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Method of grouping customers or consumers such that they are similar to one another and when faced with a certain purchase decision may develop similar stories or behave similarly.

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Grouping Customers by age, income, location, family size ( e.g DINKs)

In India, marketers use a classification called Socioeconomic classification (SEC) for families, which is combination of their education and occupation of the earning member of the family.

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Demographic Segmentation Example: Tier 1 and Tier 2 Cities in India

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Demographic Segmentation Example: Tier 1 and Tier 2 Cities in India

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The aspirations of youth and Tier 1 and Tier 2 Cities are similar

But their psychographics and behaviour may be very different. For e.g. Youth in tier 2 towns may be more value conscious. They may be using shared phones at home and hence are able to access the e-commerce websites a few times a day

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Psychographic segmentation groups customers based on their personal beliefs on how they should lead their, their personal preferences like and dislikes.

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Behavioural Segmentation is based on actual interactions and engagements with various channels, actual usage of products, referrals and recommendations to customers, writing reviews, complaints behavior.

Example: Based on customer's behaviour on e-commerce product pages - marketers may classify customers as heavy readers ( spend a lot of time on each page),

light readers ( spend less time on each page),

constant browsers ( see many products),

Specific browser ( see a few products)

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Inspiring People to Change Their Behavior through FUN

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Based on type of e-mail subject lines that customers open email, read e-mail, click on e-mail, marketers can send more relevant messages to customers and there is a higher probability that customers will respond.

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Examples of behavioral data on mobile apps or website include website/app views, product page views, newsletter sign-ups, visiting a blog, adding an item to a shopping cart, creating an account on your site, liking a social media post, and downloading an app. These interactions can be processed and evaluated to reveal why customers do certain things.