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Why is everyone talking about CLV again?

Written by Alida

Published December 01, 2022

Focusing on Customer Lifetime Value can boost your long-term revenue and help you navigate a tricky economic environment, but as with every metric, context is key.


Customer Lifetime Value (CLV) has been around for almost half a century, yet it seems to have regained its luster in recent years. According to Forrester, the spike in CLV’s popularity can be attributed to the profitability priorities in budget conscious climates, pressure to demonstrate value in economic terms, and growing data management competence.

Conveniently, CLV packages all that data into a single number that can be benchmarked over time. The metric is elastic enough to be customized based on the idiosyncrasies of each economic sector and the specific needs of an organization.

In addition, CLV looks at revenue over time, so issues like retention and customer benefit become central. Lastly, with businesses dedicating a large portion of their budget to acquisitions, CLV brings attention to the fact more revenue is driven from existing customers rather than new ones.

Prioritizing CLV is bound to impact customer retention and, to a lesser degree, new customer acquisition. Furthermore, by segmenting those two cohorts of customers via demographic data and introducing goal-oriented variables to CLV, you can obtain valuable insights regarding how each group of customers behaves, say, boomers and millennials during the holiday shopping season.


How to use CLV as a KPI to align CX and business goals

Customer journeys have gone through more changes in the last couple of years than in the decades before. Companies are struggling to figure out how to create and maintain value at every step of the customer journey. Given today’s economic climate, identifying unnecessary costs and allocating funds more effectively are key to successfully navigate CX.  It turns out CLV is particularly adept at figuring it out.

Alida’s CX gurus Amy Ko and Paul Parsons along with Kevin Kwong, Principal of Value Engineering, recently hosted a webinar focused on identifying what influences CLV, and how to make the most of it when drafting or boosting your customer’s journey performance.


Pick the right CLV formula

The obvious starting point is how to define CLV. The answer is simple: The worth of a customer relationship to a business. To be more precise, dollars generated from a customer over a period of time. This is the formula to calculate that number:


[annual revenue per customer] x [customer relationship in years] - [customer acquisition cost] = Simple CLV


A more traditional formula factors in inflation (under discount rate) and it is more effective at measuring CLV long term:


         [gross margin] x [retention rate]       =      Traditional CLV


1+ [discount rate] - [retention rate]


Retention is measured differently depending on industry, but goes back to the intention behind the introduction of a factor into the equation: Is it something your organization can make an impact on?

In turn, the predictive CLV model is based on averages:


                                           [transactions per month] x [AOV] X [avg gross margin] x [avg customer lifespan in months]           =      Predictive CLV



[customers at end of period]


Cost of goods sold encompasses more than customer acquisition costs and constitutes a good example of incorporating relevant factors into the formula. For example, in tech, training and implementation are considered costs to sell your goods and their inclusion is certain to impact CLV.

There are further formulas not included here which consider additional nuances to calculate CLV. Selecting one depends on what your goals are and what data is available to you. For example, in non-tangible services with elongated acquisition latency and lengthy consumption (insurance, finance, higher education), factors like tenure and maintenance may carry more weight.

Another nuance to consider is the lifetime of a customer. Think of a business that has seen significant changes in recent years. It may be more useful for the organization to think about a customer’s lifetime as the last five years, as opposed to a ten-year tenure or longer.


Value drivers

There are three key value drivers that bring these CLV formulas into the real world and turn them into tangible and verifiable data:

  • Increase revenue per customer: Understand customer’s buying preferences, identify new products or cross-sell opportunities, and offer a high quality customer experience.
  • Increase gross margin: Identify customer sentiment towards pricing to find opportunities to increase revenue and reduce the cost to serve. Determine areas of low customer value to reduce the costs of goods.
  • Reduce customer churn: Determine why customers stay and what drives them to leave; make them feel part of the solution and increase engagement by acting on direct customer feedback; identify successes and pain points. Prioritize and implement solutions using measurable engagements throughout the process.


What CLV means for CX and how to influence it

Customer Lifetime Value is a great way to prioritize areas where businesses can drive the most impact. With that in mind, the best thing you can do with CLV is segmenting and prioritizing your customers: You want to identify what a high value customer looks like, who they are and what attributes they have. 

This approach enables you to:

  • Focus your efforts on those high value profiles and retain them.
  • Identify customers that look similar to high value customers and nurture them until they fit the profile.
  • Identify significant costs in the customer journey and explore ways to improve margins in those areas.

CLV as a ‘north star’ metric is at its best when used to take a snapshot of your business’ wellbeing and to make strategic decisions at a high level. CLV, however, needs to be used directionally and with context in mind: are you solving a real need, or is it a problem you think your customers have?


Customer journey mapping

Customer journey mapping is an exercise all businesses should conduct in order to identify critical touchpoints throughout their customer’s journey. Mapping can help you establish listening posts for feedback collection at critical points to segment customers, combat survey fatigue, and ultimately understand the variables that impact value perception.

Intrinsically linked to feedback collection are close loop actions, intended to sustain and extend a customer’s lifetime with your business:

Closing the inner-loop: Businesses take specific action as a response to feedback such as surveys.

Closing the outer-loop: Businesses take action on a systemic level.

When closing the loop, a best practice is to capture metrics and KPIs and use them as benchmarks to find out whether your business is successful. Through measuring and benchmarking over time, businesses are able to appreciate the impact closing the loop can have in a customer’s lifetime.



While an obviously valuable concept, CLV shouldn’t be used as a replacement for your key metrics. Principal CX consultant Amy Ko explains: “If you already have a set of metrics to measure customers’ temperature, stick to what you’re already doing. Explore CLV as an addition to your existing ones.”

Value Engineering Principal, Kevin Kwong, believes “metrics are important because we can’t improve what we can’t measure, but we shouldn’t be measuring CLV for the sake of it.” Kwong also warns against getting too deep in the weeds by adopting “vanity metrics” that don’t actually impact CLV. The best way to avoid falling in this trap is context awareness.


How Alida supports CLV

CLV is one of Alida’s key drivers. Alida’s products are uniquely suited to populate CLV equations with data.

  • Surveys and Touchpoint: Capture real-time customer insights about advocacy and brand affiliation so you can increase referrals and loyalty. In addition, with Touchpoint you can collect feedback in the moment, while a customer is online or in your app, to get more responses in context.
  • Text analytics: Analyze large amounts of unstructured data to reveal trends in CSAT, sentiment, and churn. Bring to the surface common loyalty themes from large quantities of data. Recognize negative sentiment in voice and text feedback to take quick action.
  • Community: Progressively profile customers to understand how advocacy differs between segments.
  • Video: Use live and asynchronous video feedback and community forums to learn about loyalty drivers, churn drivers, and ways to deliver more value throughout the lifecycle. Invite detractors into a dedicated insight community or a video focus group to identify effective ways of resolving issues and drive more value. Test strategies across multiple channels and segments before implementing them.
  • Actions: Automate surveys and communications based on customer milestones. Automate actions on any customer contact to effectively close the feedback loop. Trigger actions to respond immediately and make your customer feel heard for better engagement.
  • Customer Journeys: Visualize the health of a customer journey as a whole and at key touchpoints to identify the root cause of issues and prioritize improvement efforts. Monitor performance at key journey points to identify and remove any roadblocks to revenue growth.

Watch the CLV webinar in its entirety and acquire even more insights here.