To increase our marketing effectiveness, we employ segmentation to tailor messages to different target groups. Understanding our customers goes beyond mere demographics like age, gender, and location. To truly connect with and influence an audience, we need to delve deeper into their psychological profiles—this is where psychographic segmentation comes into play.
What is Psychographic Segmentation?
Psychographic segmentation groups audiences based on psychological factors, such as their personality, lifestyle, hobbies and interests, attitudes, goals, and social class.
While behavioral segmentation looks at what people do, psychographic segmentation analyzes why they behave like they do. This allows us to gain deeper insights into our audience. Another difference is that behavioral segmentation usually makes use of quantitative data and psychographic segmentation focuses on qualitative data. By combining the two we can get a holistic view of our target group.
Factors in Psychographic Segmentation
- Lifestyle: How people spend their time and money. Also gives an idea about their interests and hobbies
- Attitudes: An individual’s preferences, for example regarding game genres
- Goals: What motivates them? For example, completing challenges or winning against others.
- Personality: For instance, captured by the “Big Five”
- openness to experience (inventive/curious vs. consistent/cautious)
- conscientiousness (efficient/organized vs. extravagant/careless)
- extraversion (energetic vs. reserved)
- agreeableness (friendly/compassionate vs. critical/judgmental)
- neuroticism (sensitive/nervous vs. resilient/confident)
- Social class: Purchasing power
Psychographic segmentation considers a person as a whole and isn’t limited to their in-game personality (e.g. Bartle’s player types). This paints a much broader picture we can use to acquire, retain, and monetize users.
Benefits of Psychographic Segmentation
By understanding why people act like they do, what their goals are, and how they think, we can better predict their future behavior. Moreover, we can use the insights to cater our value proposition and messaging to them.
Higher conversion rates
We can utilize psychographic data points to inform our messaging. By relating to people’s lifestyles (e.g. mom with a small child working part-time), goals (e.g. finding more time to relax), and values (e.g. tycoon game with an ecological sustainability theme), we can increase the chances that users click on an ad and download our game.
Higher ARPU
When players can relate to our game, that also makes them more likely to spend money. And by utilizing social class and spending patterns as data points, we can estimate the customer lifetime value of a user segment and optimize for high spenders.
Better products
Deep psychographic insights can also help inspire new product features. What features are needed so users can achieve their goals? Which features should we prioritize based on our users’ personalities (e.g. extroverted users may like social features)?
How to Create Psychographic Segmentation
Collected data
We can use in-game data to extrapolate psychographic information. For example, our players’ spending patterns can give hints about their social class. Or how they use features showcases their personality (e.g. are they competitive or cooperative).
Surveys and interviews
We can conduct primary market research by directly talking to our users. This allows us to capture granular data specific to our product and its user base.
Challenge: People usually have problems with introspection. Here, ethnographic studies can help where we directly observe users.
Community managers
An important bridge to our users are the community managers. They engage with players, their problems, and their wishes every day. Therefore, it’s key to gather insights from their experiences with users.
Studies
Bolster your segments with secondary research. For instance, get psychographic information for players within your genre or from competitor games.
Tip: As always, segments have to be meaningful. Users within a segment should be homogeneous (similar). Users from different segments should be heterogeneous (different from one another).
Psychographic Segmentation Data in Web3
Blockchains allow us to collect additional, verifiable, public data about users. When embedded into, for example, a questing system that requires linking wallets and social accounts together, we can quickly build out holistic segments utilizing social, in-game, onchain, and offchain data. For instance, wallet values can signal a user’s social class.
Degens
Users who like to speculate. We can identify them by their onchain footprint, for example, trading memecoins. To cater to this segment, we can add financial meta layers to our game, such as wager game modes.
Investor-types
These are not necessarily engaged players themselves but they add value to the game economy in other ways. Usually, these are higher social classes with limited leisure time but a high interest in gaming as a business.
In conclusion, psychographic segmentation can help to provide more depth to player personas by answering why users behave like they do, allowing game studios to fine-tune their messaging and features. Web3 is an interesting playground for psychographic segmentation as new player types emerge which can be best understood by looking deeper into their personality and lifestyle outside of games. Therefore, we suggest combining Helika’s behavioral data with qualitative user interviews and experiences from community managers to create holistic player personas.
