AMM-MKT (Segmentation (Cluster analysis (Procedures
Select variables for…
- Customers segment with similar characteristics are likely to respond in the same way
- Firms cannot serve all segments efficiently or with the same offer
- Better resource allocation
- Better matching of customer needs
Benefits: better matching for customer needs
- improved customer acquisition and retention
- enhanced opportunities for growth
- focused marketing effort
- better communication
- increase profitability
Variables used for segmentation
- Model/ Statistical
Cluster/ Factor/ Conjoint analysis, Latent class, any technique that allows classification
expert opinion, managerially relevant
- Select variables for analysis
- Define measure of similarity
- Identify groups of customers with similar needs.
- Select the number of segments
- Profile the needs of the selected segments
- flexible and applied to large datasets
- less affected by outliers and irrelevant clustering variables
- need to pre-specify the number of clusters, which can be determined by hierarchical procedure
Tool: Perceptual maps
- Familiarity (with product or brands) ratings
- Proximity judgments (between products or brands)
- Attribute ratings for each stimulus (e.g. product or brand)
- Preference (brands) ratings
- Demographics and attitudinal data from respondents
how similar are brands X and Y?
- No specific attributes are stated
Questions (1,2,4 are also position statement):
- Who are our customers?
- What is our offer?
- With whom do we compete?
- How are we compared to our competitors?
- Points of Parity: must haves
- Points of Differentiation
. Product attributes
. Service factors
- Vertical / Competition-Based: more/ smaller
- Horizontal Customer-based: different / lifestyle
Emphasize need or category
- Which positions are of greatest value to our target customers?
- Which of these positions are “taken,” and relatively free of competition?
- Which of the available positions fits best with our objectives
and our distinctive capabilities, i.e., can we back up the chosen
positioning by demonstrable product attributes or benefits?
- Can we “change the rules” of the game by discovering new
critical points of differentiation?
- Are all our positioning messages consistent?
- evaluates whole potential product profiles,
- rather than ask respondents directly about preference or importance on each attribute
- design of new product
- what features and attributes contribute
to consumers’ preferences
- could be used as complement of position
- not main purpose: calculate market share
Help us to learn:
- tradeoffs among product attributes
- most important features
- What values of those features are optimal (Optimal combination)?
Target market selection
Market opportunities (customer)
- segment size
- growth rate/ potential
- competitors' strengths
- competitive intensity
Company "Fit" with
- customer base