Analysis

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Analysis Decision Making in Marketingintroducto
ry notes

• Learning objectives and contents
• Prerequisite for the MgtSc Lab
• Course Lecture
• Individual preparation of reading assignments
  (there is one textbook)
• Presentations and classroom discussion
• Exercises and groupwork
• Assessment
• 3/4 individual (quizzes), 1/4 groupwork
• Check your bonus points at Learn.WU-wien.ac.at

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How to Use the Slides

• Slides assist in
• - explaining concepts during class
• - guiding classroom discussion
• - preparing for each class headwords provided on
  the slides indicate issues of relevance
  marks extensions.
• Students produce their own slide shows when
  making group presentations.

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Chapter 1 M. Engineering, Models

• Why marketing engineering?
• marketing models
• verbal, graphical, mathematical
• descriptive (predictive), normative, intuitive
• benefits decision options, relative impact of
  variables, group decisions, subjective mental
  models, opportunity costs, precision, analysis
• My statistics expert is responsible ...
• He or she is going to take over your job!

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Chapter 2 Market Response Models

• Why market reponse models?
• inputs, response/output, objectives, black box
  versus structural models aggregated vs.
  disaggregated
• model components calibration
• simple phenomena P1 P8, stylized facts
• linear polynomial (power series) potency
  (fractional root) semi-logarithmic
  exponential modified exponential (saturation-)
  logistic Gompertz - ADBUDG

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Chapter 2 Calibration

• objective subjective calibration
• Y a bX
• sales share a badvertising share
• R2 goodness-of-fit, variance explained
• decision calculus gt ADBUDG, judgmental data,
  learning by trial error

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Chapter 2 Objectives

• dependent vars, marketing objectives
• fixed discretionary cost
• short-term, long-term profit
• uncertainty risk aversion
• certainty monetary equivalent Sicherheitsäquiv.
• risk premium Risikoprämieaverage gain-CME
• multiple goals conflicting objectives?
• constraints Nebenbedingungen

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Chapter 2 Multiple Marketing-Mix Elements

• interactions
• full-linear Y a bX1 cX2 dX1X2
• multiplicative Y a X1b X2c
• dynamic effects
• carry-over, delayed response, customer-holdover
  gt customer retention (decay, erosion) rate
• sales in t a b advertising in t ? sales
  in t-1
• sales in t-1 a b advertising in t-1 ?
• sales in t-2

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Chapter 2 Market Share, Competition

• unit sales unit share market volume (of the
  product class in units)
• dollar share, share of buyers
• attraction model Mi Ai / (A1A2An)
• attraction total marketing effort
• market product class gt market volume,
  substitution, competition and market share

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Chapter 2 Individual Customer Level

• scanner data, consumer panels, bar-code scanners
  brand choice store and personal data
• purchase probability Pij exp(Ai) / ? j exp(Aj)
• Aj ?k wkbijk
• multinomial logit model (MNL)
• proportional draw assumption
• gt nested logit model

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Chapter 2 Qualitative Models

• shared experience best practice, PIMS and
  ADVISOR
• rule-based representations, expert systems,
• AI tools
• model selection
• gt visual response modeling, Conglomerate Case
  Excel Solver

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Chapter 5 Strategic Market Analysis I

• corporate strategy gt ...gt marketing objectives
• strategic instrumental planning
• overcome limitations
• improper analytic focus, functional isolation,
  ignoring synergy, short-run analysis, ignoring
  competition, ignoring interactions, lack of an
  integrated view, ...

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Chapter 5 Strategic Market Analysis II

• market demand trend analysis - forecasting
  methods
• judgmental, experts
• market product analysis demoskopische ...
• time-series analysis, univariate
• causal, multivariate
• which? when?

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Chapter 5 Strategic Market Analysis III

• the product life cycle concept
• which variable(s) to observe
• stages
• descriptive, predictive, a forecasting tool?
• consequences
• scale effects
• experience effects, the learning curve
• marketing consequences?

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Not in the textbook Discriminant analysis I

• Discriminant value for case i zi b0 b1 x1i
  ... bn xni
• Mean of zi in group 1 Z1
• Mean of zi in group 2 Z2
• Std.dev. sZ1 und sZ2
• Optimization criterion
• (Z1 - Z2 )2
• _______________ ? Max!
• sZ12 sZ2 2
• _

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Not in the textbook Discriminant analysis II

• Separate the groups at Zkrit
• Z1 Z2
• Zkrit
• 2
• Zi lt Zkrit gt group 1
• Zi gt Zkrit gt group 2

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Not in the textbook Discriminant analysis III

• Test with the classification matrix
• (Vacation trip made during the past 12 months
  yes/no)
• forecasted behavior
• no yes
• no 1496 (66) 786 (34) 2282
• observed
• behavior yes 688 (30) 1622 (70) 2310
• --------------------------------------------------
  ------------------------
• 2184 2408 4592
• correct (14961622)/45.92 68

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Not in the textbook Discriminant analysis I

• Compare with a random classification
• e.g. 30 travelers, 70 non-, p .30
• maximal chance criterion Cmax
• max(p, 1-p) .70
• proportional chance Cpro
• p2 (1-p)2 .58

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Chapter 6 Models for Strategic Marketing
Decision Making

• market entry / exit decisions original vs.
  reformulated products
• a decision tree for problem structuring
• the PIMS project, ROI, ROS, PAR, LIM and other
  mysteries
• profit influences

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Chapter 3 Segmentation Targeting I

• m. segment, m. segmentation, target market
• segm. theory practice -- the STP approach
• segmentation criteria ...
• a priori versus a posteriori segmentation
• practical implementation (phases 1-5)
• example benefit segmentation
• PBMS, segmentation strategies

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more on Segmentation Targeting I
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more on Segmentation II

• A-priori
• marketing objective defines the segments (e.g.
  loyal customers)
• search for correlates (crosstabulation,
  AID/CHAID, DA, ...)

• A-posteriori
• heterogeneity hypothesis (e.g. regarding benefits
  sought)
• create the segments (cluster analysis,
  neurocomputing)
• search for correlates (same as in a-priori s.)

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more on Segmentation IIIanalytical tools

• A-priori
• contingency tables, crosstabs, mult- response
• Automatic Interaction Detector (AID/CHAID)
• discriminant analysis (DA)

• A-posteriori
• partitioning clustering (e.g. K-means)
• vector quantization (SOM, TRN/DTRN)
• testing with DA
• hierarchical clustering

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more on Segmentation IVa new a-posteriori
segmentation philosophy

• There are naturally predetermined segments.
• The marketing analyst should identify them.
• The manager should assess them in terms of
  potential target groups.

• The marketing manager does not find segments, he
  creates them.
• Creating segments and customer types becomes a
  means of competitive strategy.

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more on Segmentation Vneurocomputing methods I
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neurocomputing methods II competitive
(un)learning in the TRN
data point
prototype
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Chapter 4 Positioning I

• perceptual maps

Ease Comfort /
MyBrand
NewBrand
Scope, Functionality /
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Chapter 4 Positioning II

• perceptual maps extensions

Ease Comfort /
IdealPointSegment1
MyBrand
IdealPointSegment2
NewBrand
Scope, Functionality /
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Chapter 4 Positioning III

• perceptual maps more extensions

Ease Comfort /
IP1
IP2
Scope, Functionality /
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Chapter 4 Positioning IV
1 2 j m
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Chapter 4 Positioning V
challenging
adventure

o




o






exciting






o


o
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Chapter 7 NPD-New Product Decisions I

• core / tangible / augmented product
• stages in the NPD process
• NPD models
• identifying opportunities
• generating ideas
• evaluating ideas
• product design
• NP forecasting and testing

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Chapter 7 NPD-New Product Decisions II

• principles of conjoint analysis
• overall preference gt part-worths (utility
  values)
• product bundle of attributes not directly
  evaluated
• advantages ?
• limitations ?
• example
• levels nr of attributes combinations 34 x 4
  324
• experimental design gt selected combinations
• part-worths gt ideal products

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more on conjoint analysis a Euro pricing
example I

• capture consumer heterogeneity with
• explanatory variables and a random coefficient
  model
• Euro confidence and
• Euro scepticism (reversed scale)
• mitigate the negative effect of bothersome
  conversion on the factors currency and price

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more on conjoint analysisEuro pricing II
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Chapter 9 Salesforce Channel Decisions I

• personal selling
• selective marketing effort, customized, people,
  costs
• functions performed by salespeople ...
• managing the salesforce
• organization own vs. commission-based
• sizing / allocation intuitive (which ?) vs.
  model-based procedures
• control compensation schemes

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Chapter 9 Salesforce Channel Decisions II

• strategy direct vs. Indirect selling
• location outlet, franchise system, mediators ...
  macro micro (GIS-geoinformation systems)
• logistics physical distribution, inventory
• gravity model
• pij Vij / ?N Vin , Vij S?j / D?in
• A (M1 M2) / D2

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Chapter 9 Salesforce Channel Decisions III

• gravity model ... steps (SCAN/US)
• geographic area gt zones
• data on competing stores
• store-zone distances
• calibration, sales potential gt shares
• locations for new store choice
• limitations IIA assumption, mode of access, ...
  interactive marketing (online shopping)

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Chapter 10 Price Sales Promotion Decisions

• Why is price involved in all these terms?
• profit (unit price unit cost) x quantity sold
• ? (?q/?p) (p/q), lt 1.0, gt 1.0 ?
• cross-price elasticities show ...
• TR pq gt ?TR/?q p q (?p/?q)
• isoelasticities q a bp, q ap-b
• limitations ... how do customers interpret price
  changes ... (examples)

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Chapter 10 Pricing in Practice

• cost-oriented
• criticism, constant marginal cost, constant ?
• demand-oriented
• criticism, value-in-use concept
• reservation price, Preisbereitschaft
• competition-oriented
• web economy auctions and bidding
• yield management

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Chapter 10 Price Discrimination

• heterogeneous, segmented markets gt consumer
  surplus
• practical difficulties gt differentiate prices
  with regard to what?
• examples
• geographical price differentiation
• grey markets, Euro introduction, online shopping
• temporal price differentiation, skimming policy

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Chapter 10 Sales Promotions I

• temporary advertised price reductions
• types of SP, targeted to whom?
• complementary effects
• communication incentive invitation
• typical marketing objectives ...
• (cross-)couponing, cross-merchandising,
• sampling, manufacturer price-off, premium offers,
  in-store displays, feature adv., deals
• examples ...

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Chapter 10 Sales Promotions II

• recommendations
• sales impact
• large share brands
• wear-out effect
• asymmetrische cross-promotion
• store traffic
• complementary and substitutional products
• problems of measuring effectiveness

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Chapter 8 Advertising Communications Decisions
I

• communications mix
• advertising, PR, SP, PS, DM, HR
• links within the marketing mix
• decisions within advertising planning
• which?
• interdependencies show in chart
• advertising effectiveness
• response shape, dynamics, interaction

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Chapter 8 Advertising Communications Decisions
II

• advertising dose/intensity (frequency)
• learning and forgetting curves (decay)
• effectiveness thresholds, saturation,
  reactance
• creating advertisements (copy effects)
• formal design elements
• measures (recognition, recall, ...)
• pretesting, copy tests, advertising research lab
• psychophysical instruments ...

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Chapter 8 Advertising Communications Decisions
III

• advertising budget decisions
• traditional rules
• all you can afford
• percentage of sales
• competitive parity
• objective and task
• model-based gt e.g. Adbudg optimization

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Chapter 8 Advertising Communications Decisions
IV

• Media planning (media decisions)
• ratios gross rating points Kontaktsumme,
  reach Netto-Reichweite, frequency mittl.
  Kontaktdosis, impact combined and cumulative
  reach
• cost per 1000 readers, or per 1000 exposures
  Media-Analyse, Streuplan-evaluierung, media
  optimization model
• Planning the message content gt hierarchy

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Chapter 8 Advertising Communications Decisions
V

• creative quality, copy prettesting
• Starch measures noted, seen-associated,
  read-most
• text analysis
• advertising design
• expert systems (ADCAD) rule base, inference
  machine limitations
• What to include in a briefing for creative
  content?