Product Research Product development marketing research serves several goals: new product design and market validation research, or assessing existing.

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Presentation transcript:

Product Research Product development marketing research serves several goals: new product design and market validation research, or assessing existing products. The goal -- and your overall positioning and market strategy -- drive product research design.

Effective product market research -- for new products and existing products -- is well integrated with R&D and technical product design functions. For consumer or business B2B product market research, we take a global approach, incorporating appropriate market research at each design stage: The goal is to align technical product R&D, product innovation and design with market demand.

New Product Development Stages For new product development market research, the question becomes one of matching the stage of new product development with the right creative or product market research method

Product development market research methods and tools used may vary according to the product type, the extent of incremental change from other products, the investment and risk factors, and the costs of seeding the new product in the marketplace.

Product development is a sequential decision process. It's a series of decisions, not one. It is key, therefore, to concentrate attention on the precise new product decision at hand, and think through the market research and creative tools needed for that stage.

Sales analysis Most organizations track their sales results; or, in non-profit organizations for example, the number of clients. The more sophisticated track them in terms of 'sales variance' - the deviation from the target figures — which allows a more immediate picture of deviations to become evident. `Micro-analysis', which is simply the normal management process of investigating detailed problems, then investigates the individual elements (individual products, sales territories, customers and so on) which are failing to meet targets.

Sales forecasting is a difficult area of management. Most managers believe they are good at forecasting. However, forecasts made usually turn out to be wrong! Marketers argue about whether sales forecasting is a science or an art. The short answer is that it is a bit of both.

Reasons for undertaking sales forecasts Businesses are forced to look well ahead in order to plan their investments, launch new products, decide when to close or withdraw products and so on. The sales forecasting process is a critical one for most businesses. Key decisions that are derived from a sales forecast include: - Employment levels required - Promotional mix - Investment in production capacity

Types of forecasting There are two major types of forecasting, which can be broadly described as macro and micro: Macro forecasting is concerned with forecasting markets in total. This is about determining the existing level of Market Demand and considering what will happen to market demand in the future. Micro forecasting is concerned with detailed unit sales forecasts. This is about determining a product’s market share in a particular industry and considering what will happen to that market share in the future.

The selection of which type of forecasting to use depends on several factors: (1) The degree of accuracy required – if the decisions that are to be made on the basis of the sales forecast have high risks attached to them, then it stands to reason that the forecast should be prepared as accurately as possible. However, this involves more cost (2) The availability of data and information - in some markets there is a wealth of available sales information (e.g. clothing retail, food retailing, holidays); in others it is hard to find reliable, up-to-date information

The time horizon that the sales forecast is intended to cover. For example, are we forecasting next weeks’ sales, or are we trying to forecast what will happen to the overall size of the market in the next five years? (4) The position of the products in its life cycle. For example, for products at the “introductory” stage of the product life cycle, less sales data and information may be available than for products at the “maturity” stage when time series can be a useful forecasting method.