JBDON
  • Home
  • Applied Analytics
    • Analytics for Decision Making >
      • What is Cluster Analysis
      • Data Reduction and Unsupervised Learning
      • Preparing Data and Measuring Dissimilarities
      • Hierarchical and k-Means Clustering
      • Defining Output Variables and Analyzing the Results
      • Using Historical Data to Model Uncertainty
      • Models with Correlated Uncertain Variables
      • Creating and Interpreting Charts
      • Using Average Values versus Simulation
      • Optimization and Decision Making
      • Formulating an Optimization Problem
      • Developing a Spreadsheet Model
      • Adding Optimization to a Spreadsheet Model
      • What-if Analysis and the Sensitivity Report
      • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
      • Digital Marketing Application of Optimization
      • Advanced Models for Better Decisions
      • Business Problems with Yes/No Decisions
      • Formulation and Solution of Binary Optimization Problems
      • Metaheuristic Optimization
      • Chance Constraints and Value At Risk
      • Simulation Optimization
    • Analytics for Marketing >
      • Marketing Analytics and Customer Satisfaction
      • Customer Satisfaction
      • Measurements and Scaling Techniques – Introduction
      • Primary Scales of Measurement
      • Comparative Scaling
      • Non-Comparative Scaling
      • Experiment Design: Controlling for Experimental Errors
      • A/B Testing: Introduction
      • A/B Testing: Types of Tests
      • ANOVA – Introduction
      • Example -Inspect Spray and Tooth Growth
      • Logit Model - Binary Outome and Forecastign linear regression
      • Text Summarization
      • Social media Microscope
      • N-Gram - Frequcy Count and phase mining
      • LDA Topic Modeling
      • Machine-Learned Classification and Semantic Topic Tagging
    • Data Engine >
      • Understanding The Growth Of Data
      • Evaluating Methods Of Data Access
      • Communication journey
      • Data Journey
      • Planning for data visualisation
      • Visualisation Component
      • Content Connection and Chart Legitibility
    • Customer Insights >
      • Introduction
      • What is Descriptive Analytics?
      • Survey Overview
      • Net Promoter Score and Self-Reports
      • Survey Design
      • Passive Data Collection
      • Media Planning
      • Data Visualization
      • Causal Data Collection and Summary
      • Asking Predictive Questions
      • Regression Analysis
      • Data Set Predictions
      • Probability Models
      • Results and Predictions
      • Perspective Analytics (Maximize Revenue and Market Structure Competitions)
    • Analytics for Advance Marketing >
      • Visualisation and statistics (Political Advertising,Movie Theater and Data Assembly)
      • Excel Analysis of Motion Picture Industry Data
      • Displaying Conditional Distributions
      • Analyzing Qualitative Variables
      • Steps in Constructing Histograms
      • Common Descriptive Statistics for Quantitative Data
      • Regression-Based Modeling
      • Customer Analytics
      • Illustrating Customer Analytics in Excel
      • Customer Valuation Excel Demonstration
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
  • Marketing
  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Demand and Revenue Analysis >
        • Demand Estimation and Forecasting
        • Demand Elasticity
        • Demand Concepts and Analysis >
          • Formulation and Solution of Binary Optimization Problems
      • Scope of Managerial Economics
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies >
        • Adding Optimization to a Spreadsheet Model
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
    • Digital Marketing Application of Optimization
  • Let's Talk
  • MBA Project Sharing
  • About Us
    • Good Read >
      • IIMC says PepsiCo CEO Indra Nooyi was an average student
      • India’s middle class figures in Fortune’s Top Ten list of those who matter
      • The Start-Up of you.
      • BUYING AND MERCHANDISING
      • HUMAN RESOURCE MANAGEMENT
      • Do You Suffer From Decision Fatigue?
      • New Page
      • About social media and web 2.0
      • Building Your Own Start-up Technology Company, Part 1
      • Building Your Own Start-up Technology Company, Part 2
      • Building Your Own Start-up Technology Company, Part 3
      • Building Your Own Start-up Technology Company, Part 4
      • Renewable energy is no longer alternative energy
      • What Makes an Exceptional Social Media Manager?
      • The Forgotten Book that Helped Shape the Modern Economy
      • Home
      • How to Think Creatively
      • A Lighthearted Looks at Project Management and Sports Analogies
      • Why Trust Matters More Than Ever for Brands
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Marketing Analytics and Customer Satisfaction
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • Untitled
  • New Page
    • Cluster analysis using excel and excel miner
    • Chance Constraints and Value At Risk
    • Adding Uncertainty to a Spreadsheet Model
  • Adidas

Picture
Picture

Product Life Cycle

To be able to market its product properly, a firm must be aware of the product life cycle of its product. The
standard product life cycle tends to have five or six phases:

1. Development
2. Introduction
3. Growth
4. Maturity
5. Decline

It can also be shown graphically. The graph often has two lines - one to show the level of profit, and one to
show the level of sales:
Firms will often try to use extension strategies. These are techniques to try to delay the decline stage of the
product life cycle. The maturity stage is a good stage for the company in terms of generating cash. The costs
of developing the product and establishing it in the market are paid and it tends to then be at a profitable
stage. The longer the company can extend this stage the better it will be for them.

THE PRODUCT LIFE CYCLE (PLC)
Unbelievably the Product Life Cycle (PLC) is based upon the biological life cycle. For example, a seed is
planted (introduction); it begins to sprout (growth); it shoots out leaves and settles, as it becomes an adult
(maturity); after a long period as an adult, the plant begins to shrink and die out (decline).

In theory, it is the same for a product. After a period of development it is introduced or launched into the
market; it gains more and more customers as it grows; eventually the market stabilises and the product
becomes mature; then after a period of time the product is overtaken by development and the introduction
of superior competitors, it goes into decline and is eventually withdrawn. However, most products fail in
the introduction phase. Others have very cyclical maturity phases where declines see the product promoted
to regain customers.

STRATEGIES FOR THE DIFFERING STAGES OF THE PLC

INTRODUCTION
The need for immediate profit is not a pressure. The product is promoted to create awareness. If the product
has no or few competitors, a skimming price strategy is employed. Limited numbers of product are
available in few channels of distribution.
GROWTH
Competitors are attracted into the market with very similar offerings. Products become more profitable and
companies form alliances, joint ventures and take each other over. Advertising spend is high and focuses
upon building brand. Market share tends to stabilise.
MATURITY
Those products that survive the earlier stages tend to spend longest in this phase. Sales grow at a decreasing
rate and then stabilise. Producers attempt to differentiate products and brands are key to this. Price wars
and intense competition occur. At this point, the market reaches saturation. Producers begin to leave the
market due to poor margins. Promotion becomes more widespread and uses a greater variety of media.
DECLINE
At this point, there is a downturn in the market. For example, more innovative products are introduced or
consumer tastes have changed. There is intense price-cutting and many more products are withdrawn from
the market. Profits can be improved by reducing marketing spend and cost cutting.

STRATEGIES FOR THE DIFFERING STAGES OF THE PLC
INTRODUCTION
The need for immediate profit is not a pressure. The product is promoted to create awareness. If the product
has no or few competitors, a skimming price strategy is employed. Limited numbers of product are
available in few channels of distribution.
GROWTH
Competitors are attracted into the market with very similar offerings. Products become more profitable and
companies form alliances, joint ventures and take each other over. Advertising spend is high and focuses
upon building brand. Market share tends to stabilise.
MATURITY
Those products that survive the earlier stages tend to spend longest in this phase. Sales grow at a decreasing
rate and then stabilise. Producers attempt to differentiate products and brands are key to this. Price wars
and intense competition occur. At this point, the market reaches saturation. Producers begin to leave the
market due to poor margins. Promotion becomes more widespread and uses a greater variety of media.
DECLINE
At this point, there is a downturn in the market. For example, more innovative products are introduced or
consumer tastes have changed. There is intense price-cutting and many more products are withdrawn from
the market. Profits can be improved by reducing marketing spend and cost cutting.

PROBLEMS WITH PLC
In reality, very few products follow such a prescriptive cycle. The length of each stage varies enormously.
The decisions of marketers can change the stage, for example from maturity to decline by price-cutting. Not
all products go through each stage. Some go from introduction to decline. It is not easy to tell which stage
the product is in. Remember that PLC is like all other tools. Use it to inform your gut feeling
The product life cycle has been part of marketing strategy since the late 50's. All of us are either intuitively
or intellectually aware of its five stages of introduction, growth, maturity, saturation and decline. Yet, this
classic model now faces the same inevitability it predicted for brands and market segments. We all face a
new reality wherein everyone knows the model, emulates it, and then with alarming regularity...fails.
Failure comes from the predictability of the strategies that we all believed were dictated by the model. Over
the past five years, we have seen mature core brands suffocate under their own weight like lost, beached
whales on the shores of EDLP (every day low price) Beach.

Marketers like Proctor & Gamble and Phillip Morris find themselves in well-published price wars executed
under the belief that mature products ultimately come under price point scrutiny. The success of private
labels and EDLP policy at retail seem to hold this precept up. Therefore, to maintain share of market, the
strategy is to coupon, discount or die. That belief came from strategies implied by the product life cycle.
That strategy says reap the rewards of your brand equity in the mature phase of your products life cycle.
You have already invested in R&D, advertising and marketing, now cash in and hold share at all costs even
if it means erosion of profits. Now, as market share for brands like Tide and Budweiser wither, we must
question the validity of these standard strategies for mature products.

Ironically, the strategies implied by the early phases of the life cycle seem to still hold their validity.
Introduction and growth phases are still driven by establishing needs and brand awareness. These early
phases are also traditionally, where most creativity and corporate resources are applied in the execution of
the model's prescribed strategy. Mature brands and segments are troubled and seem to be incapable of
finding creative executions of traditional strategies. "Me too" products, new sizes, more shelf space, and
other non-benefits (new "improvements" that have no value to the end-user) as well as discounting and
couponing, are failing miserably as tactics to revive saturated and declining brands, segments and
categories. These classic tactics are doomed to failure, as evidenced by the onslaught and success of private
labels and the erosion of market share of many "bulletproof" brands. This reality must force us to rethink
maturity. Everyone seems to think Kellogg’s is crazy to raise their prices. Flood conditions aside, if these
price increases are turned back into marketing resources, Kellogg’s could claim unforeseen new market
share. They will do this by out marketing their competitors and building new equity into their precious
brands rather than strip-mining what is left of their value.

I am a marketing and media consultant who works primarily with radio stations. Many marketers consider
radio to be in the sixth phase of maturity: death. Not so, though I must say that as an industry we have
danced in the traffic for some time. We have learned quite a bit about maturity in the past 12 years since
deregulation hit us. A few truths have begun to emerge as we raise ourselves out of the hangover of debt
leverage, and exponential growth in competition from the end of government-enforced scarcity.

We learned that heritage means nothing when a more focused niche option arrives. Targeted oldies stations
now outnumber and out bill "mass appeal" Top 40 stations -- so much for brand equity. We are learning that
more shelf space is not the answer either, as stations take advantage of further deregulation and double up
in their markets only to learn they have more to sell and not necessarily more demand. Additionally, buying
a station in a market where you already own one only increases the value of the new station 15%--so much
for catching up with the rest of the marketing world. Nevertheless, on our steep learning curve we have
discovered that there are strategies and tactics to revitalize maturity. In radio, we are learning we must be
fundamentally different from our competitors.

Death for mature brands is not a fait accompli. Line extension is still valid. There are two critical factors.
First that the originating line is still truly strong, that it still has validity. Second that the extension not
simply be better or improved, but be fundamentally and discreetly different from the originating line.
Ultimately, line extension is valid only when used properly: as a response to a new competitor in a segment,
you have established (cola wars) or as a tactic in a strategy to segment, a broad-based brand into its
emerging niches (Bayer aspirin). Witness market share erosion of Cinch spray cleaner and the roll out of Mr.

CLEAN GLASS AND SURFACE CLEANER
The traditional marketing management techniques for mature products are dead. Price wars, cannibalistic
promotional exercises, and shelf-facing politics only temporarily address declining market share. They do
not address the root problem: the changed market place and the need that is served by the brand in its
current form. Great advertising will only accelerate the death of a declining product if its fundamental
attributes do not evolve with the demands of the market. Mature brands must now adapt to market trends
with the same speed and accuracy that new entries do. To accomplish that strategy we must apply the same
resources and creativity to mature products that we use for new ones. Only then will we be sure our sacred
cash cows stay out to pasture and not get slaughtered.
Powered by Create your own unique website with customizable templates.
  • Home
  • Applied Analytics
    • Analytics for Decision Making >
      • What is Cluster Analysis
      • Data Reduction and Unsupervised Learning
      • Preparing Data and Measuring Dissimilarities
      • Hierarchical and k-Means Clustering
      • Defining Output Variables and Analyzing the Results
      • Using Historical Data to Model Uncertainty
      • Models with Correlated Uncertain Variables
      • Creating and Interpreting Charts
      • Using Average Values versus Simulation
      • Optimization and Decision Making
      • Formulating an Optimization Problem
      • Developing a Spreadsheet Model
      • Adding Optimization to a Spreadsheet Model
      • What-if Analysis and the Sensitivity Report
      • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
      • Digital Marketing Application of Optimization
      • Advanced Models for Better Decisions
      • Business Problems with Yes/No Decisions
      • Formulation and Solution of Binary Optimization Problems
      • Metaheuristic Optimization
      • Chance Constraints and Value At Risk
      • Simulation Optimization
    • Analytics for Marketing >
      • Marketing Analytics and Customer Satisfaction
      • Customer Satisfaction
      • Measurements and Scaling Techniques – Introduction
      • Primary Scales of Measurement
      • Comparative Scaling
      • Non-Comparative Scaling
      • Experiment Design: Controlling for Experimental Errors
      • A/B Testing: Introduction
      • A/B Testing: Types of Tests
      • ANOVA – Introduction
      • Example -Inspect Spray and Tooth Growth
      • Logit Model - Binary Outome and Forecastign linear regression
      • Text Summarization
      • Social media Microscope
      • N-Gram - Frequcy Count and phase mining
      • LDA Topic Modeling
      • Machine-Learned Classification and Semantic Topic Tagging
    • Data Engine >
      • Understanding The Growth Of Data
      • Evaluating Methods Of Data Access
      • Communication journey
      • Data Journey
      • Planning for data visualisation
      • Visualisation Component
      • Content Connection and Chart Legitibility
    • Customer Insights >
      • Introduction
      • What is Descriptive Analytics?
      • Survey Overview
      • Net Promoter Score and Self-Reports
      • Survey Design
      • Passive Data Collection
      • Media Planning
      • Data Visualization
      • Causal Data Collection and Summary
      • Asking Predictive Questions
      • Regression Analysis
      • Data Set Predictions
      • Probability Models
      • Results and Predictions
      • Perspective Analytics (Maximize Revenue and Market Structure Competitions)
    • Analytics for Advance Marketing >
      • Visualisation and statistics (Political Advertising,Movie Theater and Data Assembly)
      • Excel Analysis of Motion Picture Industry Data
      • Displaying Conditional Distributions
      • Analyzing Qualitative Variables
      • Steps in Constructing Histograms
      • Common Descriptive Statistics for Quantitative Data
      • Regression-Based Modeling
      • Customer Analytics
      • Illustrating Customer Analytics in Excel
      • Customer Valuation Excel Demonstration
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
  • Marketing
  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Demand and Revenue Analysis >
        • Demand Estimation and Forecasting
        • Demand Elasticity
        • Demand Concepts and Analysis >
          • Formulation and Solution of Binary Optimization Problems
      • Scope of Managerial Economics
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies >
        • Adding Optimization to a Spreadsheet Model
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
    • Digital Marketing Application of Optimization
  • Let's Talk
  • MBA Project Sharing
  • About Us
    • Good Read >
      • IIMC says PepsiCo CEO Indra Nooyi was an average student
      • India’s middle class figures in Fortune’s Top Ten list of those who matter
      • The Start-Up of you.
      • BUYING AND MERCHANDISING
      • HUMAN RESOURCE MANAGEMENT
      • Do You Suffer From Decision Fatigue?
      • New Page
      • About social media and web 2.0
      • Building Your Own Start-up Technology Company, Part 1
      • Building Your Own Start-up Technology Company, Part 2
      • Building Your Own Start-up Technology Company, Part 3
      • Building Your Own Start-up Technology Company, Part 4
      • Renewable energy is no longer alternative energy
      • What Makes an Exceptional Social Media Manager?
      • The Forgotten Book that Helped Shape the Modern Economy
      • Home
      • How to Think Creatively
      • A Lighthearted Looks at Project Management and Sports Analogies
      • Why Trust Matters More Than Ever for Brands
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Marketing Analytics and Customer Satisfaction
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • Untitled
  • New Page
    • Cluster analysis using excel and excel miner
    • Chance Constraints and Value At Risk
    • Adding Uncertainty to a Spreadsheet Model
  • Adidas