Demand Potential Analysis

Well-founded market decisions require a robust quantification of demand potential, competitive position and assortment performance. Conventional market-research approaches based on samples or extrapolations reach their methodological limits here. FOSTEC & Company’s demand-potential analysis is based on AI-supported real-time data crawling and real transaction data, thereby delivering a depth of detail and validity that sample-based methods cannot achieve. In addition, the approach integrates AI-supported demand-sensing models and real-time market signals for precise market sizing and demand forecasting.

Context and relevance

Managing sales, pricing and assortment requires a fact-based basis for decisions at article and category level. Anyone relying on aggregated industry data or time-lagged market-research studies operates with structural information disadvantages compared with competitors who evaluate channel-specific transaction data in real time. For PE investors and companies in the commerce context, the ability to quantify market potential precisely is moreover a central input for business cases, CDD processes and strategic growth planning.

Our approach

Crawling-based data collection forms the analytical foundation of the analysis. From a central data base, five core areas are analysed systematically (Figure 1: Overview of the five areas of analysis based on AI-supported crawling).

Figure 1: Overview of the five areas of analysis based on AI-supported crawling

1. Total potential of unit sales and revenue:
   Determining the channel-specific total market potential provides the central input for any fact-based business case. Using AI-supported data crawling, the total potential of selected product categories on platforms such as Amazon or eBay can be determined with high validity, based on revenue and units sold. Demand-sensing models complement the crawling data with external signals for precise market sizing.
2. Competitor market shares:
   On the basis of the collected market data, a company’s own market shares can be determined and positioned in a competitive comparison. This enables the derivation and validation of strategic targets as well as the establishment of active performance management. Developments in market share can be measured over time, for example during dedicated marketing campaigns, and used as a basis for calculating marketing efficiency.
3. Competitor prices:
   Data collection through crawling delivers daily prices at article level. Clearly defined observation periods enable a robust quantification of market and competitive dynamics and their pricing strategies – a central basis for developing one’s own pricing approaches, and for identifying price deviations among distribution partners.
4. Competitor top sellers:
   The systematic comparison of top sellers with one’s own assortment identifies assortment gaps. AI-supported evaluations of customer reviews show which product features are preferred by buyers and where there is a need for development – with direct implications for product development and portfolio optimisation.
5. Assortment performance:
   The market figures collected allow clear statements on current assortment performance in a competitive comparison. In addition, the quality of listings is analysed with regard to media content, A+ content and product descriptions as a lever for conversion optimisation. From this, targeted optimisation measures for the product portfolio are derived.

The results are consolidated into a structured growth opportunity map that quantifies central growth drivers, prioritised segments and concrete fields of action for sales, pricing and assortment.

Market transparency can be established both within a one-off study and on a continuous basis through a dedicated performance cockpit with dashboard integration, which can be linked via interfaces with internal controlling data (Figure 2: Advantages of AI-supported demand intelligence).

Figure 2: Advantages of AI-supported demand intelligence

Results and impact

Clients receive detailed, fact-based transparency on market sizes, competitive dynamics and performance drivers at article and category level. The demand-potential analysis forms the operational basis for data-driven sales, pricing and assortment decisions, and at the same time provides the structured starting point for further, AI-supported market and demand projections within the AI-supported forecasting. For PE investors in the CDD context, a robust, independent quantification of market potential emerges as a basis for business-plan validation.

Position within the service portfolio

The demand-potential analysis is part of FOSTEC & Company’s market intelligence portfolio. The complete portfolio comprises seven clusters with specialised analytical services:

• Demand & Market Potential Intelligence
• Assortment Potential Analysis
• Pricing & Revenue Intelligence
• Customer & Journey Intelligence
• Competitive & Share-of-Voice Intelligence
• Digital Shelf & Marketplace Intelligence
• Market Entry & Expansion Intelligence

Let us assess in an introductory conversation which market potential and competitive dynamics are relevant to your sales and assortment strategy – data-based, pragmatic and with clear, actionable recommendations.