If you want to understand, group and profile your customers based on similarities, demographic clustering is an option for you to consider. After all, using the information gathered through this clustering technique can help you to provide the right products at the right price, place and time. But how can you use it to generate insights from their characteristics and purchasing patterns? And especially to enhance customer loyalty?
What are demographics?
Demographic characteristics describe your target market on an individual level. You can use these attributes to characterise each individual without considering personality traits. Demographic factors such as age, income and level of education provide insights about the consumer behaviour of your target market. You can also use it within your marketing and inventory management functions.
Collected as statistical data, you can use demographic information to make strategic decisions. These traits describe the product preferences and purchasing patterns of your shoppers and are useful if your business lacks a large amount of market-related data. You can use this information to target these market segments through demographic clustering to maximise your return on investment and business profits.
As for how to access this information, you can do that through surveys, census data or through loyalty data. It is important to collect as much information as possible to understand your customers and develop a competitive advantage.
Millennials, Generation Z and baby boomers. It is important to understand the age of your consumers because each will belong to a generational cohort. Each generation will have different levels of disposable income, buying habits and propensity to spend on certain products. Your customers also have different needs and preferences at different life stages that need to be considered by your business.
Gender influences shopper behaviour. For example, it is generally accepted that women are more likely to enjoy the shopping process, make impulse purchases and sign up for loyalty programs. On the other hand, men are more likely to shop quickly and with purpose. They are also more willing to try multiple brands until they find the right product for them.
However, this is not true in all cases and outliers will need to be identified and considered in your demographic clustering process. Your business needs to consider gender when profiling your demographic clusters because this factor influences consumer needs and decision-making.
Understanding the monthly household income of your demographic clusters is important. This is valuable because you need to ensure they are willing to purchase and can afford your product.
During research and development, this will also help you to design a product that suits your target market because you will have information about their spending power. When you understand the income of your customers, you can create products that support them spending at the high and lower end of the market.
For example, high-income consumers are more likely to purchase luxury items that improve their lifestyle. On the other hand, low-income consumers are more likely to purchase products that are necessities.
Level of education
The level of education of your consumers will influence their income as well as their decision-making process.
For example, shoppers with higher levels of education are more likely to have higher incomes, busier lifestyles, higher expenses but also increased disposable income. These consumers are more likely to be drawn to products that support convenience, good nutrition, great quality and status.
The geographic location of your demographic clusters will influence the product preferences of your target market as well as the availability of certain products. Certain geographic areas are associated with specific income groups, cultural groups and logistic accessibility. This means that consumers in specific regions may only be able to afford, choose to purchase or be able to access specific products.
Family size and composition
The number of people in each household, as well as the presence of particular age groups such as children or elderly consumers, will influence the needs and products purchased by each demographic cluster. Family size and composition influences shopper basket size as well as product selection and must be considered when you create a product assortment for each cluster.
Ethnicity and cultural group
The ethnicity and cultural group of your consumers will determine which products you need to carry in your assortment. The propensity of your consumers to spend on certain product categories as well as overall product selection is influenced by their ethnicity and/or culture.
While demographics describe who your customer is, psychographics describe why they make purchase decisions. The buying habits, hobbies, purchasing patterns, lifestyle, values, attitudes and opinions are used to understand demographics on a deeper level.
An understanding of both demographics and psychographics will help you to effectively target your market segments and build cluster profiles. An in-depth understanding of psychographic variables can also be linked to behavioural segmentation.
What is demographic clustering?
Demographic clustering uses loyalty data to group consumers based on the demographic similarities between them. You can conduct this type of clustering on a basic level with just shopper data or you can include store and category-level information to group your stores together based on demographics for a particular product category. You should consider this approach if your product assortment will appeal to a specific demographic group of consumers. This approach may also be useful if you would like to understand your target market and optimise your inventory and marketing management based on this knowledge.
Demographic variables are discrete and therefore, an unsupervised clustering algorithm such as partition-based (k-means) or hierarchical (agglomerative or divisive) would be useful. Although you may need to measure statistical significance to establish a link between product preferences and demographic factors, there are numerous benefits to this clustering method.
When you conduct demographic clustering, your buyers can create a product assortment tailored to each shopper segment. Pricing and marketing strategies will be more targeted and effective, resulting in an overall decrease in capital loss and increase in ROI. This method may also assist you with product development and increase the market success rate of new releases.
How to set demographic clustering parameters
Once you have selected the clustering algorithm and method which in this case would be demographic clustering, you will need to specify your clustering parameters. In the case of these parameters, it’s best practice to consider all of them.
The similarity threshold is the lowest limit for the similarity between two data points or consumers that belong to the same cluster. You should set the similarity threshold according to the number of clusters you would like created as well as the environment in which your business operates.
If you set the similarity threshold to 0.1, for example, then data points that are less than 10% similar are unlikely to be assigned to the same cluster. This ensures that consumers that are assigned to the same cluster are very similar and dissimilar to customers in different clusters.
Similarity scale and matrices
You’d use a similarity scale to specify how you’d calculate the similarities between specific demographic variables. You may need to create a similarity matrix where you would manually specify the similarities between demographic variables.
Certain demographic characteristics may be more important to your business than others. You can give these values a higher weighted value to detect the overall similarity between your customers.
How does demographic clustering help you to understand your customers?
As mentioned previously, demographic clustering can help you to understand your target market. It will help you to plan the next moves for your business. For example, it can help you to decide which new products to develop, where to open a new store or which market segments to target. Clustering will give also your business strategic direction and an insight into your customers that your competitors may not have.
You can use demographic clustering to segment your customers into profiled groups. You can describe each cluster according to demographic variables as well as their purchasing patterns, basket composition, and overall consumer behaviour.
You can use this information to create a targeted range of products and shopping experience to increase the profits of your business.
Marketing strategies will also be more effective due to the in-depth understanding of the target market and their reaction to particular types of advertising media.
Preventing capital loss
Understanding your consumers through demographic clustering will help you to eliminate costly mistakes in the areas of assortment planning, marketing and product development. Since the needs of your shoppers are known you can remove unsuccessful and ineffective products and strategies to prevent the loss of revenue.
Improved understanding of customer needs
Demographic clustering will help you to understand the needs and wants of your customers. This will help you to identify gaps in the market and how to modify your product offering to better satisfy your shoppers.
This benefit links up with new product development as you can prioritise new development efforts based on the needs of your clusters and create products that have a higher market success rate.
Demographic clustering is a useful tool for effective customer segmentation and targeted marketing. It’s a method you can use in your business no matter if you are a large retailer looking to optimise your product offering or a small business wanting to optimise a niche market.
Need assistance with getting set up with your clustering or need advice? Let DotActiv help. Find out more about our clustering services here or book a meeting here.