Making Customer Lifetime Value Real...customer interactions (from customer service to advertising) and improving the customer experience, which can potentially create value across

A Forrester Consulting

Thought Leadership Paper

Commissioned By Pitney Bowes

December 2015

Making Customer

Lifetime Value Real

Table of Contents

Executive Summary ........................................................................................... 1

CLV Shapes Customer Strategies ................................................................... 2

The Challenges Of Complexity ......................................................................... 4

Real CLV Moves Companies To The Next Level ............................................ 5

Key Recommendations ..................................................................................... 9

Appendix A: Methodology .............................................................................. 10

Appendix B: Supplemental Material .............................................................. 10

Appendix C: Endnotes ..................................................................................... 10

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1

Executive Summary

The age of the customer is forcing firms to reconsider what

really fuels their business — their customers. Customers

now are more mobile, consume more reviews, and buy

more online than ever before. Companies must respond by

becoming customer-obsessed.1 Marketers must identify

their best customers instantly and react “in process” with

contextual interactions to grow customer profitability. To do

this, firms must measure, analyze, and optimize key

indicators of customer growth in order to find triggers that

increase the value of customer interactions and revenues.

They must also determine how best to use these indicators

at the time of interaction.

Enter customer lifetime value (CLV), a predictive yet static

indicator of customer profitability, used to aid firms in their

strategies for customer acquisition, targeting, and retention.

With data growing exponentially and firms having access to

this data in real time, CLV has an opportunity to reinvent

itself as a dynamic, living metric that comprises static

quantitative data updated with qualitative customer

information and infused with more accurate real-time

marketing, social, and transactional data. This new “real

CLV” (rCLV) will help firms redefine the CLV metric as one

that is both more accurate and more agile, thereby allowing

marketers to increase the precision of their targeting efforts

and empowering customer experience professionals to

connect with customers through more relevant interactions.

Forrester Consulting conducted a study commissioned by

Pitney Bowes to survey business professionals on their use

of CLV and introduce them to the concept of rCLV, defined

as a living model that calculates the value of all interactions

that a customer took — including transactional (such as a

purchase or service request) and non-transactional (such as

a product review or brand advocacy on social platforms).

Utilized properly, rCLV becomes not only a financial marker

but also a way to prioritize and inform the right experiences

for the right customers. Forrester conducted two studies: 1)

a quantitative survey of 120 business professionals involved

in customer data and analytics in the United States at

companies of 1,000 employees or more and 2) a qualitative

interview study of six customer data and analytics decision-

makers.

KEY FINDINGS

Forrester’s study yielded the following key findings:

› Companies see the value in CLV. Companies use CLV

to improve their customer retention and acquisition

strategies, increase customer engagement, and improve

customer loyalty. Companies in the survey indicated that

CLV strategies came from the executive level, and the

various execution and maintenance roles were filled by

various functions. Marketing is the glue in executing and

using CLV insights to engage the right customer.

› CLV doesn’t come easily. Despite progress in current

CLV strategies and results, survey respondents struggle

to create, manage, and activate the insights they derive

from CLV. This is due to several factors — from creating a

consistent, robust data set to helping others in the

company understand and feel comfortable using insights

derived from CLV. But, most importantly, organizations

using CLV are missing opportunities to use CLV to help

define customer moments that optimize the revenue

cycle, which happen both in context and in real time.

› rCLV enhances how brands value and prioritize

customers. Adding qualitative customer information and

accurate real-time data from social media, transactions,

and content searches to the existing CLV formula

enriches the context and the immediacy of CLV. This

gives marketers more information that they can put into

action to engage customers at the right time and to

maximize financial returns. The definition of rCLV shared

with study respondents resonated with them; they think

that combining transactional and behavioral data will lead

to more relevant engagement with the right customer in

real time.

CLV has an opportunity to reinvent itself as

rCLV — a dynamic, living metric that is updated

with qualitative customer information and more

accurate marketing and transactional data.

2

CLV Shapes Customer Strategies

The age of the customer is a heady time for marketers. As

firms realize that customer obsession is key to competitive

advantage, they turn to marketing to help drive obsession

and to truly understand and engage their customers.

Showered with attention and budgets, marketers have been

empowered to drive change in their company’s technology,

marketing, and research organizations. But along with those

riches comes the need to ensure that the allocated

resources are used wisely and profitably. To do this,

marketers must enter a dangerous and difficult land — the

land of data analysis and prediction. The biggest challenge

they face in this quest is forecasting which customers will

yield the most profitable revenue in return for the investment

of scarce marketing and customer experience dollars.

Customer lifetime value (CLV) stands out as a predictive

approach because it brings profitability into the picture. CLV

is a complex, powerful metric that gives firms, and specifically

their marketers, a way to understand the financial impact of

customer relationships over their forecast lifetimes.

Customers with a high propensity to buy or with high

revenue-generating potential may not always generate the

highest profit and vice versa. Revenue-based metrics mislead

marketing efforts because they focus on growth in isolation,

but contribution-based or margin-based models like CLV help

marketers create value across the customer life cycle.2 So,

CLV is gaining attention as a key metric for prioritizing

customer interactions (from customer service to advertising)

and improving the customer experience, which can potentially

create value across every phase of the customer life cycle. It

helps with tailoring sales efforts to prioritize long-term

relationships, directs marketing budgets, and helps craft

individual experiences across key customer touchpoints.

With the increased attention on CLV comes the realization

that there is vastly more potential to create a more complete

and timely picture of the customer opportunity. Companies

are thinking about how they can marry CLV calculations

with current trends and advances in big data and customer

analytics. They see the need to quantify and accommodate

critical new inputs, such as the value of being a Net

Promoter, the value of social interaction, and other more

qualitative customer information, to create a more complete

picture of the customer. The director of marketing programs

and customer loyalty at a global hotel chain realized this

when he spearheaded an effort to measure the full impact of

his loyalty program members:

“The clock starts when a customer joins loyalty, so

we don’t know what they might’ve spent before.

While we see good portion of the picture, we never

see the whole thing.”

FIGURE 1

Using CLV To Improve Customer Acquisition And Retention

Base: 120 customer data analytics professionals in the US (multiple responses accepted)

Source: A commissioned study conducted by Forrester Consulting on behalf of Pitney Bowes, August 2015.

“What business objective(s) is your company

targeting by using customer lifetime value (CLV)?”

Improve win-back 22%

Decrease cost to servecustomers

31%

Increase share of wallet 32%

Allocate budgets forlong-term planning

34%

Improve sales leadgeneration

40%

Increase customerengagement

54%

Improve customer loyalty 59%

Improve customeracquisition and retention

72%

“Which of these activities has your company been

able to achieve by using customer lifetime value?”

Improve win-back 44%

Decrease cost to servecustomers

65%

Increase share of wallet 66%

Allocate budgets forlong-term planning

66%

Improve sales leadgeneration

60%

Increase customerengagement

72%

Improve customer loyalty 62%

Improve customeracquisition and retention

64%

3

CLV already plays a significant role in shaping companies’

revenue strategies in a more holistic way, with 24% of

survey respondents ranking it among their top three

business metrics for informing decisions around their

company’s revenue plan. In the course of this study,

Forrester research uncovered several key elements of the

current CLV climate:

› Companies use CLV to improve customer retention

and acquisition strategies. Through the survey, we

found that 72% of respondents use CLV to drive customer

acquisition and retention strategies because it allows

firms to target based on potential profitability — having a

direct impact on their company’s financial model (see

Figure 1). This focus on acquisition and retention allows

firms to target the medium-value customers in the hope of

pushing them further along the value curve.

› A focus on CLV increases engagement and customer

loyalty. Forrester believes that pervasive, enterprise-level

loyalty strategies are rooted in customer knowledge and

deep insights about their relationship with the company.

The insights that CLV provides are a key part of that, and

survey respondents agreed. Seventy-two percent of

respondents felt they were able to increase customer

engagement by using CLV, 62% improved customer

loyalty, and 64% said they improved customer acquisition

and retention. In some cases, companies were even able

to beat their business objectives, thanks to their use of

CLV.

› Marketing leads the execution of CLV strategies. When

asked about the role that different departments in their

company play in developing CLV, respondents saw it as a

collaborative effort across functions, with marketing being

the executing force and being involved in every aspect of

CLV development. Fifty-seven percent of respondents

indicated that CLV must be directed by executive

management, who should define the strategy for and use

of CLV. Marketing works to establish the process for using

CLV as well as how to factor in all the metrics. Finance

provides expertise on the actual calculations and is often

the “maintenance team” once CLV has been adopted into

the analysis stream (see Figure 2).

› Overall, companies are satisfied with their CLV

strategy. Companies are generally satisfied with their

ability to increase CLV by improving customer service

delivery, engaging customers across different platforms,

and designing a superior customer experience. The

director of enterprise analytics at a major US retailer that

Forrester interviewed said:

FIGURE 2

Executive Management Plays A Large Role In Developing CLV

Base: 120 customer data analytics professionals in the US (multiple responses accepted)


“What role do the different departments within your organization play in

developing customer lifetime value (CLV)?”

Defining strategyfor use of CLV

Defining metricsthat calculate CLV

Data collection andmanagement of CLV inputs

End user ofCLV calculation

Don’tknow/NA

Executive management 57% 26% 18% 31% 4%

IT/data management 10% 25% 57% 21% 13%

Call center/CRM 12% 16% 32% 40% 26%

Service/field support 17% 20% 30% 42% 22%

Sales 17% 24% 30% 52% 12%

Finance 18% 50% 39% 28% 7%

Line-of-business operations 19% 22% 36% 40% 16%

Business intelligence/customer analytics

21% 32% 53% 25% 13%

Operations 28% 42% 43% 32% 3%

Marketing 29% 43% 37% 36% 6%

4

“We relate CLV to retention, acquisition, and

reactivation and how it works into campaign

management and customer personas — it’s all

integrated together.”

However, firms using CLV are also keenly aware that they

are only scratching the surface of CLV’s potential.

“We have a lot of data, and I’d be

lying if I said we were making great

use of it. For us, the main challenge is

having great data on customer

profiles but not being able to plow it

back into our marketing strategy.”

Director of marketing programs and customer loyalty, global

hotel chain

The Challenges Of Complexity

Customer lifetime value doesn’t come easily. Despite

current CLV progress, respondents struggle to create,

manage, and activate the insights they derive from CLV. A

single CLV calculation may capture a moment in time, but

more often it comes from disparate data over a period of

time and is used as a strategic forecast rather than an in-

process operational element. The complexity is enormous,

and survey respondents are aware of the challenges in

collecting and managing data, working for consistency and

usage in their CLV formula, and applying the results to

forecast future customer behavior. Specifically, firms:

› Don’t incorporate data across different sources.

Gathering, preparing, and normalizing data to feed the

calculation is a daunting task that involves various functional

roles with different priorities. Forty-five percent of

respondents listed collecting and managing required data

from multiple sources as a top three challenge in calculating

CLV. Furthermore, data from these sources may not always

be in an ideal form for CLV calculation. Standardizing and

reconciling data for consistency was a top three challenge

for 37% of survey respondents (see Figure 3).

FIGURE 3

Forecasting Future Customer Behavior Is A Major Challenge

Base: 120 customer data analytics professionals in the US


“What are the biggest challenges your organization faces in calculating customer lifetime value (CLV)?”

Rank 1 Rank 2 Rank 3

Segregating marketing and service costs toappropriate time periods

6% 6% 5%

Using the calculation to activate insights from CLV 4% 8% 10%

Minimizing the lag time in getting data from certainsystems or parts of the organization

5% 10% 8%

Including the influence of competitive factors 8% 7% 9%

Settling on a common definition of variablesacross the organization

13% 12% 9%

Understanding cost attribution at the customer level 10% 11% 13%

Standardizing and reconciling data for consistency andusage in the formula/model

13% 12% 12%

Collecting and managing required data from multiple sources, includingsales, marketing, service, operations, and eCommerce/digital

10% 16% 19%

Forecasting future customer behavior accurately 28% 16% 12%

5

› Fight to understand the cost attribution at the user

level. Being able to correctly assign the cost of a

customer’s journey through the buying cycle is critical to

calculating true value, and survey respondents in the

survey also had concerns about cost attribution at such a

singular level. Thirty-four percent ranked it as one of their

top three challenges).

› Fail to take action on CLV. When asked to choose the

top three obstacles preventing greater action on CLV, the

greatest portion of respondents (38%) said that current

CLV models don’t factor in non-transactional customer

behaviors and aren’t in real time, limiting the actions that

companies can take. Further, 36% indicated that gaining

the support and confidence of their colleagues also

prevented them from taking action on CLV, and 28% saw

the difficulty of incorporating CLV into sales, marketing,

and service plans. And, in an increasingly real-time world

for customer data, 29% see a challenge with CLV not

being a real-time or near-real-time metric (see Figure 4).

Companies that recognize these challenges should attempt

to position CLV in a more customer-centric way, which

requires investment in data discipline, strong cross-

functional collaboration, investment in data analytics

technologies, and the vision to use CLV to help inform and

prioritize the customer experience.

Real CLV Moves Companies To The Next Level

Once an enterprise overcomes the challenges of calculating

CLV and applying its insights, it is in a position to take its

proficiency in CLV to the next level. In the context of

exponential data growth and unprecedented levels of

access to this data in real time, firms have the opportunity to

reinvent CLV as a dynamic, living metric that is used in-

process and updated with qualitative customer information

and more accurate marketing and transactional data.

FIGURE 4

Companies Are Limited In The Action They Can Take Using CLV



“What are the most challenging obstacles preventing you from taking greater action

from customer lifetime value (CLV)?”


CLV calculations are too complicated 4% 3% 4%

The CLV model does not include certain key cost metrics 5% 7% 8%

Existing media partner and/or agency contracts prevent usfrom leveraging CLV to change budgets across

specific channels or campaign efforts6% 4% 9%

Determining how to take action on CLV insights 10% 4% 5%

The CLV model does not include certain key sales,marketing, or service activities

5% 9% 8%

CLV results differ from those coming from other analyses 11% 4% 8%

CLV takes too long to generate useful results and guidance 9% 6% 8%

CLV is not a real-time or near-real-time metric 7% 13% 9%

Incorporating CLV into sales, marketing (including media),and service plans is too difficult

8% 9% 11%

Gaining the confidence of colleagues and executivesin predictions/recommendations 10% 18% 8%

CLV does not take into account other customer behaviorsand actions, like motivations 13% 13% 12%

6

This study defined “real CLV” (rCLV) as a living model that

calculates the value of all the interactions of a customer,

and it includes the following:

• Transactional activities and associated data (such as

a purchase or service request).

• Non-transactional activities and associated data

(such as a product review or brand advocacy on

social platforms).

It is a metric that bridges the waning gap between

transactional and behavioral data, thereby enabling

companies to understand total customer value. An rCLV

model combines available data from transactional

databases (purchase behavior); accounting systems;

marketing databases (customer segment information); and

social data (social influence and engagement).3

As enterprises think about capturing, calculating, and taking

action on rCLV, there are several factors they must consider:

› Companies recognize the mutual benefits of CLV.

Metrics that help measure the value of a customer can

help a company understand and prioritize which

interactions best maximize that value. This is a potential

win for both sides: Companies can optimize the economic

benefit from a customer by offering them relevant

interactions and offers that increase wallet share, while

customers receive targeted solutions to their needs — all

based on rich data. CLV champions within a company are

seeking to share the potential power of CLV and to

position it in a more customer-centric way.

FIGURE 5

Companies See The Benefit Of Real CLV



“What do you believe are the greatest benefits from implementing a real

customer lifetime value (rCLV) solution?”


Identify the right channels to grow long-term customer value

2%

3% 6%

Identify customers that are not valuable and build strategies tomanage those relationships

4% 12%

Shorten the sales cycle for the most valuable customers 4% 4% 9%

Improve customer satisfaction scores across all customers 5% 13% 7%

More accurately allocate budgets over both the short run andfor long-term planning

9% 11% 7%

Use the analysis to provide compelling offers for each customer 10% 12% 6%

Use the analysis to create compelling content for each customer 15% 7% 7%

Gain a greater share of wallet from the most valuable customers 3% 13% 13%

Identify customers that have a high potential to growlong-term customer value

8% 13% 13%

Understand the complete potential value of each customerthrough their buying journey — beyond pure revenue

23% 3% 8%

Retain more of the most valuable customers 18% 14% 12%

1%

7

“There is a real shift [at my company]

to calling [CLV] our ‘customer health

score’ and using it differently, so it

gets more to the customer level.”

(VP customer experience, US travel management firm)

› Companies see the potential benefit of rCLV. When

asked what they believed to be the greatest benefits of

implementing an rCLV solution, 34% ranked an

understanding of the complete potential benefit of each

customer through their buying journey as one of their top

three benefits; for 23%, it was their No. 1 benefit.

Rounding out the top four benefits was retaining more of

their most valuable customers (44% put it in their top

three); creating compelling content (29%); and creating

compelling offers (28%) (see Figure 5). All of these

benefits point to companies’ desires to both understand

and act on what customers want and what they are willing

to buy.

› rCLV has its own challenges. Those challenges include

getting the rCLV calculation right and leveraging scores

across platforms for real-time interaction (see Figure 6).

All of the top challenges highlighted the difficulty of the

work, but when asked in a separate question how

confident they felt about identifying the most valuable

customers via rCLV analysis in real time, 50% of

respondents felt confident, very confident, or completely

confident.

› CLV professionals are making progress toward rCLV.

Thirty-seven percent of the customer analytics

professionals surveyed felt that rCLV is very or extremely

important to their organization, and in qualitative

interviews, CLV leaders talked about the progress they

are making in their organizations. One VP of customer

experience at a global technology company said: “Our

model had 42 factors from CRM and financial data, social

media, and voice of the customer surveys. We

FIGURE 6

Real CLV Has Its Own Challenges



“What are the challenges in calculating real customer lifetime value (rCLV)?”


Being able to assign a value to non-transactional interactions 5% 4% 12%

Changing the overall business strategy to focus on rCLV 5% 9% 10%

Training personnel (e.g., sales force and customer service) in howto use it effectively and how to communicate it to clients

7% 7% 13%

Being able to define strategies (e.g., best next offer, servicingtiers, dynamic pricing) that leverage the rCLV scores

4% 16% 13%

The complexity of the calculation of rCLV 15% 11% 7%

Selling the value of rCLV internally 8% 10% 14%

Investing in the right technology to enable rCLVmanagement and activation

15% 11% 8%

The ability to integrate the right data intothe rCLV calculation/model

23% 10% 8%

The ability to integrate rCLV scores into all of the criticalreal-time interaction platforms in sales, marketing, and service

15% 19% 13%

8

experimented over time to figure out what was interesting

and what could be moved out. We settled on things with

the most predictive value [so we could learn] at the

customer level what their lifetime value was, and whether

there was an opportunity to influence that (both for current

and past customers). In the end, it became a core part of

how marketing forecast their numbers and was eventually

adopted by finance over their own model because it used

things that finance didn't traditionally look at.”

The age of the customer is driving companies to evolve their

CLV strategy to get a more complete view of their customer,

their buying journey, and how that impacts the bottom line.

In order to make this leap and maximize the value of rCLV,

marketers and customer data analytics professionals need

to ensure they have the proper technology and processes in

place to effectively manage the necessary data,

assumptions, and algorithms. As the head of analytics for a

global hotel chain mused, “Knowing our highest-value

guests allows for more laser focus, giving 15% to 20% of

guests the best possible experience so they have a higher

propensity of coming back.” And that is something they can

take to the bank.

9

Key Recommendations

With data growing exponentially and firms having access to this data in real time, CLV has an opportunity to become a

dynamic, living metric that is updated (often in real time) with both qualitative customer information and more accurate

marketing and transactional data. This new, real customer lifetime value (rCLV) will help firms redefine the CLV metric

with more accuracy, allowing marketers to increase precision in their targeting efforts and empowering customer

experience professionals to engage customers with more relevant interactions. This ability will prove invaluable not

only for new customers but also, more importantly, for engaging existing customers more fully, more deeply, and more

profitably. To achieve this vison, companies must:

› Champion the cause of customer centricity. Use rCLV to broaden the scope of customer value management,

elevating its role from model building and campaign planning to devising customer-centric rCLV strategies. This

requires strong organizational design and tight cooperation between different roles — from marketing to

technology to finance.

› Develop even stronger discipline around data. Respondents to this survey saw the challenges in collecting,

reconciling, and structuring the data so that it can be used quickly and consistently to measure customer value

and, more importantly, act on it. Good data discipline will make rCLV a trusted and critical part of any customer

engagement strategy.

› Infuse predictive analytics in rCLV. rCLV must be considered as an “on the go” measurement, used to identify

potential high-CLV customers. Build on strong data discipline with incremental technology to run analytics, and

feed this in to a real-time (or near-real-time) insight model that informs actionable marketing and customer

engagement plans.

› Take actions on insights across functions. Tailor sales efforts to prioritize long-term relationships,

remembering that existing customers are potentially more valuable as they cost less to keep and provide more

revenue potential as their engagement with the brand deepens. Direct your marketing budget to target those

high-value customers, and use rCLV to help you find them and provide them with the best possible interactions.

› Make rCLV a reality. The best and most direct way to do that is to leverage technology and expert partners to

help make the complexity of feeding and caring for the CLV model less daunting. Start to collect, clean, and

normalize data that enables rCLV, and align technologies to ensure that data and calculations are conducted and

used in-process, in real time.

10

Appendix A: Methodology

In this study, Forrester conducted an online survey of 120 customer analytics professionals in the US; it also interviewed six

customer analytics professionals to evaluate their use of CLV and receptivity to the concept of rCLV. Survey participants

included marketing, customer experience, strategic planning and analysis, or technology managers and executives.

Respondents were offered a small incentive as a thank you for time spent on the survey. The study was fielded in August

2015.

Appendix B: Supplemental Material

RELATED FORRESTER RESEARCH

“Winning In The Age Of The Customer,” Forrester Research, Inc., April 6, 2015

“Navigating The Customer Lifetime Value Conundrum,” Forrester Research, Inc., June 3, 2011

Appendix C: Endnotes

1 “Winning In The Age Of The Customer,” Forrester Research, Inc., April 6, 2015

2 “Navigating The Customer Lifetime Value Conundrum,” Forrester Research, Inc., June 3, 2011

3 “Navigating The Customer Lifetime Value Conundrum,” Forrester Research, Inc., June 3, 2011

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Making Customer Lifetime Value Real...customer interactions (from customer service to advertising) and improving the customer experience, which can potentially create value across