Understanding who your customers are can help you make better decisions about who to target, where to focus your marketing and where future opportunities may exist.
Most businesses already hold useful information about their customers, from addresses and transaction histories to loyalty and CRM data. On its own, however, that information only tells part of the story. Combining it with demographic, consumer and location data can reveal patterns across your customer base and help you understand what your strongest customers have in common.
Here are six customer profiling factors worth considering.
1. Location
Knowing where your customers are located can tell you much more than simply how close they live to a store, branch or other location. Mapping customer postcodes can reveal the geographic spread of your customer base, show where particular groups are concentrated and help you understand how far people are prepared to travel.
It can also highlight differences between individual locations. One branch may draw most of its customers from the immediate area, while another attracts people from a much wider catchment. Looking at those customer locations alongside demographic and consumer data can then provide greater context about the types of areas your customers come from and help identify other places with similar characteristics.
2. Age
Age can be a useful part of a customer profile, particularly when considered alongside other characteristics. Rather than assuming that everyone within an age group has the same income, interests or purchasing habits, it is more useful to look at whether particular age groups are over or under-represented within your customer base and whether that changes between locations.
Combined with purchasing data, age can also help uncover differences in behaviour. Certain groups may buy different products, visit more frequently or represent a greater proportion of customers in particular areas. Those patterns can then contribute to a more rounded understanding of the audiences your business attracts.
3. Income and affluence
Income and affluence data can provide useful context when you’re trying to understand the purchasing potential of different areas. Rather than attempting to estimate the income of individual customers, demographic datasets can provide broader measures of household income and affluence across different geographic locations.
This becomes particularly useful when comparing customer catchments or potential markets. You might find that some of your strongest-performing locations serve areas with similar affluence profiles, or discover that your most valuable customers don’t fit the profile you originally expected. Either finding can help challenge assumptions about where future opportunities may lie.
4. Household characteristics
Household composition can have a significant influence on people’s needs and purchasing behaviour. Families with young children, single-person households, couples and multi-generational households may all have different priorities, making household characteristics another useful layer of customer profiling.
Comparing these characteristics with your existing customer base can help identify the types of households you currently attract and how that varies between locations. It can also reveal potential gaps. An area might contain a high concentration of households that closely resemble an existing customer group, for example, but relatively few current customers. That could make it worth investigating as a potential acquisition opportunity.
5. Purchasing behaviour
Your own transaction data can provide some of the most valuable information for customer profiling because it shows what people actually do, rather than what you assume they might do.
Looking at what customers buy, how frequently they purchase, how much they spend and which locations they use can help identify your most valuable customer groups. When this information is combined with location and demographic data, further patterns can emerge. You might discover that customers travelling from one particular catchment visit less frequently but spend more when they do, or that certain customer groups favour particular products or locations.
Understanding those differences can help you build a much more useful picture of customer value and the characteristics associated with it.
6. Consumer characteristics and behaviours
Demographic information can tell you a great deal, but two households of a similar age, income and composition won’t necessarily have the same interests, preferences or behaviours. Consumer data can add another layer to the customer profile by helping you understand these differences.
Combined with your existing customer data, this can help identify groups that share characteristics with your strongest customers. It can then be used to look beyond the people who already buy from you and identify other areas where similar potential customers are concentrated.
Bringing the different factors together
No single characteristic gives you a complete picture of a customer. The value comes from combining different factors and looking at the relationships between them.
For example, you might discover that your highest-value customers share particular demographic and consumer characteristics and tend to be concentrated within certain types of area. You can then look beyond your existing customer base to identify other locations where similar audiences are present but where your current customer penetration is relatively low.
This is where Customer Intelligence becomes particularly useful. Periscope® enables businesses to combine their own customer information with demographic, consumer and location data, helping them identify patterns, understand their customer base and uncover potential opportunities for acquisition and growth.
Discover how Periscope® can help you understand your customers and identify where more of the right ones can be found.
