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Business Unit 3&4 > 3.1 Setting Marketing Objectives > Flashcards

3.1 Setting Marketing Objectives Flashcards

1
Q

Marketing objectives

A
  1. Sales volume and market size
  2. Market size
  3. Market and sales growth
  4. Market share
  5. Brand loyalty
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2
Q

The value of setting marketing objectives

A

Helps departments to stay on track with what the business hopes to achieve overall

Marketing department objectives must align with corporate objectives

  • E.g. if the business wants to expand, the marketing dept may set an objective to increase market share to support this
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3
Q

The marketing objectives are of value as:

A

Provide a focus and direction for the marketing activities and strategy of the business

Help ensure the resources of the marketing dept are used effectively

Motivate and align the people working within marketing dept/functional area

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4
Q

Two categories of Market Research

A

Primary Research: Data collected first-hand for a specific research purpose

Secondary Research: Data that already exists and which has been collected for a different purpose

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5
Q

Sources of Primary data

A
  1. Observation
  2. Postal survey
  3. Telephone interview
  4. Online survey
  5. Focus groups
  6. Face-to-face survey
  7. Test marketing
  8. Experiments
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6
Q

Focus groups

A

A form group is a form of qualitative research in which a group of people are asked about:

  1. Their perception
  2. Opinion
  3. Beliefs
  4. Attitudes towards a product
  5. Service
  6. Concept
  7. Advertisement
  8. Idea
  9. Packaging
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7
Q

Benefits and drawbacks of Primary Market Research

A

Benefits:

  1. Specifically built based on business needs
  2. Up-to-date and relevant
  3. Kept private
  4. Detailed insight - particularly into customer views

Drawbacks:

  1. Expensive to obtain
  2. Time consuming and needs to be analysed
  3. Risk of survey biased
  4. Sampling may not represent the wider market
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8
Q

Sources of secondary data

A
  • Google - quick and inexpensive
  • Government departments - detailed insights on the economy
  • Trade associations: great for market analysis
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9
Q

Benefits and Drawbacks of Secondary Market Research

A

Benefits:

  1. Often free but usually cheaper than primary research
  2. Good insights as data has already been analysed
  3. Quick to access and use

Drawbacks:

  1. Can quickly become out-of-date
  2. Not tailored to specific business needs
  3. Specialist report are often quite expensive
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10
Q

Quantitative and Qualitative data

A
  • Quantitative data:
    1. Based on numbers and figures.
    2. Focused on quantity.
    3. Easy to analyse but not detailed.
  • Qualitative:
    1. Based on opinions, attitudes and beliefs.
    2. Focuses on the reason.
    3. More difficult to analyse but detailed
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11
Q

Market size

A
  • Indicates the potential sales for a firm
    Measured in terms of both volume (units) and value (sales)
  • Size of individual segments within the overall market can also be measured
  • Not a market objective since a firm cannot influence it
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12
Q

Market growth

A

Key indicator for existing and potential market entrants

Growth rate can be calculated using either value (e.g., market sales) or volume (units sold)

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13
Q

Market share

A

Explains how the market is divided between the existing competitors

Tends to be calculated based on market value but volume can also be used

Good indicator of competitive advantage

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14
Q

Sampling in a market share

A

Sampling involves the gathering of data from a sample that can represent the population

  • E.g., target market
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15
Q

Types of sampling: Random

A

Every member of the population has the equal chance of being selected.

  • E.g., every tenth person can be stopped and asked to complete a questionnaire

Random sampling does not target any specific segments of the market

It is quick and easy to select and it reduces bias

The sample may not represent the target market

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16
Q

Types of sampling: Quota

A

Respondents are selected based on specific characteristics. E.g., age, income or location

  • The required number of respondents (the Quota) is drawn from each segment of the population
  • Quota sampling is representative of the whole market and requires less respondents than Random sampling
  • It is not random, could bring bias in the selection process
17
Q

Types of sampling: Stratified

A

The researcher stratifies the target group into sections representing a key group or characteristics to represent the final sample.

  • For example: a class has 20 students, 18 (M), 2 (F). The researcher needs 10 students, so it would randomly take 9 (M) and 1 (F), to represent the population.
18
Q

Correlation

A

Looks at the strength of the relationship between two variables

19
Q

Correlation and Scatter graphs

A

Correlation is used in Scatter Diagram, on which data points are plotted

The independent variable is plotted on the X axis. This is the factor that causes the other variable to change

  • E.g., if a business may be keen to understand the impact of the customer enquiries if advertising expenditure is varied
  • In this case, advertising expenditure would be the indipendent variable and customer enquiries would be the dependant variable
  • A line of best fit would be used to plot the mathematical relationship between the variables
20
Q

Types of correlation

A
  • Positive: a positive relationship is where the independent variable changes as well as the dependent variable
  • Negative: a negative correlation is when the independent variable increases and dependent variable falls
  • No correlation: There is no discernible relationship between the independent variable and dependent variable
21
Q

Strong and weak correlation

A

Strong Correlation:
- The line of best fit indicates the strength of the correlation.
- Little rooom between data points and the line
- A strong correlation can suggest marketing predictions

Weak correlation:
- Weak correlation means data points are spread from the line of best fit.

22
Q

Confidence interval

A

A confident interval gives the percentage probability that an estimated range of possible values in fact includes the actual value being estimated

23
Q

Confidence intervals

A
  • Businesses benefit from the use of statistics in estimating or predicting future intervals
  • A confidence interval helps a business evaluate the reliability of a particular estimate
  • Because no estimate can be 100% reliable, businesses need to know how confident they should be in their estimates or whether to act on them
24
Q

Confidence intervals (example)

A
  • If a manufacturing firm takes samples of finished goods from it’s production line to check for quality, how confident can the business be that sample of products inspected is representative of all products being made.
  • A common confidence interval acceptable to management is 95%. This means that 19 out of 20 will give results that represents the overall population. Or, -1 out of 20 (5%) is unrepresentative.
25
Q

Confidence intervals: (Example p.2)

A
  • Quality management: percentage reliability of machines. Chances that quality control samples will detect issues
  • Market Research: statistical estimates for sales forecasting reliability of data from customer surveys
  • Risk management & contingency plans: risk of sales forecast not be achieved scenario planning for competitor actions
  • Budgeting and forecasting: likely range of revenues and costs based on key assumptions. Sales forecasts to support new product launches.
26
Q

Extrapolation

A

Uses trends estabilished from historical data to forecast the future

27
Q

Extrapolation: How it works

A
  • Identify trends, e.g., in sales.
  • Draw a line of best fit.
  • Continues the trends in blue (future) (EXTRAPOLATE).
  • Used to make predictions.
28
Q

Evaluating Extrapolation

A

Adv

  • Simple method of forecasting
  • Not much data required
  • Quick and cheap

Disadv

  • Unreliable if there are significant fluctuations in historical data
  • Assumes past trends will continue into the future. (Unlikely in the majority of competitive business environments)
  • Ignores qualitative factors (changes in taste/fashion)
29
Q

Elasticity

A

Elasticity measures the responsiveness of demand to a change in a relevant variable such as income/price

30
Q

Price elasticity of demand (PED)

A

Price elasticity of demand measures the extent to which the quantity of a product demanded is affected by a change in price.

Formula:

% change in quantity demanded
÷
% change in price

31
Q

Why is price of elasticity of demand important?

A
  • PED helps a business examine the likely impact of a change in price
  • If PED >1 (price elastic) then a change in price will cause a larger change in demand
  • This means overall revenues would increase if the price was reduced
  • But overall revenues would decrease if price increased
  • If PED <1 (price inelastic) the the opposite would happen
32
Q

Factors influencing PED

A

Brand strength: mostly price inelastic

Necessity: higher necessity = higher demand (inelastic)

Habit: demand and consumption are matter of habit (inelastic)

Substitutes: higher substitute choice (elastic)

Time: in a short run, price changes have less of an impact on demand

33
Q

Income Elasticity of Demand (YED)

A

Income Elasticity of demand measures the extent to which the quantity of a product demanded is affected by a change in income

Formula:

% change in quantity demanded
÷
%change in income

34
Q

Interpreting YED

A

Positive: (normal products)
- Rise in income correlates to a rise in demand and viceversa
- The extent of the change depends on necessity and luxury

Negative: (inferior goods)
- A rise in incomes decrease the demand as consumers switch to a better alternative

35
Q

Normal goods: Luxurious and Necessity

A

Luxurious:

  • Income Elasticity more than 1
  • More income = higher expense on luxury
    EXAMPLE
  • consumer goods, expensive holidays, branded goods

Necessity:

  • Income Elasticity less than 1 but more than 0
  • As income grows proportionally less is spent on necessities
    EXAMPLE
  • Staple groceries (milk), own lable goods
36
Q

The value of the concepts of price and income elasticity of demand to marketing decision makers

A
  • Elasticity provide useful insights for management and decision making
  • Firms tend to like products with inelastic demands
  • Building strong brands and product USP’s is a good strategy for making demand more price inelastic
  • It is difficult to get reliable data, especially in rapidly changing markets
  • Other factors such as customer tastes, also affect demand
  • Firms should be aware that competitor’s will react, price decisions cannot be isolated
37
Q

The use of data in marketing decision making and planning

A
  • Businesses use variety of tools to analyse marketing data and make forecasts
  • The key aim of interpreting data is to make reasonable assumptions to support marketing decision making
  • This information can help the business planning (e.g., resources) to meet demand
  • Data can also be used inform financial planning, such as sales forecast, costs and profits as well as cash flow forecast and break even
  • No technique is fully reliable

Business Unit 3&4 (1 decks)

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