Marketing Research - International University College, Sofia

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Transcript Marketing Research - International University College, Sofia

Market Information
& Analysis
Lecture 5
Karen Knibbs
Marketing Practice – U14210 S2 07/08
Lecture Objectives
By the end of the lecture, you should be able to:
Identify the typical types of information
which marketers would use
 Understand a range of methods of
collecting & measuring information
 Evaluate the significance of MR data to
marketing decision making
 Consider the case of Tesco’s use of
information
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Kotler & Keller (2006)
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‘Information is the competitive advantage that
drives success…just so long as the
information is appropriate and adequate and
we know how to use that information!
Competitors can copy and better equipment,
processes and products but they can’t
replicate the company’s information and
intellectual capital.’
MR in the Marketing Process
from last week…
MR information needed at all stages:
 new product idea generation and
product development
 marketing testing
 launch implementation
 brand performance management
 positioning and repositioning etc
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Why the need for metrics?

Corporate demand for accountability

Attempts to curb spiralling costs, longrange budgeting
• spend in advance of return (ROI) - ROM
• Legitimacy and credibility for marketers in
the eyes of senior managers
Discontent with traditional measures
 Enhanced availability of data due to
new technology and internet
infrastructure
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The value of intangible assets
“Today intangible assets are worth, on average, 69%
of the firm’s total market value as compared to 17%
in 1978 (Sawhney & Zabin, 2002). If marketing
expenditures are an investment, and the creation of
marketing are assets, then it is of utmost concern
that their assets be valued by metrics in use.”
Seggie, Cavusgil & Phelan (2007)
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Typical marketing data
How tangible are these data and how are they
collected / measured?
Market share
 Market growth
 Brand value
 ROI in M/ ROM: marketing
productivity
 Competitive Advantage

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Demand estimation

Estimation of market demand is essential for effective
marketing and as illustrated below, demand is
measured on a number of levels.
Kotler & Keller (2006): Ninety types of demand measurement (6  5  3)
Types of market

Potential market
• Consumers have some stated interest in a product or service.

Available market
• Set of consumers who have the interest, income and access to the product
or services.

Qualified available market
• Set of consumers who have the interest, income, access and qualifications
for a particular product or service.

Served or ‘target’ market
• Part of the qualified market that the company decides to pursue.

Penetrated market
• Set of consumers that have already bought a particular product or service.
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Measuring market demand
“The total market demand is the total
volume of a product or service that
would be bought by a defined
consumer group in a defined
geographic area, in a defined time
period in a defined marketing
environment under a defined level and
mix of industry marketing effort.”

Kotler & Keller (2006)
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Measuring market demand
Kotler & Keller (2006): Market demand
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Types of demand
The primary demand is the total
demand for all brands of product and
services (e.g. music downloads, MP3
players, mobile phones, laptops)
 The selective demand is a specific
demand for a given brand of product
(e.g. iTunes, iPod, iPhone, iMac etc.)
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Estimating market demand

Q= n x q x p

Where
• Q = total market demand
• n = number of buyers in the market
• q = quantity purchased by an average buyer
per year
• p = price of an average unit
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Forecasting future demand

Environmental forecast


Industry forecast


What is currently happening?
Company sales forecast
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Inflation, Unemployment, Interest rates,
Consumer spending and saving, Business
investment, Government expenditure.
Buyers’ intentions, Composite of sales force
opinions, Expert opinion.
Test market method.
Time series analysis, Leading indicators,
Statistical demand analysis, Information
analysis.
Qualitative & Quantitative data

Accounting (tangible) data
Based on actual, financial, quantifiable ‘fact’
 Typical historical then future projections /
forecasts / benchmarking
 If these are inaccurate, planning is futile

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Non-accounting (intangible) data
Tend to be qualitative & subjective in nature
 Considers long-run wealth creation & future
development
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Intangible metrics
Accounting measures: Non-accounting measures:
 Balanced scorecard
 Customer contribution
(Kaplan & Norton, 1992)
 EVA (economic value
 CE: customer equity
added) Stewart 1993

Where expenditures are
seen as future investments
instead of only current costs
• But financial measures must
also consider impact of
competitive actions
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(Blatberg & Deighton 1996,
Zeithaml & Lemon 2000)

CLV: customer lifetime
value (Jackson 1989, Jain
& Singh 2002)
Balanced Scorecard
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“Intangible assets”
Seggie, Cavusgil & Phelan (2007)
 Competitive advantage
 Knowledge, Networks
 Innovative capability
 Equity (brand-financial, brand-psychological,
relational & customer)
Plus:

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USP/differentiation, Positioning, Perception
Customer satisfaction, WOM recommendation
Behavioural intent, loyalty, perception
What to measure?: Products

Competitive advantage: “sustained
differentiation from rivals” (Barney 1991; Wernerfelt 1984)


Declines over time
Is context specific: to competitors and
uncontrollable environmental forces (PESTLE)
• For one company, could be in the form of price
premium, e.g. Jaguar, Ipod, Bang & Olufsen, Gucci
• Which can be used as a “measure of brand health &
brand equity” (Alawadi, Neslin & Lehmann 2003)
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What to measure?: Services

Tend to involve subjective measures

E.g. Customer satisfaction, loyalty, perception

But informational power of the Internet is making
objective attributes (i.e. company history, customer
recommendations etc., which appear as “factual”)
increasingly important, and brand loyalty is declining
(Bennett & Rundle-Thiele 2005)

Brand equity is now measured on future expectations
and “what have you done for me lately” consumer
philosophy, reducing brand halo effect
• E.g. Bank, Mobile network provider, Utilities, Fitness
centre
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Collection methods
Data capture (passive)
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ECR: electronic cash registers
Databases: data mining &
warehousing
CRM: micro monitoring of
customers
ERP software
Online purchases, accounts &
direct contact/feedback
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Data collection (active)
 Online surveys
 Consumer (internet)
panels
Shoppers upload info on
purchases

Mystery shoppers
Profit per customer interaction &
CLV
Looking
through
existing
customers?
Identifying
potential
customers?
Forecasting future demand
Kotler & Keller (2006) Common sales forecasting techniques
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Tesco’s – how much do they
know about you?
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Why are Tesco’s so nosey?
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Identification of segmentation profiles of various target
markets
Above added to typical purchase frequency, channel
choice (store or online), value of orders, best/worst
performing products/services (for category
management decisions), utilisation of sales
promotions and responses to direct communications
(past performance)
Identify opportunities to cross-sell, make changes
(future performance)
Global research
Business globalisation is increasing
the demand for accurate local and
regional information on the new
markets to be entered.
 Research needs to cover everything
from cultural issues to consumer
behaviour and competitive activity.
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Marketing research in small businesses and
non-profit organisations

Often limited by budgetary constraints, but
the following can be accomplished:
Observation of market, competitors and
industry
 Secondary data collection
 Surveys
 Experiments
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Summary
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Accurate information enables intelligent decision
making in pursuit of organisational objectives
Information must be continuously collected,
monitored, analysed and communicated all around
the organisation (via a MIS)
More information is necessarily helpful, but better use
and understanding of it to drive marketing decision
making is imperative
The internet is becoming a key information source for
businesses and consumers alike, but all must be
wary of the reliability and credibility of the data
Further reading suggestions
Kotler & Keller (2006) chapter 4, as per unit handbook.
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Chisnall (2004), Marketing Research, (7th Ed.), McGraw Hill.
Doyle, P (2000), Value Based Marketing, John Wiley.
Seggie, S., Cavusgil, E. & Phelan, S. (2007). Measurement of
return on marketing investment: A conceptual framework and
the future of marketing metrics. Industrial marketing
management. 36, 843-841.