U.S. homeowners and car owners data, how to filter out customers more suitable for development

When working in the US market, homeowners and car owners have always been the more common labels. The reason is very simple. Many home furnishing, automobile, insurance, maintenance, home decoration, energy, and life service products are themselves related to housing and vehicle usage scenarios. However, promotion of U.S. homeowners and car owners cannot be started directly after obtaining the list. The U.S. market is huge. A homeowner may live in an apartment in New York or a single-family house in Texas; a car owner may just commute daily, or he may own multiple cars at the same time. To truly conduct accurate customer screening in the United States, we should not just look at whether there is a house or a car, but also consider the region, product demand, data sources and follow-up communication channels.

Why U.S. homeowner data needs to continue to be broken down

There are a large number of homeowners in the United States, but the target customers corresponding to different products are obviously different.

When doing home decoration, doors, windows, furniture, courtyards, roofs, solar energy, smart home and other businesses, the identity of the homeowner does have certain reference value, because the products are directly related to residences. But a homeowners label isn’t enough.

For example, for the same residential product, the climate, housing types and consumption habits of different states may be different. Promoting sun protection, patio or air-conditioning related products to Florida users is completely different from promoting heating and insulation products to northern regions.

Therefore, when organizing data on U.S. homeowners, you can first group them by target areas, and then select the groups of people who need to be followed up based on your own products.

If you already have state, city, zip code area, product consultation, advertising source and other information, you can continue to use it in combination. This makes it easier to narrow down the scope than simply developing a list of U.S. homeowner numbers one by one.

U.S. car owner data can’t just look at whether there are cars or not.

The same goes for car owners.

Businesses such as automotive supplies, repair and maintenance, insurance, tires, vehicle equipment, car wash services, and automotive software all focus on U.S. car owner data, but different products target different people.

When selling car beauty products, you need to focus on people who have daily car needs; when doing commercial vehicle-related business, you are more suitable for finding corporate vehicles, logistics, transportation and other scenarios; when promoting new energy vehicle-related products, you need to further differentiate between vehicle types and usage needs.

Therefore, US car owner data screening is best done around products.

If the product is aimed at ordinary consumers, continue to classify it according to region, channel and user interest; ifFor B2B automotive services, you may need more information such as company, industry, fleet type, etc.

The car owner is only the first layer of labels. What really determines whether the product has development value is whether the product has an actual relationship with this user.

Homeowner and vehicle owner tags can be combined, but the more the better

Some customers may belong to both homeowners and car owners.

For some businesses, this cross-labeling is valuable. For example, home energy, garage equipment, home charging facilities, and some insurance products may involve both housing and cars.

But it cannot be simply assumed that people with two labels are necessarily more accurate than people with only one label.

If you are selling car tires, the identity of the homeowner is not very helpful; if you are doing roof repairs, whether the customer has a car is not a core condition.

Customer tags should be used around the product, not to make a piece of data look informative.

When selecting accurate customers in the United States, you can first ask a very practical question: Will this label affect users' purchase of my product?

If the answer is no, there is no need to put it in the main filter.

The source of the data deserves more attention than the number of tags

The same data on U.S. homeowners comes from different sources and may have completely different usage values.

If a group of users come from the company's own official website consultation, advertising form, event registration, and old customer system, you can at least know why these users entered the database.

For example, if a user has filled out a home improvement quotation form, then there is a direct relationship between the homeowner label and the current business; if a user has clicked on a car service advertisement and actively submitted contact information, then the car owner-related information will be more easily connected with actual needs.

If you only have the name, mobile phone number, and homeowner’s car owner tag, but do not know where the data comes from, and there is no clear authorization and business background, subsequent marketing risks and invalid contacts will increase.

Therefore, when it comes to U.S. customer data, it is not that the richer the labels, the better. First, it is necessary to ensure that the source is clear, the purpose is clear, and the user's contact preferences must be respected.

After organizing the data of homeowners and car owners, you can continue to screen communication channels.

After completing the classification of American homeowners and car owners, the next step is usually to solve the problem of how to contact them.

Some companies mainly useWhatsApp does follow-up work with overseas customers, and some businesses will use Telegram, email, text messages or other channels. Apple eco-related products may also focus on iOS, iMessage and other usage environments.

At this time, number screening can be used as a subsequent data sorting step.

For example, an enterprise has obtained a batch of U.S. customer numbers through compliance business channels, some of which are labeled as homeowners or car owners. It can first unify the phone number format, remove duplicate data, and then continue to classify them according to actual marketing channels.

Digital Planet can be used for number sorting and platform screening at this stage. Based on business needs, existing U.S. numbers can beWhatsApp activation detection, Telegram related filtering, iOS or iMessage type data sorting, etc., combined with the original homeowners, car owners and regional tags to create different customer groups.

In this way, the U.S. customer list no longer only has one homeowner or car owner label, but gradually forms a more complete usage structure.

For example:

American homeowner＋Official website home improvement consultation＋WhatsApp can communicate

American car owners + car product form + target state users

American homeowners and car owners + Apple device related users + specific product needs

These combinations make it easier to arrange a subsequent sale than listing a homeowner or vehicle owner alone.

Regional filtering is often more practical than blindly expanding the amount of data

The U.S. market is huge, and it is not necessary to cover all states at the beginning when targeting customers.

If the business can only serve certain areas, it will be more practical to filter based on service scope first.

For local home improvement, maintenance, cleaning, insurance agency and other businesses, you can prioritize customers in target states or cities. For nationwide e-commerce products, although there are fewer regional restrictions, you can still adjust key markets based on logistics, season and advertising effects.

For example, if a product has a significantly higher inquiry rate in southern states, the data on U.S. homeowners in that area can be given a higher priority.

Customer screening is ultimately not to create the largest database, but to help sales first find people who are more likely to generate demand.

The identity of homeowners and car owners cannot directly represent spending power

This is also easily misunderstood.

Owning a house and a car can indeed explain part of the life scene, but it cannot be directly equated with high consumption, high income or strong purchase intention.

Housing prices vary widely in different regions of the United States, and vehicle prices also vary greatly. It is easy to judge the customer value too simply by judging the user's spending power based only on the identity of the homeowner or car owner.

What really has reference significance is still user behavior.

Active inquiry, service reservation, filling in product requirements, applying for quotations, and consulting on installation methods are often closer to real purchase intentions than simple crowd tags.

Therefore, in the precise customer screening in the United States, homeowners and car owners are suitable as the entrance to the crowd, and behavior and needs are more suitable as the basis for judging sales priorities.

Different businesses require different customer mixes

If you are doing home decoration, you can focus on the status of U.S. homeowners, target areas, housing-related inquiries and contact information.

If you are doing automotive supplies, you will focus on American car owners, product interests, target regions and actual consultation behavior.

If we build home charging facilities, we can combine the needs of homeowners, car owners and new energy vehicles at the same time.

If you are doing ordinary cross-border e-commerce, homeowners and car owners may only be auxiliary tags, and do not necessarily need to be the core filtering criteria.

In this type of data processing, Digital Planet is more suitable to be responsible for number-level sorting and social platform screening, helping to assign existing customers to more appropriate communication channels. As for who really belongs to the precise customers in the United States, we still have to go back to the company's own products, user sources and actual needs.

The real value of U.S. homeowner and car owner data is not simply telling salespeople that they own a house or a car, but helping to quickly narrow down the target range. First determine who is needed for the product, then look at the region and user sources, then use number detection and channel screening to continue sorting, and finally hand over the customers who really need it to sales for follow-up.

When screening American customers, you don’t need to pursue the largest number of homeowners and car owners at the beginning. The closer the data and product match, the more time will be saved in subsequent development.

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