2. SEGMENTATION & TARGETING

https://hbr.org/product/marketing-reading-segmentation-and-targeting/8219HB-HTM-ENG

Segmentation: group customers based on similar needs, and determine the characteristics of customers in thoses segments

Targeting: asses attractiveness of each segment, and select segments that the firm wants to fucus on for its products or services

Positioning: formulate the firm's value proposition for target segments

1. SEGMENTATION

(withour segmentation, firms will often overlook opportunities as they continue to provide a single solution for everybody)

segmentation rules:

1. identifiable: organization can identify customers in each segment and measure their characteristics

2. substantial: large enough for a firm to serve profitably

3. accessible: a segment needs to be reached through communication and distribution channels 

4. stable: a segment should be stable over a long enough period of time 

5. differentiable: consumers in a segment should have similar needs, which should differ from needs in other segments

6. actionable:organization should be able to create products and mkt programs for acctrating and serving customers

how to segment:

bases for segmentation

2. TARGETING

one to one marketing----mass customization----mass production

how to select target segment:

niche strategy----one segment and expand in adjacent segments----multiple segments----all segment

from targeting to strategy fromation:

-product strategy

-price strategy

-communication strategy

-salesforce and channel strategy

-crm strategy

3. analytical tools to identify customer segments

a. cluster analysis: 

group customers based on a set of variables so that customers in one group are similar to each other but are different from customers in another group. 

b. preference-based segmentation

1)multiattribute model: explicitly asks consumers about their preferences for a variety of attributes that a manager may consider relevant for their purchase decision.

2) conjoint analysis:  works around this problem by forcing consumers to make tradeoffs between several pairs of products that differ on a carefully designed combination of attributes.

c. response-based segmentation:

if we have a large data series for each consumer that would allow us to run a statistical analysis, such as regression analysis, to infer each individual consumer’s price sensitivity, which in turn can be used as a variable in a cluster analysis for segmentation.