In today's digitized world, consumers are bombarded every day with a huge amount of information, but only a fraction of it is consciously perceived. Only those who really know their target groups and bring the right products to the right region(s) can best meet the demand and ensure high response rates for advertising measures.
But how can you use geodata to find out more about your own customers, about whom only little sales information is available and hardly any further preferences are known?
Well, “tell me where you live and I'll tell you who you are”, since a place of residence reveals a lot about a person, be it for example their income segment or their likely consumer behavior. And since people are shaped by society, it is assumed that people with similar preferences and circumstances often live next to each other.
Based on this information, conclusions can be drawn, for example regarding purchasing power, level of education or even travel habits. By analyzing existing customer data regarding the place of residence of the respective customer, and enriching it with further current spatial, socio-demographic, economic or consumption-relevant data, customer profiles can be sharpened, market shares increased, and marketing costs reduced.
Dirk Simon, CRM expert and managing director of Merifond, uses 6 steps to explain how successful data segmentation and enrichment works.
1. Spot gaps in customer profiles for sales potential
Even if that sounds trivial, but the first step is to understand that the existing customer sales data are not complete and that they do not allow any conclusions to be drawn about the true potential of the customers.
2. Check the status quo and target state of the customer profiles
There are different methods and options for enriching customer profiles with geodata. For example, if you have already subjected your customers to a cluster process, the profiles can be further developed with the help of the geodata and the clusters can be supplemented with metadata that you would normally not receive from the customer (all data on the living situation, but also purchasing power, family constellation or purchasing and travel preferences).
3. Add geodata to customer profiles
After the existing customer sales data are enriched with spatial, socio-demographic, economic or consumption-relevant information, these data are used as statistically representative target group characteristics in microcells without personal reference by special providers. In addition, during data enrichment, the expanded customer segments must be compared again with the sales and marketing goals that have been set.
4. Validate target group definition and derivation
After the customer segments have been supplemented with valuable geodata, it must now be tested to what extent this can now be operationalized. In practice, you take a very striking example: you choose a powerful target group and use the geodata to better describe the target group. The description is applied to the entirety of the customer segments, regardless of whether they have already bought the "starting product" or not. This gives you a wider circle of potential interested parties. To validate how successful the enrichment and the resulting results were, it is necessary to start testing.
5. Test and find out which customer group offers the most
Now the segments should be analyzed again regarding the sales potential, which can best be implemented with the help of comparison marketing. As part of, e.g., newsletter campaigns, the existing customer group and the new customer group can be determined and compiled. And thanks to data enrichment addressed and encouraged to buy a certain product. The result (number of product sales, registrations, etc. per group) is a clear indication of which group has the greater potential. The test phase is the alpha and omega of the geomarketing process because the results achieved here provide an important basis for further business decision-making.
6. Addressing customers – the supreme discipline of marketing automation
Finally, the customer communication should be derived from the formed clusters with the help of marketing automation. With marketing automation, the entire communication workflow is "automated", based on the customer segments created. In addition, it makes sense to opt for a flexible software solution in the context of CRM and geomarketing, and to work with an expert who takes care of the entire range of sales, geo and analysis data and has the corresponding expertise. In this way, abstract series of numbers become accessible customer landscapes with sales potential.