MARKETING DECISION MAKING

Decision Making

CAC

This document covers the basic concepts of Marketing

Decision Making

CONTENTS

1. Go-To-Market Strategies

2. Marketing Research a. MDS and Semantic Analysis (Perceptual Maps) b. Conjoint Analysis

3. Sales Force Sizing

4. Resource Allocation

5. Forecasting Product Category Demand (Bass Model)

6. Estimating Maximum Willingness to Pay

Go-To-Market Strategies

A Go-to-Market Strategy involves designing& managing an efficient& effective portfolio of "go-to-market" participants that connect a firm with its customers to create sales.

Activities: Customer Attraction& Retention Activities: • Interest creation • Pre-purchase • Purchase •

Post-purchase; Other channel functions: Processing ownership, breaking bulk, Delivery, Credit& finance.

Participants: Sales Force Options: Direct Sales Force Agents / Distributors / Retailers/Value-Added Partners. Non Sales Force: Advertising &/Promotion/Direct Mail/Tele-channels/Internet.

Steps in the Process:

Marketing Research

Uses of marketing research:

Diagnostic analysis: Nature of the market? What is our current performance?

Opportunity analysis: Opportunities for growth?

Two Key Questions: What attributes does the consumer use in comparing competing products& how do these characteristics relate to the technical features [Perceptions]. What is the relative weight assigned to each attribute when deciding which product to buy [Preference]

MDS and Semantic Analysis (Perceptual Maps)

Uses of Perceptual Maps:

1. Customer Analysis and Competitive Analysis 1. Understand the competitive market structure as perceived by customers.

a. Position relative to competition b. Select the set of competitors to compete against

2. Represent customers’ perceptions in a manner that aids

communication and discussion within the organization

2. Product 1. Perceptions of a new product concept in the context of existing brands in the market 2. Finding the “gap” in the market to position the product

Semantic Analysis REMEMBER: Semantic Scaling always asks questions about the perceived products along a number of dimensions.

MDS Analysis: REMEMBER: MDS always asks questions about SIMILARITIES and DISSIMILARITIES between TWO Products on various attributes

Conjoint Analysis

1. Steps in Conjoint: a. Attribute list formation b. Data collection c. Utility Calculation d. Market Simulation

Conjoint (trade-off) analysis has become one of the most widely-used quantitative methods

in Marketing Research. It is used to measure the perceived values of specific product

features, to learn how demand for a particular product or service is related to price, and to

forecast what the likely acceptance of a product would be if brought to market.

In contrast to simpler survey research methods that directly ask respondents what they

prefer or the important of each attribute, these preferences are derived from these relatively

realistic tradeoff situations. Each profile includes multiple conjoined product features (hence, conjoint analysis), such as:

There are different ways to show product profiles. Respondents usually complete between 12 to 30 conjoint questions. The questions are

designed carefully, using experimental design principles of independence and balance of

the features. By independently varying the features that are shown to the respondents and

observing the responses to the product profiles, the analyst can statistically deduce what

product features are most desired and which attributes have the most impact on choice.

The result is usually a full set of preference scores (often called part-worth utilities) for each attribute level included in the study. (This is obtained by running a regression) Summing up the part-worth utilities gives the utility of the particular profile.

Mathematical Representation Example:

Summary Steps of Conjoint Analysis Application:

2. Applying the choice Model (converting utility scores for product alternatives to probabilities of choice):

a. Maximum utility rule (deterministic) Pick the Product with the maximum utility score

b. Logit Model (Probabilistic)

3. Mind Share Indications:

Pros and Cons of Conjoint Analysis:

Pros: 1. Results are easy to interpret& key attributes are easily established. 2. Attributes can be categorical as well as intervally scaled.

Cons: 1. Relevant attributes& key levels must be known in advance 2. Approach gets messy with many attributes& levels 3. Market share estimates obtained differ from actual shares.

Some Real World Applications of Conjoint:

Sizing the Sales Force

Four-Step Market-Based Process:

1. Customer Understanding: a) Identification b) Needs c) Buying processes

2. Customer Segmentation.

3. Segment Coverage& Assessment of segment value for the firm.

4. Sales Force Sizing.

Approaches to Sales Force Sizing:

1. Financial approaches: a) Percentage of sales b) Affordability

2. Workload buildup approaches: Develop the most appropriate workload for each market segment; Add up the effort required to cover each of the market segments; SFS=SE/SEapp

3. Sales response approach:

Adbudg:

• Used to measure market response to advertising& sales force • Uses judgments-structured survey among managers to harvest the collective wisdom about market responsiveness •Uses soft data to quantify market responses i.e puts equation to intuition • Upside– very useful in scenarios with no data– quick–builds consensus–encourages systematic thinking;

Implementation:

What do you expect the sales level (relative to current levels) to be in response to – no sales force – 50% of current sales force

– 100% of current sales force

– 150% of current sales force

– saturation level sales force

Answering these questions is usually done by forcing a consensus estimate from a team of managers– all

members of the team first answer the questions privately– results are revealed& discussed– adjustments

are made& discussed until a single set of answers to the 5 questions remains.

After the calculations are made, Sales Response is calculated as: Sales response = min + (max – min) SF

c/ (d + SF

C) ; d = Competition Parameter, c = shape parameter.

Resource Allocation

Market Share Identity: Market Share = Awareness x (Intention/Awareness) x (Market Share /

Intention) = α (product quality) x Advtβ-1 x Prt

β x Sft

β

where β are the advertising, price& sales force elasticities.

From Elasticities to Allocation:

Allocating resources across multiple products within an SBU:

1. Without interdependent demand: 2. With interdependent demand : Interdependent demand Examples: Gillette Sensor and Gillette Sensor Prestige Detergents (Tide and Cheers) by P&G

American Express Green, Gold and Platinum cards

Empirical Generalizations on Elasticities:

Allocating Resources across Segments

BCG Matrix Approach:

Classify Product/Business Groups on two dimensions: – “market/industry attractiveness” [how good is the

market] – “company/business strength” [how strong am I]

Business strength is measured as “Relative Market Share’’ – The larger I am, the greater is the likelihood that I can generate cash

Industry Attractiveness is measured as “% age growth rate of the market” – Growing industries are more attractive

– Growing industries require cash

Assumptions: • All managers of various divisions share the same corporate goal • All managers agree that opportunities vary at any point in time and over time • There is sufficient information about ajor competitors and market structur