Customer analytics – how data-driven decisions can drive your business forward

If you want to reach customers in the best possible way, you need to know them and respond to their wishes and habits. Customer analytics help you get to know your users and derive useful insights from the information you have about them.

Customer analytics can not only help you target customers more effectively, but also save you money.

Our guide will explain what customer analytics actually are and how you can use them.

What are Customer Analytics?

The term customer analytics describes the process of collecting and systematically evaluating customer data. In this way, it is possible not only to determine the needs of customers, but also to predict future developments with regard to churn or purchasing trends.

The data for customer analytics comes from a wide variety of sources and channels such as the CRM system, communication on social media, transactions, or newsletter tools.

The basic concept of customer analytics can be summarized as follows:

Customer data is evaluated and processed with the help of analysis technologies in order to make better, more informed decisions.

Customer Analytics graphic
Customer Analytics overview

Why you should be using Customer Analytics

Customer analytics enables you to learn about and understand customers and their needs, desires, and motivations. These insights will help you identify and target the most valuable customers. Customer analytics can help you get more out of your business model in the following ways:

  • Customer analytics allow you to make predictions about the success of campaigns or sales
  • You increase the response rate to promotional actions by tailoring the promotions to the customers
  • Reduce campaign costs by focusing on customers who are most likely to make a purchase
  • Unhappy customers can be identified and damage to the reputation of your brand can be prevented
Level of Freedom
Reporting vs. Analytics

Use data analysis to productively communicate with existing customers

Customer analytics are primarily suitable to support existing customers. Managing those customers is much less time-consuming and cost-intensive than acquiring new customers. Loyal existing customers often buy more and at higher prices, which is how they create more value. They are also less price-sensitive and have a higher payment morale.

All these reasons speak in favor of intensively addressing existing customers, yet many companies are rather reluctant in this respect. Deutsche Post’s Dialog Marketing Monitor 2019 found that only about 30 to 60 percent of companies use targeted communication with existing customers. Customer analytics enable you to tap the potential of your existing customers and provide them with the best possible individual support.

Customer Analytics and Customer Insights!

Customer Insights Suite Light dark version

Steps towards success in Customer Analytics

If you want to take advantage of the opportunities offered by customer analytics, a structured approach is recommended. Find below the most important steps on your way to successful customer analytics.


Define your goals

For successful and insightful customer analytics, it is important to determine which goals are actually to be achieved. Depending on the type of response desired, there are the following approaches:

  • Descriptive – What has happened?
  • Diagnostisc – Why did it happen?
  • Prescriptive – Answers on certain questions
  • Predictive – How could future developments look like?


Know your customer

First, you should understand who your customers are by looking at the Customer Journeys. Consider all points of contact between your company and your customers. The following questions can help you:

  • Who are the customers you want to reach? This question can be answered with socio-demographic data such as age and income (for other data that can be collected, see market segmentation)
  • Which of your products are they buying?
  • When are they buying? At what time of day? During the week or rather at the weekend?
  • How do customers purchase your products? Online or offline?
  • Through which (online) stores do customers purchase your products?
  • Which channels do customers use to communicate with you?
  • How do they react to promotions?
  • Why are they buying your products?
  • How do they use your products?


Collect the data

Collect customer data in all possible interaction points with your customer. Possible sources include:

  • Your website and its analytics
  • Visits, purchases and other interactions in the online store
  • Email-clicks
  • Your app
  • Social Media
  • Mail Automation Tools
  • Surveys
  • Your Customer Relationship Management-System (CRM System)

Compile the data in a central location, such as the CRM system.


Organize and arrange the data

Filtering out the relevant information from the flood of information collected is important, as is finding a common thread. A CRM system or a Customer Data Platform (CDP) helps you sort your data so that it can be evaluated effectively.


Evaluate the data

With the help of data visualization and dashboards, you can present collected data clearly. Reporting tools in your CRM system or external tools such as Datawrapper can help you do this.

Not only charts, but also infographics or videos can be used for visualization. The better the data “comes to life,” the easier it is to identify outliers, patterns, and ultimately opportunities and market gaps.

Is Customer Analytics really useful?

The consulting firm McKinsey has found that the use of customer analytics offers companies significant added value and has a substantial impact on the performance of companies. It was determined that the use of customer analytics brings considerable benefits in KPIs such as profit, sales or ROI.

Companies that make extensive use of customer analytics are more likely to report outperforming their competitors on key performance metrics, whether profit, sales, sales growth, or return on investment.
For example, companies that use customer analytics comprehensively report outstripping their competition in terms of profit almost twice as often as companies that do not.

Customer Analytics

Case studies - how successful companies use customer analytics

Many well-known companies are already using customer analytics successfully. The following examples show how diverse the possible applications can be.



How Netflix uses analytics to keep its subscribers glued to the screen

The world-renowned streaming provider knows its users very well and suggests potentially relevant content to them every time they log in. With more than 182 million subscribers (April 2020, source:, Netflix is able to gather data on a wide variety of people and their viewing habits. The use of Big Data analytics helps to identify patterns in search and viewing habits and make suggestions on this basis

Netflix collects a wide variety of data. For example, it collects data on how long a series is watched, whether it is watched to the end, and at what point it is interrupted. If, for example, 70 percent of users who have started a series watch it to the end, Netflix can decide on the basis of this data to produce another season.

Through its data-driven, personalized content offering, the streaming provider thus manages to retain its users and counteract churn.


Customer analytics help Amazon improve user experience

Amazon collects a wide variety of information about its users and their purchasing and surfing behavior in order to offer them a better user experience. For example, it records which products are viewed and for how long, as well as many other metrics.

With the help of this data, a 360-degree view of the customer is created, which makes it possible to suggest suitable products. This makes purchasing decisions easier and prevents users from feeling lost in the flood of products.



Customer analytics is the collection and use of customer data. It helps you make better decisions based on data.

It is important that you formulate target questions which will be answered using customer analytics. The collected data must also be processed in a way that allows patterns to be identified and insights to be generated.


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As a founder and entrepreneur, I experience every day how important customer centricity is for companies.

Integrate the essential customer perspective into your product genesis and marketing processes. That puts horse powers on the street, until it runs.


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