How can we utilize Customer data? Customer Analytics is the answer

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How can we utilize Customer data? Customer Analytics is the answer

Any brand’s most important stakeholders are the individuals it is attempting to reach: its customers. It is customer analytics which reveals who your customers are and how their decisions are influenced. Customer-related key indicators provide important insight sales and marketing strategies. If you want to improve your bottom line, you must first gain a thorough understanding of today’s customers in order to attract, keep, and grow them.

Today’s consumers are more informed and opinionated than ever before, and with access to limitless information at their fingertips in seconds, they can easily be persuaded by other brands. You must have a great awareness of customer behaviour if you wish to succeed in a competitive environment with such smart customers. Customer analytics enables you to make well-informed business decisions based on your customers’ preferences. Everyone is happy at the end!

Data from each stage of the customer journey assists firms in strategizing their marketing and sales operations, as well as lead generation methods. Customer Analytics through data analytics services can be used to develop a business map from a customer journey that is customised to specific customers by leveraging trends in customer behaviour.

How can we utilize Customer data? Customer Analytics is the answer

The need for Customer analytics

Customer analytics 

Helps you answer an almost infinite number of questions, and right answers to those questions will benefit every department in your firm. Customers will  be able to drive more personalised, timely marketing efforts using customer insights.

Assists your sales team in gaining a better understanding of your clients’ purchasing processes. The insights further assist in shortening your sales cycle.

Helps your product team figure out what features your consumers enjoy and don’t like so they can design a better product.

The kinds of customer analytics

Here are some broad categories of customer analytics:

Descriptive analytics: It is a type of data analysis that is used to describe any data type and happening. . It gives you information about previous consumer behaviour. (For example, within a month of purchase, 30% of customers returned product X.)

Diagnostic Analytics: It assists you in comprehending the “why” underlying customer behaviour. (For instance, 50% of buyers believe product X is not what they expected.)

Predictive: It is a category of analytics that refers to the study of patterns in It can assist you in predicting future customer behaviour. (For example, product X sales are predicted to drop in the fall of 2020.)

Prescriptive analytics: It refers to the use of data to provide advice on how to influence or change customer behaviour. (For example, social media campaigns and internet marketing can boost product X sales by 25%.)

What kind of customer data to collect/store for customer analytics?

In general, customer data can be divided into four categories, which are as discussed below:

Data on Web Usage: A website’s users generate a large amount of data. Analyzing how visitors use the website, navigate, and spend time on a certain page can help you understand customer behaviour in many ways.

Data on the use of a product or service: Customers who use a company’s product or service create data as well. For instance, health app generates a large amount of data on mobile app on-screen time, app feature usage data, in-app spending, and so on. So, each product or service provides useful information. This data helps to  upgrade/delete the features of the product/service. 

Data on Transactions: Customer payments, transactions, purchases, and other transactions generate the most data. This information will include the customer’s ID, date, time, amount, and product purchased, among other things. 

Text Data: Customers contribute a large amount of text data, which can include reviews, comments, and other information. This type of information can aid in the comprehension of client feelings. It is possible to comprehend the attitudes of customers about the organisation using Machine Learning and Deep Learning techniques like NLP.

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Leverage all your customer data to drive customer analytics

When you begin tracking and collecting customer data, you will be able to use it to answer inquiries and address issues. Ultimately, you will make better business choices. Data is a tool that helps you customise content for users, focus on campaign promotion to the correct audience, and improve product development, sales, and marketing.

You should analyze all your customer channels, and learn how the service or product helps/serves customers of all demographics. Understanding customer-generated data such as ratings, reviews, and comments can help to advertise the business more effectively.

Customers who are at risk of being lost should be targeted for retention to increase customer lifetime value. Here customer segmentation can be used to target customers more effectively across all channels and groups.

Customer analytics helps you better understand your customers and significantly impacts your business’s bottom line. So, you must take customer analytics very seriously. Take the effort to establish a customer analytics stack if you want to take your company to the next level by providing a better experience to your consumers.