We are living today in a chaotic transition period defined by global competition, free flow of communication and information, rapid disruptive changes and globalization. The pace of change is characterized by breakthrough technological advances, where consumers are overwhelmed by choice – albeit in information , products and services. By reducing time to market ,smaller and nimble companies are challenging the market leaders and bringing in greater instability in market leadership and profitability of companies.
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The shape of the world in which speed, intangibles and connectivity dominate the social and economic landscape imply that these new forms of exchange is a transfer of power from the producer to the consumer( Meyer and Davis, 1998). Collaborative projects such as open source are transforming customers into product co-creators. Companies are looking to merge product and services to give customers a value added experience than mere product selling. A combination of these factors has created a tipping point for marketing, and techniques that used to work may not work anymore.
Product Life Cycle (PLC) is a well known marketing and strategy planning tool. It’s logical sequence and comparison with the biological world holds appeal for marketers and academics. Theodore Levitt (1965) introduced marketers to the concept of PLC , putting it to work as an “instrument of competitive power” and how it helps companies with their marketing and positioning strategies. PLC has generated a lot of research and academic discussion with conflicting views about its utility on one hand , it’s lack of customer focus and empirical backing and hence it’s utility as a marketing tool on the other hand . One school of thought propagates that using PLC for market forecasts to predict takeoff stage of a product is risky as each product has a different life cycle and estimation of stages is guesswork . An example being provided by the home computer boom which though predicted for 1978 didn’t happen till 1982 , by then most companies had left the market or gone bankrupt. Enis (1977) concluded that the PLC is the result , rather than the cause of marketing strategy decisions.
This author seeks to evaluate the assumptions and basis of PLC , with the backdrop of the new age marketing environment . The paper examines it’s efficacy as a managerial strategy framework by assessing linkages between PLC and various diffusion innovation models . It highlights the innovation growth drivers and how disruptive innovation models can be used to overcome limitations of the PLC . It concludes that while PLC has some limitations , however, when used with the correct management tools and techniques it can serve a useful purpose for marketers
New Age Marketing
The world in which marketing operates has fundamentally changed. Kenchi Ohmae (2005) in his book has discussed the requirements of operating on the new global stage (Wind Y , 2008) . Technologies from internet to biotechnology are fundamentally changing relationships of companies to the societies in which they operate with social concerns covering environmental impact and corporate social responsibility assuming great importance. Advertising in no more restricted to traditional means like TV, print media or broadcasts ,but has changed to include channels like Second Life , social networking , iPod , podcasts and computers. For example, SMS activity is a key marketing media vehicle in India and China(Soberman David ,2004). By breaking down distinction between products and services, (e.g.: home TV, mobile phones), and with more direct involvement of customers in the buying process (e.g.: eBay , Netflix) the sales distribution system has undergone a change .
The knowledge component of products and services has increased dramatically, knowledge as a source of business value has become critical for success . Market leaders are those who create and combine knowledge into new product and services faster than their competitors. This linked to the power of the internet has changed the fundamentals of doing business . As new ways of building and delivering products and services online emerge, competition goes beyond existing competitors to new companies , new innovations or ways of improving products . While speed to market is important , the evidence is that winners in emerging markets are those who dominate the phase of ‘early growth’ via fast penetration and a shortened ‘time to market’ (Patrick Barwise ,1995) .
The age of the active consumer is here to stay. Marketers need to see their customers as individuals with life time equity which needs to be retained by creating customer loyalty. Consumers today want to be in control. They want personalized products at competitive prices with an option to choose. This paradigm shift has brought the customer closer to the company. Products today are customized and marketing messages developed with customer participation in a YouTube world. The market place is becoming a forum where customers dynamically participate in product related activities (Prahalad and Ramaswamy, 2000). Customer involvement creates linkages between the demand and supply side forces. This has a bearing on the speed of diffusion of innovation and the market strategy firms need to adapt over the life of a product.
PLC as a Managerial Strategy Framework
Derived from the theory of diffusion of innovations, PLC is based on market conditions and requirements providing a framework to guide marketing strategies (Kotler,1984). Relative stability and growing affluence of the 1960s saw the PLC being positioned as an indicator of market dynamics describing the four stages taken by most products from introduction to decline. Due to absence of any research validating the concept and lack of empirical backing, it’s use as a predictive model in determining the timing of changes or alternative strategies to be adopted at each stage of the life cycle is limited. The definition of PLC has changed over the years, starting from market and brand life cycles by Levitt (1965) to Demand Life Cycles by (Kotler 2000) (Laurie ,1990) . Polli and Cook in 1969 suggested that the life cycle pattern was best captured by product class as a unit of analysis (Mary and George S , 1989) ; however Tellis and Crawford in 1981 felt that while brands are difficult to model ,PLC has little validity for product forms . Exhibit 1 shows the life cycle trends in filter cigarettes. The evidence shows lack of correlation between sales pattern of various filter cigarette brands and the product form and it does not provide any visibility into future sales ( Dhalla, Yuspeh S ,1976)
Exhibit 1 : Life cycle patterns of brands compared with product forms (Dhalla N , Yuspeh S , HBR ,1976)
There is a need to break out of the circle of product life and death syndrome which is unrelated to customer behavior but influences management into irrational decision making, like prematurely killing a valuable brand instead of looking for ways to resurrect it. While PLC lays emphasis on new product innovation, the current economic environment suggests a need to prolonging product life by retaining customers as against acquiring new customers. Marketers use tools like social networking and user groups to get insights into customer behavior and tastes. Apple, Chrysler and Starbucks offer marketing resources to customers, seeking their participation to stimulate market demand, reduce customer negligence towards marketing campaigns and drive them to making purchasing decisions (Agnihotri R , Hu Michael Y , 2009).
Use of marketing tools and smart advertising can alter the life cycle pattern. Dhalla and Yuspeh state that as long as a product satisfies the unmet needs of a large customer segment and is competitively priced, it will receive customer acceptance irrespective of how long it has been in existence (e.g.: cars , mouth washes).
Diffusion and Innovation Models : Linkages to Product Life Cycle
Diffusion of innovation is linked to the penetration of products. Traditionally, diffusion models have been based on the Bass model which considered consumer durables, and investigated the first-purchase growth in a single market (Agnihotri R , Hu Michael Y , 2009). It serves as a marketing framework for modeling the entire life-cycle of an innovation covering communications and consumer interactions. As shown in Exhibit 2, the social network is assumed to be fully connected and homogenous with two types of individuals who either adopt innovations due to external influences (i.e. advertising and other communications) or internal influences like word of mouth and interpersonal communications Measures of diffusion cover both the depth and breadth of innovation penetration (Chircu and Mahajan, 2009).
Exhibit 2 : Growth drivers for diffusion of an innovation
CRITICAL DRIVERS FOR DIFFUSION
WORD OF MOUTH
The gap between early adopters and the main market has increased due to sophistication and high-tech innovations. The role of adopters and influencers has increased, for example, penetration of internet and mobile phones in the 1990s was greatly influenced by the number of early adopters . Closely linked to this is the blurring of lines between products and services which has made customer choice processes more complex (for example should an iPhone be categorized as a mobile handset or a music player?). Globalization, increased competition, communication products and services has led diffusion to cover multiple markets (for example mobile phones were introduced across Scandinavia during one year) even going beyond consumer durables in a heterogeneous social system. A major growth driver of new products is consumer heterogeneity which claims that the population is heterogeneous in innovativeness, price sensitivity and needs, leading to heterogeneity in propensity to adopt. (Song and Chintagunta, 2003; Golder and Tellis,1998).
Based on the diffusion theory, three turning points emerge in the PLC influencing the shape of the curve. These are : takeoff – at the beginning , saddle – during early growth, and technological substitution – at the later stages of growth. Golder and Tellis (1997) using the proportional hazard model have defined takeoff time as the time at which a dramatic increase in sales occurs that distinguishes the cutoff point between the introduction and growth stages. While takeoff does not require any consumer interactions, the acceptance rate depends on price sensitivity, probability of failure , competitive advantage and ease of availability.
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Heterogeneity influences the stage prior to takeoff, while consumer interactions impact the succeeding stage (as shown in Exhibit 2). Following takeoff, the classic diffusion model predicts an increase in sales; however, in some markets, the increase might not follow this trend, and a chasm or dip in sales may occur after an initial rise (Moore,1991) followed by sales that eventually exceed the initial peak ( shown in Exhibit 3). The diffusion process ends when the market potential is saturated. In practice, however, products are substituted with advanced products and next technological generations . This may not always be correct, as in the case of analog phones, where both generations coexisted with analog subscribers continuing to increase long after digital technologies became available. With time, as buyer’s familiarity with a product increases, there is more emphasis on price and reduced impact of consumer interactions (as shown in Exhibit 2).
Exhibit 3 : Turning points in the product life cycle (Name of Journal, Author, Year)
Disruptive Innovation Techniques and their Impact on PLC :
In his disruptive innovation model, Clayton Christensen describes how competitors with simpler technologies or service offerings create vulnerabilities for mature brands who have added a multitude of features to the base product (Moon , 1995) . Exhibit 4 shows how companies have manipulated the PLC by altering product positioning to the growth phase or by redefining category boundaries. IKEA used a combination of reverse positioning by combining a basic offering with smart marketing (through a novel store experience ) to escape the PLC and targeting a new customer category . Jet Blue and Ryan Air have used simplicity , transparent pricing and a no frills approach to create loyal brand ambassadors and a unique market positioning (Moon , 1995 ). Products can prolong their life by manipulating PLC stages or by altering the marketing mix and product positioning. Swatch is a prime example of how Swiss watches sold as jewellery were repositioned as affordable fashion accessories. Swatch thus revived the product growth and created a new sub category. In technology products and services where time to market is key, Apple Mac Mini changed consumer resistance and accelerated its move from introduction to maturity stage by orchestrating an alternate market positioning strategy (Moon, 1995).
Exhibit 4: PLC and Smart Marketing Repositioning of Products for Growth (HBR , Moon Youngme , 1995)
Swatch repositioned the category by changing the perception that watches were also affordable fashion accessories
Apple repositioned Mac Mini outside its category to enhance diffusion and quick penetration to growth stage
Ikea stripped attributes in it’s offerings but created a novel store experience moving products back from maturity to growth stages.
Conclusion : Has the PLC outlived itself
The popular notion that products follow a pattern of birth, growth, maturity and then decline appears to be flawed logic, as conditions prevailing in the biological world are not true for the marketing world. The product phases cannot be accurately judged (for example video game industry boomed and faded like a typical fad). Products jump from introductory to maturity stage, and sometimes even gain a new lease of life or rebirth thanks to smart marketing campaigns (Moon, 1995). Many product classes because they satisfy basic human needs (e.g.toothpaste) have lived long lives not adhering to the life cycle pattern highlighting that PLC is based on qualitative measures.
Marketing Science Institute in its validation for over 100 consumer durable products arrived at a hypothesis that PLC was slightly better than a chance model in explaining sales behavior as only about 20% of products followed the life cycle stages, with an even lesser relevance for brands (Polli and Cook 1969 ). Over time as the marketing concept has enlarged , weaknesses have emerged when we try to fit the PLC to cover high tech products (Tiger and Farrivar, 1981) , consumer durables (Harrell and Taylor,1981) and services (Buskirk ,1986) . The key utility of PLC has been perceived to be in forecasting and pre-planning (Levitt,1965). However, Kotler(1988) accepts that its value in forecasting is also limited , it being more applicable to historical sales patterns, for planning and control .
In today’s environment where marketing is focusing itself to meet individual customer needs; technology and management techniques focus on marketing environmental analysis . At product and brand level, conjoint analysis and diffusion models provide accurate estimates of customer behavior and decision making while market modeling techniques are used to solve situation analysis problems. Consumer behavior looks at purchase decisions over the product’s life covering “first” versus “repeat” purchases , “innovative first purchase” versus. ” imitative first purchase” and choosing between “incumbent” and “substitute” products as a starting point rather than using the sales pattern (Paul ,2002).The limitations are not with the PLC but with its proponents ignoring evolutionary market trends and placing undue reliance on the sales curve. In applying predetermined solutions to marketing situations, companies become predictable and vulnerable to smaller competitors .
It is evident that PLC alone cannot serve the purpose as a marketing tool . It’s application has to be combined with a consideration of underlying factors and processes relevant to a market situation. A PLC forecast should not become a fait accompli but be one of the many options available that have a dependence on a robust information system, understanding of market forces and competition (Day, 1981). In the current marketing environment it can play a supportive role in marketing strategy decision making so long as it’s limitations are known.
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