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.
