Definition

Contributor(s): Tim Ehrens

In marketing, customer lifetime value (CLV) is a metric that represents the total net profit a company makes from any given customer. CLV is a projection to estimate a customer's monetary worth to a business after factoring in the value of the relationship with a customer over time. CLV is an important metric for determining how much money a company wants to spend on acquiring new customers and how much repeat business a company can expect from certain consumers.

CLV is different from customer profitability (CP), which measures the customer's worth over a specific period of time, in that the metric predicts the future whereas CP measures the past.

CLV is calculated by subtracting the cost of acquiring and serving a customer from the revenue gained from the customer and takes into account statistics such as customer expenditures per visit, the total number of visits and then can be broken down to figure out the average customer value by week, year, etc.

But the process is more nuanced than that. By concentrating on what a customer has previously spent, companies neglect how their marketing or advertising practices have changed over time, resulting in new customers who behave differently than old ones. CLV should never be determined by dividing the total revenue by the number of total customers, since this is too simple a calculation and does not factor into how long some customers have had a relationship with the company. Changes to any of these strategies, as well as any shifts in a company's customer base as a whole, in the future will prevent companies from depending on past CLVs to predict upcoming ones.

Common ways of calculating a company's CLV include the following:

Average revenue per user: Determine the average revenue per customer per month (total revenue ÷ number of months since the customer joined) and multiply that value by 12 or 24 to get a one- or two-year CLV. This approach is simple to calculate but does not take customer behavior into account or changes over time, either in customers' preferences or company strategy.

Cohort analysis. A cohort is a group of customers that share a characteristic or set of characteristics. By examining cohorts instead of individual users, companies can get a picture of the variations that exist over the course of an entire relationship with groups of customers. Factors such as market changes, seasonality and the introduction of new products, competitors or promotions could skew cohort analysis.

Individualized CLV. Companies not interested in broadly calculating CLV often focus on determining the total value of customers by source, channel, campaign or other mediums such as coupons or landing pages on a company website. This could mean comparing CLVs as obtained through social media advertising against those from other digital marketing tactics, for example, with a focus on whether company resources are being efficiently spent.

The CLV can affect many different areas of the business since it is not focused on acquiring many customers or how cheaply those customers can be obtained but, instead, emphasizing efficient spending to maximize customer acquisition and retention practices. Customer segmentation can affect CLV in that some groups of customers might be more highly valued than others.

This was last updated in July 2015

### 1 comment

Send me notifications when other members comment.
How does calculating the customer lifetime value impact your marketing, product development, customer support, sales and other internal processes?
Cancel

## File Extensions and File Formats

• ### Reddit and the aspiring data scientist

For amateur data scientists, Reddit provides the opportunity to post about personal projects, chat with like-minded people and ...

• ### Talking Data: AI advances and the MIT Startup Exchange

The Talking Data podcast team discusses some of the MIT startups that are making advances in AI and natural language processing.

• ### Tableau BI gets Extensions API in version 2018.2 update

Tableau's BI software sees general release of a 2018.2 update with an API for dashboard extensions, while a 2018.3 beta adds more...

## SearchDataManagement

• ### Chief data officer skills tested by AI tech blitz

A reporter's notebook from a recent MIT symposium provides insights on chief data officer needs, as the AI wave starts to hit ...

• ### Open source database software finally gets down to business

Once used primarily in web applications, open source databases are finding a place in more mission-critical business systems -- a...

• ### Open source RDBMS uses spurred by lower costs, cloud options

Open source technologies have become more capable alternatives to mainstream relational databases for cost-conscious users -- and...

## SearchSAP

• ### SAP S/4HANA Cloud update adds functionality for two industries

SAP focuses on manufacturing and professional services with the new features it's adding to S/4HANA Cloud. The enhancements are a...

• ### French transit develops chatbot with SAP Conversational AI

The transit system in the Paris metropolitan area is tackling an AI-driven chatbot project to create an easy way for riders to ...

• ### Renewed push for Business One could boost SAP SMB strategy

SAP has strived to dispel a reputation for pricey, hard to deploy ERP with aggressive marketing and products for small businesses...

## SearchOracle

• ### Oracle Autonomous Database Cloud gets transaction processing

Oracle launched a transaction processing version of Autonomous Database, a cloud-based platform that automates configuration and ...

• ### The future of SPARC/Solaris is cloudy -- in multiple ways

Cutbacks by Oracle have put the future of SPARC and Solaris in doubt, but the vendor says it's still committed to the ...

• ### How Oracle DBA responsibilities change with Autonomous Database

Oracle's Autonomous Database automates basic tasks of database administrators. That may put some DBA jobs at risk, but many will ...

## SearchAWS

• ### Compare EKS pricing to other managed Kubernetes services

With Elastic Container Service for Kubernetes now available, enterprises can weigh the cost benefits of the service. Dig into the...

• ### AWS IoT Analytics churns device data into insights

To tap into the business value of IoT data, organizations first need the right set of tools. Compare these AWS analytics services...

• ### Amazon Sumerian an experimental service with enterprise potential

AWS' foray into virtual reality and 3D apps simplifies certain tasks for developers, but the vendor could struggle to find an ...

## SearchContentManagement

• ### Box AI, workflow automation strategies about to unfold

Box is set to reveal new AI and workflow automation tools to add to its cloud content services platform -- technology seen as key...

• ### Office 365 SharePoint Online features raise CIO concerns

Most of Office 365's products can help solve specific challenges facing CIOs, but they also seem to compete directly with some of...

• ### Content services platforms are the new incarnation of ECM

A tribal council is preserving British Columbia's native languages with the help of a newer type of content management platform ...

## SearchSalesforce

• ### Einstein artificial intelligence leaves headroom for AI tools

Einstein AI shines, but sometimes Salesforce customers customize their cloud with additional AI tools in hopes of launching sales...

• ### Sales enablement tool uses AI to hone pitches

Sales enablement AI goes beyond Einstein lead scoring as Brainshark applies sentiment and other analyses to practice videos that ...

• ### Salesforce marketing automation tools close the data divide

Marketing automation CEO offers tips on bringing together siloed data, spotting sales trends, analyzing sales funnels and ...

Close