehensively analyze similar product attributes, distribution channels, regional characteristics, and external data fundamentally solves the data scarcity problem for new products.

Deepflow MarketView: LLM-Based Consumer Preference Prediction

ImpactiveAI offers an innovative consumer preference prediction system through Deepflow MarketView that overcomes the limitations of traditional surveys. While conventional market research costs tens of millions of won and takes months, MarketView employs LLM-based agents that automatically conduct and analyze consumer preference surveys for each new product feature.

Generative AI agents simulate diverse consumer personas to predict reactions to new products. By analyzing product preferences, purchase intentions, and price sensitivity across segmented customer groups—by age, gender, income level, and lifestyle—it delivers insights comparable to actual market research.

MarketView comprehensively analyzes importance by product feature, differentiation points versus competitors, optimal price points, and target customers to quantify the new product's market potential. These analytical results feed directly into Deepflow's demand forecasting model, enabling more accurate and reliable predictions.

Core Technologies of the Integrated AI Forecasting Platform

Deepflow pits 224 models against each other—including transformer-based time series forecasting models like I-transformer and TFT, along with GRU, DilatedRNN, TCN, and LSTM—to produce optimal forecasting results. Through Dynamic, Scalable Learning technology, it continuously processes millions of real-time signals such as social media trends and competitor activities, automatically adjusting forecasts.

Hierarchical Reconciliation technology maintains forecast consistency across complex product hierarchies, from individual SKUs to product families, regions, and channels. It even predicts cannibalization effects that new products may have on existing product sales, supporting optimal decision-making from an entire portfolio perspective.

What-If Scenario Planning allows for advance evaluation of potential outcomes when key variables like marketing budget, pricing, and promotions change. With Expert-in-the-Loop and Explainable AI technologies, it transparently explains the rationale behind AI predictions while enabling users to modify and refine forecasts based on market insights.

‍

New Product Demand Forecasting Success Stories

Global Healthcare Company S's Massage Device New Product Forecasting Case

Medical device company S faced difficulties as existing new products repeatedly failed and competitors launched similar products, prompting the new product planning team to move beyond gut-feeling-based planning and adopt a data science approach.

Ahead of launching their next massage device, they applied machine learning predictive models to forecast 12-week sales volumes under various conditions. By simulating sales while combining innovative features like posture analysis, reclining, and health monitoring, they identified the optimal killer feature. They also predicted sales volumes based on launch timing to identify the most advantageous market entry window.

As a result, company S achieved highly accurate sales volume and trend predictions, successfully planning a new product that significantly improved actual sales performance.

Chocolate Specialty Food Company's New Product Development Case

Chocolate manufacturer B needed innovation in developing new chocolate products. While they needed to secure market competitiveness through products differentiated from their existing lineup, accurately identifying new consumer needs proved challenging.

They took an integrated approach from innovative idea generation to market viability validation using ImpactiveAI's generative AI agents. This generated innovative product ideas previously nonexistent in the market, such as squeezable liquid chocolate, functional chocolate for concentration enhancement, and health-oriented premium chocolate.

ImpactiveAI quantitatively analyzed consumer preferences for each product idea through MarketView, detailing response differences by age group and gender. In particular, they confirmed high interest from the 20-30 age group in functionality-focused products, and selected priority development products based on this insight. Upon launch, the product achieved over 85% satisfaction among the expected target demographic, accomplishing successful market entry.

‍

Forecast New Product Demand in 2025 with ImpactiveAI

Intelligent Forecasting Beyond Data Scarcity Limitations

In 2025, new product demand forecasting is no longer an optional task that can be abandoned due to lack of historical data—it's an essential imperative. ImpactiveAI's Deepflow delivers accurate and reliable demand forecasting even in data-scarce environments by integrating similar product analysis, LLM-based consumer preference prediction, and cutting-edge AI technology.

By overcoming the limitations of traditional methodologies and combining AI with human expertise through a hybrid approach, you can systematically manage the uncertainty of new product launches. Beyond simple prediction, it supports strategic decision-making prepared for all possibilities through diverse scenarios and What-If analysis.

Your Partner for Successful New Product Launches

Successful new product launches begin with accurate demand forecasting. You need a forecasting system that prevents both opportunity loss from stockouts and capital waste from excess inventory while responding agilely to market changes.

ImpactiveAI is setting new standards in new product demand forecasting based on patented AI technology and numerous success stories. We're committed to helping your new products succeed in the market. Don't give up just because you lack data. Experience new possibilities in new product demand forecasting with ImpactiveAI's Deepflow.