3.3 decision making to improve marketing performance

• Marketing objectives


  The process of identifying, anticipating (predicting), and satisfying customer needs profitably
• Effective marketing objectives


  • Ensure functional activities consistent with corporate objectives
  • Provide a focus for marketing decision-making and effort
  • Provide incentives for marketing team and a measure of success/failure
  • Establish priorities for marketing resources and effort

  
• Types of marketing objectives


  • Sales volume
  • Sales value (revenue)
  • Market growth (%)
  • Market share (%)
  • Brand loyalty/awareness
• External influences on marketing objectives and decisions


  • Economic environment
  • Competitor actions
  • Market dynamics
  • Technological change
  • Social and political change
• Internal influences on marketing objectives and decisions


  • Corporate objectives
  • Finance
  • Human resources
  • Operational issues
  • Business culture
• Primary market research


  Involves the collection of first hand data that did not exist before and therefore it is original data
• Primary research methods


  • Focus groups
  • Interviews (online & in-person)
  • Surveys & questionnaires
  • Mystery shoppers
  • Product testing and product trial
• Advantages of primary research


  • Directly focused on research objectives = fit for purpose
  • Tends to be more up-to-date than secondary research
  • Provides more detailed insights – particularly into customer views
• Disadvantages of primary research


  • Time-consuming and often costly to obtain
  • Risk of survey bias – research samples may not be representative of the population
• Secondary market research


  Research that has already been undertaken by another organisation and therefore already exists
• Sources of secondary research


  • Government publications
  • Newspapers
  • Magazines
  • Company records
  • Competitors
  • Market research organisation
  • Loyalty cards
  • Internet
• Advantages of secondary research


  • Already gathered so may be quicker to collect
  • May be gathered on a much larger scale than possible for the firm
  • In some cases it can be very cheap or free to access
• Disadvantages of secondary research

  • Information may be outdated, therefore inaccurate
  • The data may be biased and it is hard to know if the information was collected is accurate
  • The data was not gathered for the specific purpose the firm needs or is not relevant to the original context
  • In some cases it can be costly (e.g. marketing firm reports)
• Market mapping


  A framework for analysing market positioning is a 'market (positioning) map'. A market map illustrates the range of positions that a product can take in a market based on two dimensions that are important to customers
• Dimensions for the axes


  • Low price v high price
  • Basic quality v high quality
  • Low volume v high volume
  • Necessity v luxury
  • Light v heavy
  • Simple v complex
  • Unhealthy v healthy
  • Low-tech v hi-tech
• Advantages of positioning maps


  • Help spot gaps in the market
  • Useful for analysing competitors – where are their products positioned?
  • Encourages use of market research
• Disadvantages of positioning maps


  • Just because there is a gap in the market doesn't mean there is demand for the product
  • Not a guarantee of success
  • How reliable is the market research that maps the position of existing products based on the chosen dimensions?
• Sampling


  Involves gathering data from respondents whose views or behaviours are representative of the target market as a whole
• Types of sampling


  • Random = member of target population has an equal chance of being chosen
  • Quota/Stratified = based on obtaining a sample that reflects the types of consumers from whom the business wished to gain information (e.g. gender, age)
• Advantages of sampling


  • Provides a good indication
  • Helps avoid expensive errors
  • Can be used flexibly
  • Reliable information
  • Helps firms learn about the market quickly
• Disadvantages of sampling


  • May be unrepresentative
  • Bias
  • Difficult to locate suitable correspondents
  • May not have an accurate profile of customers
  • Can be out of date due to time taken to collate
• Confidence intervals


  They measure the probability that a population parameter will fall between two set values. The confidence interval can take any number of probabilities, with the most common being 95% or 99%
• Factors influencing confidence levels


  • Sampling size – the larger the sample, the better the reflection of opinion of the whole population, so confidence levels fall
  • Population size – the target market for the product has a minor effect on confidence intervals
  • % of sampling choosing a particular answer – if high or low % of sample expresses the same opinion, then confidence intervals are likely to be low
• Extrapolation


  It is like an educated guess or a hypothesis. When you make an extrapolation, you take facts and observations about a present or known situation and use them to make a prediction about what might eventually happen
• Disadvantages of extrapolation


  • Less reliable if fluctuations occur (e.g. weather is unpredictable)
  • Assumes past changes will continue
  • Ignores qualitative factors (e.g. changes in tastes and fashion)
  • Ignores the product life cycle
• Correlations


  Another method of sales forecasting that looks at the strength of a relationship between two variables. Positive correlations means the two sets of data are connected in some way. Negative correlations also means the two sets of data are related but as x increases, y decreases
• Big data


  The process of collecting and analysing large data sets from traditional and digital sources to identify trends and patterns that can be used in decision-making
• How big data is generated


  • Retail e-commerce databases
  • User-interactions with websites and mobile apps
  • Usage of logistics, transportation systems, financial and health care
  • Social media data
  • Location data (e.g. GPS-generated)
  • Internet of Things (IoT) data generated
  • New forms of scientific data (e.g. human genome analysis)
• How technology enables more effective marketing decisions


  • Analytics and customer insights
  • Dynamic pricing
  • Audience reach and segmentation
  • Customer relationship management (CRM)
  • Campaign testing
  • Competitor analysis

  
• Price elasticity of demand (PED)

  Measures the responsiveness of quantity demanded for a product to a change in price. It is calculated as the percentage change in quantity demanded divided by the percentage change in price
• What firms use PED to predict


  • The effect of a change in price on the total revenue and expenditure on a product
  • The likely price volatility in a market following changes in supply
  • The effect of a change in an indirect tax on price and quantity demanded
  • Information on the PED can be used by a business as part of a policy of price discrimination
  • How responsive customer demand will be to pricing tactics used
• Values of PED


  • If PED = 0 demand is perfectly inelastic
  • If PED is between 0 and 1 demand is inelastic
  • If PED = 1 demand is unit elastic
  • If PED > 1 demand is elastic
• Factors affecting PED


  • The number of close substitutes for a good
  • The cost of switching between products
  • The degree of necessity or whether the good is a luxury
  • The % of a consumer's income allocated to spending on the good
  • The time period allowed following a price change
  • Whether the good is subject to habitual consumption
  • Peak and off-peak demand
  • The breadth of definition of a good or service
• Income elasticity of demand (YED)


  Measures the relationship between a change in quantity demanded for good 'X' and a change in real income. It is calculated as the percentage change in demand divided by the percentage change in income
• Most products have a positive income elasticity of demand – so as consumers' income rises more is demanded at each price
• Price elasticity of demand


  The degree to which the quantity demanded of a good responds to a change in its price
• The longer the time period allowed following a price change, the more price elastic demand tends to be
• Habitual consumption


  When a consumer becomes less sensitive to the price of a good because their default position is to buy the same products at regular intervals
• Demand tends to be price inelastic at peak times and more elastic at off-peak times
• Breadth of definition of a good or service

  If a good is broadly defined, demand is often inelastic, but specific brands are likely to be more elastic following a price change