If only we would know how a new product will do in the market, we will be super-rich. In this data-driven world, all innovations are highly backed by data and are really coming from consumer needs measured on a regular basis. However, still, new products fail in the market causing drastic losses and stalling growth of companies. Most companies depend on new launches to be a major driver of revenue growth in any planned year and failed new products affect those targets significantly.

A new product or innovation largely depends on two factors for its success in the market, and they are people factors and product factors.

People Factors:

Everett Rogers popularized this theory of how people accept a new innovation. It turns out that various personality profiles respond to innovation in different ways and accept innovation at different stages of its evolution. Everett categorized these adopters as innovators(2.5%), early adopters (13.5%), early majority (34%), late majority (34%), and laggards (16%). The product life cycle is categorized into different stages such as development, introduction, growth, maturity and decline stages of the product. The market characteristics for each stage change and the marketing mix used during these stages differ as well.

The blue line shows the adoption of various types of consumers which reaches its peak when a majority of the consumers have adopted the innovation and the orange line shows the growth of market share which theoretically grows to 100% as all consumers have adopted the innovation.

Product Factors:

It is understandable that apart from the people factors, the making of the product, the type of innovation itself drives the customer behavior in the direction of adoption. Therefore, the funnel of awareness, interest, evaluation, trial, and adoption itself becomes a critical process for innovation adoption. These funnel factors are determined by what kind of an innovation the product is, and we categorize that ‘kind of innovation’ as product factors.

• Relative Advantage: the degree to which an innovation is perceived as being better than the previous product(s) or idea.  This factor is considered to be a necessity in any innovation, however, it is not sufficient to influence trialability and adoption.
• Compatibility: the degree to which an innovation is perceived as consistent with the values and experiences of the potential adopter. This factor is considered to be important in influencing the rate of product adoption, better the compatibility faster the adoption.
• Complexity: the degree to which an innovation is considered as relatively difficult to understand and use. This factor reduces the rate of adoption and effective marketing and customer education is the counter to overcome this blockage.
• Trialability: the degree to which an innovation can be experimented on a limited basis by the customers. This factor significantly drives product adoption if implemented correctly.
• Observability: the degree to which an innovation or new product’s results are visible to others (not product users). This factor again drives product adoption significantly.

Measuring innovation (especially before launch) is as complicated as the human behavior itself. These ideas, though may seem theoretical, are crucial to gain a directional sense-check of new products and new product planning & development in any category.

Hope this is useful, thank you!