WHITE PAPER Great ROAS, Terrible Results...GREAT ROAS, TERRIBLE RESULTS: THE CASE FOR CLV-CENTRIC...

Great ROAS, Terrible Results:The Case for CLV-Centric Advertising

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TABLE OF CONTENTS

CLV: Three Key Things To Remember

Choosing An Investment Timeframe

The Story So Far: An Evolution Of KPIs

The Importance Of Incrementality

Great ROAS, Terrible Results

Assessing Customer Value

Brand vs. Non-Brand Forecasting

Making CLV Actionable

Why Change Management Matters

03

12

05

14

08

15

11

19

21

GREAT ROAS, TERRIBLE RESULTS: THE CASE FOR CLV-CENTRIC ADVERTISING 2

Few retailers doubt the effectiveness of performance

advertising. From humble origins to something more

complex, it remains a preferred tactic for advertisers

the world over. The reasons why remain simple.

Retailers can target shoppers better. And they can

measure their campaigns more accurately.

But as campaign expectations have evolved, so have

the metrics which determine success.

This paper explores the latest step on that

measurement journey: Customer Lifetime Value (CLV).

It doesn’t matter how big (or small) your organization

is. In a hyper-competitive environment, optimizing for

CLV helps you hold your ground against giants like

Amazon.

At Crealytics, we’ve incorporated CLV into our

optimization strategies for over 10 years. We

discovered that advertisers who focus on long-term

revenue goals make about five percent more revenue in

the first 12 months, and can triple that number when

they look over a longer time horizon.

INTRODUCTION

3GREAT ROAS, TERRIBLE RESULTS: THE CASE FOR CLV-CENTRIC ADVERTISING

Return on Ad Spend [ROAS] remains the go-to

metric for retailers seeking to evaluate their

performance marketing campaigns. Most bidding

systems encourage it: top-line revenue is easy to

measure, and easy to justify.

Smarter retailers know that optimizing for revenue

proves efficient but ineffective.

They can unlock a three-dimensional view of

performance, but only by incorporating margins, returns

and new customers into their approach. Achieving this

requires co-operation across all departments.

01

02

New customers generate more revenue than

existing ones - which is why smarter retailers

optimize for customer lifetime value (CLV). This

entails adding the profit they make over a

customer's “lifetime” (typically 12 months) to the

profit of their first purchase. Choosing CLV over

ROAS means switching from short- to long-term

revenues. It demands more than pure marketing

execution. You will need stakeholder alignment, as

well as a willingness to sacrifice profits in the here

and now in exchange for future gain.

03

IF YOU READ ANYTHING, READ THIS


Today’s retailers enjoy unparalleled measurement

finesse. Access to - and aggregation of - data across

one’s organization bears little resemblance to the early

days, when data quality remained low.

As one of the earliest metrics, Cost Per Order (CPO)

treated everything equally. It didn’t matter what the

order was - cheap socks and expensive sweaters both

received the same value, regardless of the large gap in

margins.

Revenue soon replaced orders as a better indicator

of value, as it empowers decision makers to optimize

campaigns based on previous earnings. They can

thus allocate more budget to a campaign that drives

higher revenues (sweaters) vs. lower ones (socks).

Thousands of retailers continue to optimize for

ROAS. However, its sole focus on top-line revenue

makes it a one-dimensional KPI. One, inescapable

truth continues to diminish ROAS' value: it excludes

other factors that paint a more robust and accurate

picture of performance.

THE STORY SO FAR: AN EVOLUTION OF KPIs

CPO: The lowest rung on the ladder

Return on Ad Spend [ROAS]: Still popular, but one-dimensional


Incorporating margin data into measurement represents

a big step up from Return on Ad Spend. Retailers who

know the order, revenue and margins involved can power

their campaigns more effectively.

As an example, if a retailer sells a laptop for $1000 per

unit, and each has a 10% margin [i.e. $100], they can

then reinvest this margin back into their bidding system.

Once you factor in profit margin, selling laptops at a

lower efficiency rate will likely yield more value to the

organization than selling pencils at a high ROAS (unless

you're selling very expensive pencils) It’s a much healthier

way of looking at search, albeit only in the present. While

close to an ideal solution, ROI still misses a key ingredient

in future-proofing your customer acquisition

campaigns: It fails to reveal performance

advertising’s role in acquiring new customers [who

bring more value to a business than existing ones].

Today, optimizing for profitability is no longer

enough. Acquiring new customers doesn’t just yield

value in current transactions, it also incorporates the

value of future transactions. CLV-centric marketers

add the estimated value of future purchases to the

current margin: resulting in a more accurate view of

new customer value. Let’s say the dresses you sell

attract more new customers than shirts. Even if

shirts have a higher margin, the dresses will still

receive more budget.


ROI: Measuring performance by profitability

GREAT ROAS, TERRIBLE RESULTS: THE CASE FOR CLV-CENTRIC ADVERTISING

Customer Lifetime Value (CLV)

6

The reason? Over a longer period of time, those dresses will generate additional purchases and, subsequently, larger

lifetime profits.

When you optimize for CLV, you focus on specific subsets of new customers brought into the fold. You then target your

ad spend on the most valuable ones.



+9%

PERIOD 0

HIGH MARGINMargin differences might make lower-priced products more attractive than high-priced products

Product categories differ in their return rates: the lowest return rates are favorable

Only by targeting first-time and loyal customers can you achieve maximum long-term value

LOW RETURN RATES

NEW CUSTOMERS

REVENUE

PERIOD 1

MOST BUSINESSES FOCUS ON REVENUE: …BUT WHAT THEY REALLY WANT IS

7

Even though marketers have long known that ROAS-based KPIs only tell a partial story, they persist in using it. Why is

that? Data access plays a big role. The siloed nature of most retail organizations means that it’s sometimes difficult to

unlock new customer identification, costs associated with selling, and CRM data. Furthermore, most analytic and

bidding systems emphasize ROAS as an ideal metric, largely because it can be easily measured and adjusted.

Most automated bidding solutions optimize towards a fixed ROAS efficiency target, focusing on achieving efficiency

across products, geographies, or defined segments. To drive as much revenue as possible, they seek to display a similar

ROAS, regardless of differences in markets or audiences. In the event that, say, LA displayed a much higher ROAS than

Atlanta, a bidding system would reallocate the latter’s budget to achieve more revenue.

If you asked a bunch of performance advertisers to look at the below chart, they’d acknowledge the automation’s job

well done:

GREAT ROAS, TERRIBLE RESULTS


NYC

2.2 2.12.4 2.22.2 2.12.0 2.02.2 2.3

ROAS

LA SF ATL CHI

KPI TOP 5 CITIES TOP 5 BRANDS

8

But factor in new customer recognition, margins, returns and cancellations, and you’ll notice that things start to lose

balance. Because your bidding system chases down the cheapest available revenue, it comes from the revenue sources

you don’t necessarily want: existing customers, low margin products, high return rates.

What happens if you factor in repeat purchases accrued over time? First, we measured each new customer's initial

purchase for six months. We then tracked their behavior for a further six months to determine all additional revenue

generated beyond their first purchase.

Accounting for margins and returns changes the game. What seemed balanced when viewed through a ROAS lens

breaks down completely once you measure for long-term profitability.



0.4

0.40.4 0.4

0.8

0.8

0.2

(margins, returns)

(margins, future margins, returns)

-0.1

-0.1

-0.2

-0.3

-0.3

-0.1 -0.1

0.2

0.2

0.2

0.20.10.2

0.3 0.5

-0.4 -0.4

0.50.3-0.4 -0.4

0.1

-0.1

ROI

CLV ROI

9



REVENUE

1,000

300

330420

300

580

280

10

RETURNS COST OF GOODS SOLD

MARGIN CLV FUTURE MARGIN

AD SPENDMEASURED WITH ROAS MEASURED WITH CLVMEASURED WITH ROI

ROAS: 33% ROAS: -15% CLV: 76%

Only Customer Lifetime Value can attune you to the full picture. It unlocks the true value of each campaign with

technicolor accuracy:

10

Many retailers still view performance marketing as a whole,

rather than making a distinction between branded terms

(low incremental value) and non-branded search terms

(high incremental value). ROAS-driven campaigns mask

this reality. By targeting easy-to-achieve branded search

profits, they subsidize weaker, non-branded terms.

Try deducting non-incremental sales. You'll see how limited

the contribution of branded search terms really is. Only

when non-branded revenue has its own, separate targets

can marketers start managing both groups in a profitable

way.

Forecasts split brand from non-brand. CLV helps you reflect

long-term investment and growth strategies - for both

customer acquisition and marketing budgeting. You can

solve for channels with different revenue curves - rather

than assigning blanket targets.

BRAND VS. NON-BRAND FORECASTING


PPC BRAND NON-BRAND:

PLA & TEXT ADS

Revenue Revenue

Budget BudgetGro

wth

pot

entia

l

Grow

th p

oten

tial

The CLV calculation has the biggest value for Non-Brand: it gives us investment boundaries; we do not need to look at blended numbers anymore.

Brand is the most efficient channel but incrementality is questionable.

Growth potential is high but more costly in ROAS.

FORECAST FOR NON-BRAND

11

A customer’s “lifetime” spans between first order, 12, 24 and even 36 months. Deciding which timeframe you want to

optimize for will deliver varying levels of profitability in the short term.

CHOOSING AN INVESTMENT TIMEFRAME


INVESTMENT PROFIT OVER TIME

Maximize profit on first order

Optimize 12 month profit

Optimize 24 month profit

2.0

-1.0

-3.0

1st ORDER 12 MONTHS 24 MONTHS

3.0

2.0

1.0

4.0

5.0

8.0

12

So, if you want to be profitable after 12 months you

would:

CHOOSING AN INVESTMENT TIMEFRAME


Your choice of time frame hinges on how long-term you

want your organization's focus to be. In this hypothetical

scenario, your customers generate the following:

12 months 24 months 36 months

an average of 1.8 purchases



with a profit of $30



ADD 12 MONTHS’ PROFIT TO EACH PURCHASE MADE BY A NEW CUSTOMER:

AD SPEND

AD SPEND

$300

$300

$280

$280 $580

$300

MARGINNEGATIVE ROI, UNPROFITABLE

TOTAL PROFIT:

FUTURE PROFIT:

POSITIVE CLV AFTER 12 MONTHS

(10 NEW CUSTOMERS X CLV $30)

MARGIN

13

In order to develop a clear view of the lifetime value of

your customers, you need to understand the varied

touchpoints that impact a purchase decision. Most

retailers look to their MTA (Multi-Touch Attribution)

systems to guide their thinking.

But assigning touchpoints is only half of the story. The

other half is understanding the marginal contribution of

each media tactic. What is the marginal lift that each

channel can create for your business?

A/B testing supplies the genetic makeup of a customer

conversion. It shines a spotlight on each media type’s

contribution, and should form the cornerstone of any

investment decision. Without clean data any future

investments can go pear shaped; and the longer the time-

frame you seek to optimize, the wonkier your potential

results.

To illustrate, Crealytics ran the below test with a high-

volume, fast-fashion retailer. A miscalculation in

incremental value saw expected profit fall like a house

of cards:

THE IMPORTANCE OF INCREMENTALITY


-50

-50

100

100

45

45

65

65

52

28

2

-24

EXPECTATION

REALITY

Investment Revenue NC Value ProfitIncrementalvalue

assumedincrementality:

80%

actualincrementality:

40%

Margin afterreturns

14

Pursuing CLV leads to two important questions: How much

is the average customer worth to my business? And what

percentage of value do my top customers bring to it? The

clues, revealed through your CRM, will better inform your

investment strategy.

A customer cohort analysis - in other words, determining

shared characteristics of those who’ve bought your

products - will lead the way. And the longer the transaction

history, the better the calculations.

At Crealytics, our BI team uses the past five years’ of a

retailer’s transaction data, along with (new or existing)

customer IDs. We evaluate how much each shopper comes

back per channel, along with how much profit they

generate over set amounts of time. That way, profits will

always incorporate future cost and ad spend.

New customer values vary depending on their type, so

different retailers might project different values

depending on their vertical. You can also get more

granular, and base value on initial basket composition,

demographics and payment details.

How dependent is your company on specific cohorts?

After all, you’re optimizing for long-term profits. You

want to ensure you spend your money targeting the

most valuable, most loyal customers. With your CRM

data under the microscope, you can determine what

percentage of shoppers are responsible for the bulk of

your revenue. Segmenting them via Recency, Frequency

and Monetary Value (RFM) can help you find an answer:

ASSESSING CUSTOMER VALUE


Attributing Recency, Frequency and Monetary labels for each of your customers will help you to evaluate where each

of them falls in terms of overall value. Assigning each variable its own scale (for example, dividing Recency into 1, 2

and 3; from least to most value) will help you ascertain the value of your customers.



FREQUENCY RECENCY

MONETARY VALUE

How many times did your customer buy a product within a specific time frame?

Someone who purchases all the time has a better chance of returning than a sporadic buyer.

When did your customer last make a purchase?

Someone who bought a product recently carries greater potential for doing it again.

How much does your customer spend within that time frame?

Someone who spends more is more likely to return to you vs. a customer who spends less.

16

FREQUENCY MONETARY VALUE RFM SCORERECENCYCUSTOMER

Customer K 3 3 2 8

Customer L 3 3 1 7

Customer F 2 1 3 6

Customer O 2 2 1 5

Customer J 3 2 1 6

Customer D 1 2 1 4

Customer B 3 1 1 5

Customer H 1 1 3 4

Customer C 2 3 2 7

Customer E 2 1 3 6

Customer I 2 3 1 6

Customer A 1 2 1 4

Customer M 3 2 1 6

Customer G 1 1 2 4

Customer N 3 1 1 5

Customer P 1 2 1 3

To illustrate, a customer who has not made more than one purchase over a four month period might receive a “2” for

Frequency and so on:



More often than not a hefty slice of revenue comes from a

small portion of customers. Crealytics’ Business

Intelligence unit discovered that just 3% of U.S. zip codes

drive an astonishing 50% of repeat purchases. What does

that 3% have in common?

Maybe they come in through a certain channel, or

through a specific promotional activity. Once you

understand who they are, you can ramp up your

marketing efforts to target this group in particular.



3% OF US ZIP CODES DRIVE OVER 50% OF REPEAT PURCHASES THREE STEPS TO CRM SUCCESS

Analyze which customers contribute the most

Find similarities in order to identify them early

Ramp up your marketing efforts to target those customers

01

02

03

97%$90

$10

$1703%

48%

52%

ZIP Codes CLV AverageCLV

RestCLV

Top ZIP

TOP

REST

Sales

18

Customer tracking also plays an important role when optimizing for CLV. Remember- most retailers still ingest revenue

figures into their bidding systems. Making CLV actionable requires you to ingest the margins of products you’ve sold

(excluding order-related costs like shipping and packaging).

MAKING CLV ACTIONABLE


Luxury dress

Purchase history, returns, COGS, warehouse cost, etc.

New CustomerESTIMATED TRANSACTION VALUE

ESTIMATED TRANSACTION VALUE

POST PROCESSING(APPROX. 24 HOURS)

REAL-TIME TRACKING TAG

CONVERSION IMPORT

$200

+$48

Transaction value:Higher CLV, low returns

Attribution & incrementality: Cart abandoner

This is added to the real-time estimated value

+20% +80%

19

You should also know how to find out who made the

purchase. Was it a new or existing customer? The former

requires you to assign them an additional value, in line

with the results from your cohort analysis.

By ingesting these data points into your biddable media,

you set yourself up to make smarter decisions. Instead of

chasing cheap revenue, you can expect your systems to

reallocate budget to high value, new customers.

Predictive CLV is time consuming. It can also be resource

heavy - not everyone has the technology providers in place,

nor the in-house capabilities to pursue it. If you’re

comfortable with cohort analysis, however, preparation for

the next stage shouldn’t be difficult:

1

2

3

Select customers who placed their first purchase

in e.g. 2019.

Add a 12 month window to each first customer

order.

Top up the total customer revenues within this

timeframe and divide it by the total number of

new customers from step one.

MAKING CLV ACTIONABLE


From Customer Cohorts to Predictive CLV

20

Many retailers struggle with the idea of switching to a

CLV-centric model. Efficiency-based metrics like ROAS

see budgets flow toward branded terms, or RLSA, as

these areas cost less and boast better conversion rates.

Adopting a long-term approach involves a leap of faith.

Retailers must sacrifice short-term revenue, and allocate

budget towards areas that just aren’t as efficient. This can

create friction in departments incentivized towards short-

term revenue targets. It requires a change management

approach that goes beyond pure marketing execution.

It’s impossible to make smart decisions if you don’t

understand each piece of the marketing trifecta

(advertising, pricing and inventory) and how they relate to

one another. But you can also expect to see more retailers

taking steps to align these channels - and focus their

whole business on a single set of mutually beneficial,

coordinated metrics.

A truly effective performance marketing strategy will be

one that makes decisions based on price

competitiveness, inventory sell-through rates and stock

levels. Marketing departments have started waking up

to new, company-wide metrics that promote true

profitability instead of individual siloed success.

WHY CHANGE MANAGEMENT MATTERS


Crealytics is a retail advertising solutions company. With a

balanced focus on customer acquisition and site

monetization, it empowers brands and retailers at all

points of their product advertising lifecycle. A worldwide

team of retail experts supports its offices in New York,

London and Berlin.

For more on CLV-centric performance, get in touch via

[email protected]

www.crealytics.com

GET IN TOUCH


Great ROAS, Terrible Results: The Case for CLV-Centric Advertising

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