In this world where customer experience is the key to success, we often hear people discussing the various uses and advantages of customer data analytics. This term generally refers to the process of using data and information and surrounding the customer behavior to make business decisions and it usually involves techniques that include predictive modeling, data visualization, and information management. 

When it comes to understanding your own customer, “Customer analytics is a set of data that is used to understand the composition of the audience, satisfy your customer’s needs. Also, the enabling technology used to segment buyers into grouping and based on the behavior of the audience, to determine general trends, or to develop targeted marketing and sales activities.”

Organizations are relying on customer analytics to gain a deep understanding of your audience of their prospects and customers. The information gathered enables businesses to deliver relevant information and strengthen relationships with existing customers and potential customers, as well as identify key drivers of buying behavior to better target prospects and nurture leads through the sales funnel. 

Ultimately, customer analytics and data analysis services can lead to an increase in loyalty and customer lifetime value as well as greater efficiency in customer acquisition and provide your company growth.

Benefits of Using Customer Analytics

While some of the retailers have barely scratched the surface of customer insights, the retailers who are effectively utilizing customer data and analytics are able to identify the information that is always responsible for streamlining the operations, enhancing the productivity, customizing marketing initiatives for both current and potential customers, determining where to open new locations and improving the profitability of the organization.

1. Marketing Efficiency

Focusing on the individual customer takes your marketing analysis beyond just knowing your spending and the eyeballs you received in return. Knowing which marketing channels bring the highest value customers in terms of order size, retention rate and profitability allows you to either cut marketing costs or expand your reach more efficiently.

2. Customer Retention

Customer acquisition is expensive, so it’s important to understand what causes customers to leave. Customer analysis can help you identify common denominators among lost customers and give you an early warning that existing customers may be in danger of leaving if you don’t take corrective action.

3. Increased Sales

Understanding customers purchasing strategies is the key to increasing sales. Use customer analysis to identify the factors that have both a positive and negative impact on sales of the organization. This could include shipping times, how customer service interactions are handled, whether you have a minimum order or bundled discount, or the customer’s location or income.

4. Improved Profit Margins

Not all customers are equal. Some customers are more profitable than others, and some may even cost you money. Factors that affect customer profitability include order size, cost of handling the order, time spent in servicing the account, and returns. Amazon has gained notoriety for issuing lifetime bans to customers who cost the company money by returning too many items.

Tools for Gathering Customer Data

There are many people, products, and reasons behind moving your goods back and forth. That’s why there are many tools you can collect customer data to inform your business decisions.

1. Order Forms

Order forms outline the details and names of the transaction to build a transaction history. Order forms can either be hard copy/paper form or online, which makes record storage easier.

2. Customer Satisfaction Surveys

Surveys are documents where customers provide details about their purchasing experience with you. Some surveys will ask respondents for their gender, age or education level. This information is helpful in providing a clear picture of the target customer.

3. Competitions

Sponsor a contest with prizes to customers who sign up to play. Customers may be willing to share personal information if they think there is a prize on the other end.

4. Customer Service Records

A customer service record describes the transaction history between the business and the customer. Information recorded includes customer service representative names, product returns, and other sale histories.

What Types of Customer Data to Collect

The purpose of collecting customer data is to build the profile of your ideal customer. This allows you to influence your company’s marketing campaigns, current, and future sales. See the list below on the basic types of customer data you should collect.

1. Name and Contact Details

Collecting this information will allow you to make your outreach individualized to them. This is also a good way to build a relationship with your customers and notify them if orders are going to be late.

2. Age, Gender, Profession, and Income Information

This can help build a clearer profile of who your target customer is. This information will also help focus marketing efforts and develop your pricing strategy.

3. Previous Transactions History

This information is available from your customer service records. It allows you to notice trends and preferences for products, such as when they’re most likely to buy them and how often.

4. Tools Customers Use to Find You

This metric helps you test which communication type convinced the customer to buy. If your sales data shows that customers listed your office outgoing voicemail message as their source for upcoming sales, you may have found the method of communication that encourages them to buy more. 

Conclusion

It might be somewhat impossible to dive into the raw data of your customer behavior analytics because it seems disparate and unpredictable when it comes to understanding. It might not reflect your products roadmap, your existing support strategies, or your sales cycles process.

When it comes to reality this data is crucial for growth and revenue. Brands are fighting tooth and nail to differentiate themselves in developing innovative, hyper-competitive world’s. Armed with the right data and analytics strategy, the right approach to customer relationship management, raw data can be easily understood and shared among the organization.

Creates a context for individual stories, streams of the activity or behavior, that show relationships and reveal the impact of relationships for both customers and organization. At the end of the day, it’s all about relationships, isn’t it?