Five things to know about customer profitability analysis:

  1. Customer profitability analysis is a way to work out the 'profit' each customer generates for your business.

  2. You can analyze customer profitability to tailor pricing and promotions and fine-tune marketing campaigns in your organization.

  3. Profitability analysis can be difficult if data exists in lots of different systems.

  4. Data warehousing can help you move data to a single source of truth and carry out profitability analysis through BI tools.

  5. is a data warehousing integration solution that requires little or no code, making profitability analysis even easier. 

Digital retailers often talk a lot about 'profit' without ever determining the factors that drive profitability in their businesses. One of the biggest contributors to profit in e-commerce is existing and new customers who purchase products and services from online stores. However, the connection between customers and profitability can be unclear unless you carry out the right kind of analysis. In this guide, learn more about customer profitability analysis and how it can influence pricing and promotions in your organization. 

Table of Contents is the data warehousing integration solution for e-commerce. Now you can move customer data from sources in your organization to a data warehouse and run that data through BI tools that perform customer profitability analysis. Email to learn more. 

Customer Profitability Analysis, Explained

In the simplest terms, customer profitability analysis (sometimes abbreviated to CPA) determines how much profit each customer brings to your business. That 'profit' isn't just the amount of money a specific customer spends on products or services. Customer profitability analysis looks at all the touchpoints and contributions a customer makes and the expenses they incur throughout the sales lifecycle. It tells you which customers make you the most money after you account for sales, returns, marketing costs and initiatives, pricing decisions, consulting costs, and other factors. 

Say you own an e-commerce company. Customer A purchased $1,000 worth of goods from your store. However, you spent time and money prospecting that customer and moving them through your sales and marketing funnels. The customer also returned some of their purchases. Customer B purchased $500 worth of goods from your store and didn't return any of those goods, and you didn't spend a significant amount of money prospecting this customer. In this simplified scenario, Customer B provided your enterprise with greater profitability than Customer A.

Analyzing the profitability of each customer can improve decision-making and reveal which customers provide your company with the greatest value. You can use data analytics to set the right pricing for products and target 'high-value' customers with promotions to increase profit for your enterprise. By optimizing pricing and pricing models, for example, you might generate more sales from customers and improve profit margins.

Customer profitability analysis is an important metric. Still, many e-commerce business owners focus on the profitability of their company as a whole rather than segmenting customers based on individual profitability. That's why this metric can help you outrank your rivals and provide in-depth intelligence that you can't find anywhere else. 

How to Carry Out Customer Profitability Analysis

There is no golden rule for customer profitability analysis. However, you will want to determine the notion of 'profitability' when deciding whether certain customer segments provide your enterprise with value. 

What Makes a Profitable Customer?

Before conducting a profitability analysis, determine what makes a customer 'profitable.' As mentioned earlier, a profitable customer isn't necessarily one that generates the most money for your e-commerce company. That's because a profitable customer might spend relatively small amounts of money but keep doing business with your company over many years, making them valuable in the long term. (This is a similar concept to customer lifetime value or CLV.)  

There are also costs that you might incur when dealing with customers. You might need to spend money on marketing to raise awareness about your product before a customer purchases it or pay for shipping costs when sending out items. 

Say a U.S.-based e-commerce company offers free domestic and international shipping. A domestic customer might prove more profitable than an international one because it's cheaper for the company to ship products across the country rather than around the world. 

Segment Customers

For meaningful profitability analysis, you need to segment consumers into groups rather than analyze individual customers. You can segment groups of customers or demographics based on age, location, socioeconomic status, or any other factor as long as you have enough big data, and that data is in the same location (more on this later). You might want to discover whether young customers produce more profit for your organization than older customers, for example.

Decide What to Do After Analysis

Customer profitability analysis is useless unless you do something with that data. Most successful enterprises analyze profitability to target their most valuable customer bases with promotions and marketing materials and increase profit further. After analysis, other companies might optimize their pricing strategies to reflect customer needs or further track customer behavior. 

If you're an e-commerce business owner, it's important to understand how your customers behave online. makes customer profitability analysis easy with its data warehousing integration tools for e-commerce. Now you can move data from sources to a warehouse and carry out profitability analysis through BI analytics tools with little or no code. The platform exists in a jargon-free environment, making it easy to use for any online retailer. Email to discover more. 

Why You Need a Single Source of Data for Customer Profitability Analysis 

Data is the bedrock of any profitability analysis. The more data you have, the more accurate your analysis will be. That data might exist in siloed systems that don't 'talk' to each other, making profitability analysis a fruitless exercise. 

If you own an e-commerce company, you might keep data in relational databases, transactional databases, SaaS tools, social media platforms, and customer relationship management (CRM) systems. By creating a single source of data, profitability analysis suddenly becomes easier. That involves moving data from disparate sources into a single location, such as a data warehouse, allowing you to run that data through business intelligence (BI) tools. From here, you can start to analyze profitability and produce real-time insights into your customers. 

The problem is, moving data to a warehouse can be a challenge, especially if you lack coding and data engineering experience. The process requires building complicated 'data pipelines' that require programming skills many enterprises, especially smaller e-commerce companies, don't have. 

There are also issues surrounding data governance when moving data between different locations. Many e-commerce companies that handle customer data from the European Union, European Economic Area, or the United Kingdom have to abide by GDPR, which lays down strict regulations for data sharing. Breaking any of these regulations can result in a fine of up to 10 million Euros or 2 percent of a company's annual turnover, whichever is higher. For e-commerce organizations that deal with customers in California, the California Consumer Privacy Act (CCPA), similar to GDPR, applies. 

Why Use a Data Warehousing Integration Tool for Customer Profitability Analysis?

Data warehousing integration tools like make it easy to move data from siloed sources to a data warehouse like Snowflake or Amazon Redshift. You can then run that data through the BI tool of your choice and execute customer profitability analysis. Data warehousing integration platforms use two main methods to move data from one location to another:


Extract, Transform, Load (ETL) is a data integration technique that extracts data from the tools used in your e-commerce business, cleanses and transforms that data into an appropriate format for customer profitability analysis, and then moves the data to a warehouse of your choice. 


Extract, Load, Transform (ELT) is similar to ETL but reverses the 'transform' and 'load' parts. It extracts data from sources and loads it to a warehouse before transforming it into a format for profitability analysis. This technique might prove beneficial if you have lots of data you want to run through customer analytics tools.

How Helps With Customer Profitability Analysis is a data warehousing integration solution designed for e-commerce companies like yours. It removes all the pain points associated with moving data for customer profitability analysis by carrying out fast ETL and ELT without lots of code.'s pre-built native connectors transfer data from sources to a warehouse without any fuss, helping you run data through BI analytics solutions and analyze profitability in your business. 

As well as ETL and ELT, carries out other data integration methods that might prove useful for your e-commerce brand.


ReverseETL moves data from a warehouse back to an operational system like a CRM or other e-commerce-related tool. 

Change Data Capture

Change Data Capture (CDC) syncs two or more databases in your e-commerce business so you can track changes made to those databases in real-time. carries out super-fast CDC.

Other benefits of include world-class customer service, simple pricing, and a simple drag-and-drop interface that makes data integration a piece of cake. also helps you comply with data governance regulations when moving data, such as GDPR and CCPA. is a data warehousing integration platform with deep e-commerce capabilities. Use it to move e-commerce data from your sources to a data warehouse for customer profitability analysis and improve pricing and promotions in your enterprise. Schedule a demo now and see how can revolutionize e-commerce.