Psychographic Segmentation

Psychographic Segmentation

Quick definition

Psychographic segmentation is a marketing strategy that involves taking insights about somebody’s affinities or preferences – often based on both demographic and behavioral data points – and using those insights to create specific audience segments.

Key takeaways:

The following information was provided during an interview with Matt Skinner, senior product marketing manager for the Adobe Audience Manager and Adobe Real-time Customer Data Platform.

What is psychographic segmentation?

When is it best to use psychographic data?

When would you use psychographic segmentation over behavioral or demographic segmentation?

What are other uses for psychographic segmentation?

Are there other ways to gather psychographic data?

What are the drawbacks to using psychographic segmentation?

How do you categorize psychographic segments?

What will psychographic segmentation look like in the future?

What is psychographic segmentation?

Psychographic segmentation is separating a group of people based on their preferences and affinities of a particular subject.

The best way to understand psychographic segmentation is to learn about its cousins in market segmentation, demographic segmentation, and behavioral segmentation.

For instance, a psychographic segment might be women interested in sports. To create this segment, you take data points like a person’s gender (demographic) and the fact that they visited a sporting goods website (behavioral) and connect this data to form a market segment.

Marketers may try to gain specific data points with market research using things like surveys and focus groups. Or they might try to infer things based on other data points that they have available to them.

When is it best to use psychographic data?

Psychographic data is most valuable when you’re developing creative and brand messaging. For instance, a dish soap company wants to tailor their commercials to their largest target audience — parents with children and a busy schedule.

They would put huge amounts of research into that type of demographic to create a commercial that these types of consumers relate to.

This is where psychographic data is useful.

During qualitative research, if the dish soap company marketing team finds that busy parents want to reduce their dishwashing time while also making sure their dishes are clean, this important insight will inform what kind of commercial the dish soap company decides to broadcast for these target customers.

When would you use psychographic segmentation over behavioral or demographic segmentation?

Psychographic segmentation has a much higher strategic value in more competitive industries. Say there are two rival companies that both have access to similar behavioral data and demographic data.

Each company has an opportunity to differentiate by understanding their customers better than their rival. This is where psychographic segmentation is worth the investment because it becomes strategically important.

When behavioral and demographic data are similar, psychographic segmentation can be the tiebreaker.

Most popular brands have high affinity because they’ve taken the time to think about psychographic insights and what makes their brand likable, and how they can appeal to everyone.

Most likely, there is a feeling and emotion associated with that brand that they’ve taken the time to create using psychographic segmentation.

What are other uses for psychographic segmentation?

Psychographic data is important because it helps marketers and product developers figure out how to successfully appeal to a certain segment.

For example, a blue jeans company gains insights from a focus group that more of their younger customers prefer to wear yoga pants because they’re more comfortable than jeans.

The jeans company uses this behavioral data to figure out ways to make jeans more comfortable so that their younger audience will continue to buy their products.

What are the drawbacks to using psychographic segmentation?

One of the most common drawbacks with psychographic segmentation is making insights that are over-assumptions, not meaningful enough, or not relevant enough to be compelling.

For example, a B2B marketing agency is designing an ad campaign targeting an audience of web developers. Through marketing research, the agency discovers that a lot of web developers are also gamers.

The creative team builds a whole campaign about the agency’s web development software using video game imagery to appeal to gamers. But the ad campaign, though appealing to that demographic, alienates anybody that isn’t interested in video games.

This is why psychographic segmentation can be risky, because you’re making conclusions based on the data you have available.

The marketing agency was probably successful with a specific part of their target audience, but they alienated members of a broader audience that would also have been interested in their services.

How do you categorize psychographic segments?

There are no concrete ways to categorize psychographic segments. Most of the time, psychographic segments are based on preferences and interests.

You could have a psychographic segment like the women who are interested in sports, mentioned above. This is an example of affinity-based segmentation.

Affinities could also be toward actual goods, like luxury cars, or toward a certain brand. You could also have the opposite — things that people really dislike. Affinity-based segments help you understand what to avoid and what not to mention in your targeting.

How will psychographic segmentation look in the future?

There are a couple of exciting things to look forward to about psychographic segmentation.

For one, more opportunities are arising for consumers to express their preferences for how companies engage with them.

Consumers are becoming smarter — which means companies are developing more ways to collect psychographic  data  to make experiences more personalized. As consumers and companies become savvier about data, psychographic segmentation will be much more accurate.

Another thing to anticipate for the future is second-party data sharing: two organizations with a business relationship sharing customer data with each other — with customer consent, of course.

Second-party data sharing is most handy when one business doesn’t have great psychographic data, or they have an incomplete view of customer data in general, but their business partner has access to data that augments what they already know.

For example, say you move to a new neighborhood. You might get a bunch of mail offers and coupons from companies welcoming you to that area.

A home goods store might send you an offer for 20% off at their store, which would certainly come in handy when moving into a new home.

But the home goods store doesn’t know that you’re new just off-hand — they got that information from the town’s data.

This type of relationship — sharing data between businesses and institutions with customer consent — is another good way to build richer psychographic profiles.

And with emerging technology, this relationship can be much more optimized for highly tailored  customer experiences.

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