Customer Data Mining: 8 Practical Examples

Customer data can be a gold mine for companies, but many aren’t using this data to its full potential. Customer data mining can provide insights to help your organization increase customer loyalty, enhance product profitability, and reduce client churn. Here are eight ways to use customer data for marketing and general insight.

Affinity Analysis

Affinity analysis, or basket analysis, looks at the products that a customer purchased, helping physical locations optimize their store layout and online companies recommend related items. The ‘basket’ in basket analysis refers to a customer’s shopping basket.

Companies use affinity analysis to look at purchases over time. This technique isn’t limited to products purchased at the same time. In fact, most analytics tools observe customer behavior over time, helping you spot opportunities and trends.

An example of a beneficial finding is what products are often purchased together, which one they purchased first, and if you can encourage them to purchase a third item.

Card Marketing

For companies that issue credit cards (e.g. Delta SkyMiles Credit Card), you can mine card data for information about the card’s usage to, for example, identify your customer segments and engineer programs to boost acquisition and improve retention.

Many businesses do not have the volume to justify having their own credit card. But if it is ‘in the cards’ for your company (see what we did there? #puns), having them will provide a more granular level of data for customer spending habits. This can lead to better customer loyalty and higher overall revenue.

Customer Loyalty

Customers can be lost, and retained, for a variety of reasons. Customer data mining can help you minimize churn.

When mining customer data, focus on values like customer lifetime value to help you improve your acquisition costs and identify what happens when customers move on to a competitor.

If you sell through social media platforms like Facebook and Instagram, the data you collect  can generate new ideas to improve your brand, satisfy your customers, and increase their loyalty.

Product Development

Customer data mining also works well to help you create custom products designed for specific market segments. To create a truly innovative product, enterprises look at customer data to determine gaps in the market that consumers want filled. Some elements that must be part of that product include:

• Fulfilling a need or solving a common problem
• Offering a truly unique product
• Entering the market with a relevant, unique name
• Designing with looks in mind (in addition to usefulness)
• Serving a wide market
• Selling your product in generations
• Creating a price that encourages impulse purchases
• Creating it with low enough costs to make a strong profit

Begin with a customer pain point that you uncover from data mining, work towards a minimum viable product, and you’ll be on the road towards a viable product.

Related Article: Data Preparation: What Is it?

Pricing Strategy

Diving deep into your sales marketing data can provide great insight into how much you can and should be charging your customers for different products and services. If you charge too much, people will typically lean towards more competitively priced offerings from your customers. If you charge too little, you’ll be leaving cash on the table and can even leave the impression that your products have less value.  

Entire books have been written about the techniques for pricing, so the topic is too complex for this article. But the company AdRoll has provided a great write-up that can serve as a solid next-step in your research.

Call Record Analysis

Call data from both inbound and outbound phone traffic can be mined for patterns and insights. Modern systems can link calls directly to records within your CRM and other systems. This data can be crucial for mapping out an accurate picture of what your customer journeys’ look like.    

Market Segmentation

Market segmentation is one of the best uses of data mining. You can use the data to split your customers into meaningful segments like income, age, occupation, income level, geography, etc. These segments can be used to create your most prevalent Buyer Personas.  

Segmentation allows for better targeting when marketing and advertising, better message creation, and better identification of relevant competitors.

Warranties

Data mining can also help you predict the number of customers who will take advantage of any warranties or guarantees you offer. One of the best ways to create a successful warranty is by looking at the data from past warranties, sales, and profits.

In some cases, it might be more profitable to offer a higher-quality warranty to gain an edge over your competitors than saving in the short term by offering smaller guarantees and warranties with less coverage.

What’s Next

Are you making efficient use of your data? Schedule your data assessment strategy with Zuar today, and find out how you can improve your customer data mining for marketing.

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• Zuar Runner: Transport, warehouse, transform, model, report & monitor. Runner gets data flowing from hundreds of potential sources into a single destination for analytics.
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