Latent Class Analysis: Model & Segmentation

Instructor: Fred Hathaway

Fred has been a business consultant for over 20 years. His expertise includes marketing, human resources, and management.

Latent class analysis is a statistical modeling tool that is being used in marketing to create prospective customer segments for leading brands. Underlying (~'latent~') characteristics are identified for planning marketing campaigns. Read on to learn more.

Latent Class Analysis in a Real-World Application

Imagine you work in management for a cellular phone company, and you want to understand what factors are most important to your subscribers (and potential new subscribers). You may commission a market research study to get at unseen data that would support your marketing efforts.

A group in Australia did just that! In their study, the researchers hoped to identify segments of subscribers to whom they could market cellular services and devices. By sending out a questionnaire that was optimized for collecting independent responses, and applying latent class analysis (LCA) statistical modeling, they were able to isolate two market segments:

  • One segment of individuals was focused on keeping their monthly bill as low as possible.
  • A second segment was comfortable spending more money but didn't want surprises with their bills.

The survey respondents were grouped by two factors: monthly bill amount and attitudes about cellular use. Bill amounts were broken down into 11 categories (e.g., <$10/month, $10-19/month, $20-29/month...$200+/month) and attitudes into 7 categories (e.g. calls short and to the point, closely monitors time on phone, difficult to determine best deal, etc.). By looking at the correlation versus independence of bill amount in relation to attitudes, the market researchers were able to gain these insights:

  • There were two groups/segments.
  • Each segment had preferences that could become the basis for promoting cellular services to them.

So What Exactly Is LCA?

LCA is a data-driven method by which segments with multiple characteristics in common can be identified using an analysis of category variables. Within each market segment, each characteristic is seen as unrelated to the other characteristics (e.g., A segment of Millennial generation cell phone users may have consumers who enjoy podcasts, listen to Spotify, and use Instagram. Each activity is an independent characteristic, though any given consumer may express more than one characteristic.) If we were to take away the fact that the consumers in the segment are grouped together via LCA, the relationship between the consumers would appear to be random.

An important key to the LCA model is a calculation of the probability of response to an item or variable. Choosing the best variables to measure is very important to the process.

Segments are the overlap of characteristics

Why Is LCA Used in Marketing?

Market research seeks to understand why consumers choose one brand over another. In order to understand consumer choices, marketers must study market size (including segment size), theories for understanding the segments, and insights as to how the consumers make decisions regarding purchasing. These theories are validated through collecting data, analyzing the results, and then identifying what is unique or insightful about the members of a segment.

A market research team may use LCA to better understand attitudes held by portions ('segments' or 'niches') of survey respondents. Market researchers could also use demographic and preference data to set up buyer segments for improved targeting of marketing messages.

Additionally, latent class analysis is being used more and more often as a marketing theory validation tool. A marketer wanting to test her assumptions about a group of consumers may use LCA to test ('validate') theories prior to making a presentation to a boss about what she feels she knows about the target market.

What Else Can I Do with LCA?

Advanced users of LCA find it valuable under the following scenarios:

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