No two customers are the same. Even though customer segmentation is not a new concept, the need for it has reached new heights. This is because the market place is becoming more diverse. Customer segmentation data mining helps you address customers in a way that resonates with them.
Segmentation is the first step towards personalization. Additionally, creating segments based on the likelihood of engagement helps you prioritize your marketing. Personalization is important but can prove expensive and difficult to scale.
Customer segmentation data mining can help you personalize your marketing in a cost-effective way. Effective data mining needs a powerful platform.
Here’s our three-step guide to customer segmentation data mining
Step 1: Start with Big Data
Having a great platform is not enough. You need to start with high-quality data as it can generate great insights.
Data is everywhere. In fact, Big Data management is still considered a challenge. All data is not equal. It is important to gather high-quality data to feed your analysis. To this end, screening your database can add great value. Screening can take basic information about your customers (such as names and email addresses) and helps you fill in the gaps. The process can append other relevant information about them.
For instance, WE Screen takes our proprietary wealth scores and ratings and merges them with your contact data. Further, you can know more about your contacts’ interests, political affiliations, net worth, and their capacity to spend. Combining these data points with wealth ratings can be powerful. Wealth ratings ultimately help you rank customers in order of priority.
For example, let’s say you are a luxury travel company that curates bespoke experiences. You can screen your database to understand your customers beyond their age, name, and email. Screening gives you a holistic picture including ownership of vacation homes, boats, private jets, etc. All this information can help you refine their experience.
However, it is important to note that data is not an end in itself. It is a means to get actionable insights. This brings us to the next step of Customer segmentation data mining.
Step 2: Conduct Data Mining for Customer Segmentation
The high-quality data you acquired from screening should go into the right analytics platform. A powerful platform can deliver actionable insights by mining your data.
Data mining for customer segmentation helps you see what makes your customers unique. Further, you can understand the composition of your audiences in detail. These insights can also help you determine your messaging.
As an example, WE Analyze is a powerful analytical platform. The solution lets you enter hundreds of attributes that the engine uses for data mining. Further, WE Analyze can identify what traits your customers have in common.
For your luxury travel company, the analysis could reveal usable insights. You could find out that all customers with a Lifetime Value (LTV) of over $250,000 have five traits in common. They are all between the ages of 40 and 55 and have either two or three children. They have leased from the same brand of car over the past eight years or more and they have vacation homes in Florida.
Knowing all this means that your marketing can be highly personalized.
Step 3: Automate Customer Segmentation through Data Modeling
Modeling can further refine data mining for customer segmentation. If you have a specific marketing question, a model finds you an answer that is backed by data.
Let’s say you are trying to find more luxury travelers to market your services to. This prospecting exercise can become highly precise when you use data models.
You could take the important traits identified by your analytics platform and enter them into a model. The model will examine your database and segment it for you. Let’s say are trying to find top luxury travel customers out of a database of 100,000. The model will automatically segment them into 10 equal groups. The first group will contain your top 10% of customers.
How does this work? In the data mining or analysis stage, you found the most important common traits found among your customers. The model uses these traits to find more prospects that are just like your best customers.
WealthEngine’s modeling suite goes beyond pre-set models for luxury industries. Each model is custom built for your business. This means you don’t stop at what works well in your industry. You actually find out what works best for you.
Thus, the third step of customer segmentation data mining creates refined segments for you. Refined segmentation acts as a foundation for personalization. Data mining also removes manual effort in segmentation, making it cost-effective and scalable.
Learn more about how you can use power up your customer segmentation through powerful data mining and modeling solutions. Model your data now.
Why You Need a Concierge Marketing Strategy
Using Big Data and Fundraising Data Analytics for Marketing