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Customer Lifetime Value
in Digital Marketing
DATA restart, 22. 4. 2016
Pavel Jašek (@paveljasek)

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CLV:
The Holy Grail
of Customer Centricity

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“ Customer centricity is a strategy that
aligns a company’s development and
delivery of its products and services with the
current and future of a select group of
customers in order to maximize their long-
term financial value to the firm ”

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Focusing on profitable customers
% of Total Customers (sorted by profit)
%ofTotalProfit
ID 123
When there is a large heterogenity in your customer base
in terms of profits that your customers bring you or
losses you can count, you need to focus on selecting
such segments. Create a Pareto chart like this using
Tableau.

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“ Customer Lifetime Value (CLV) is the
present value of the future (net) cash flows
associated with a particular customer “
“ Customer Equity is the sum of customer
lifetime values across a firm’s entire
customer base“
noca.cz/clvbook

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When a telco company acquires a customer,
cash flow for next 2 years is easily predictable

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When an e-commerce acquires a customer,
how can you predict future profit?

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How easily can you predict customer behavior?
History Present Future
Customer 1
Customer 2
Customer 3
Transactions in the learning period

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E-commerce settings
Focus on end customers (B2C)
Non-contractual settings
Non-membership status
Always-a-share (vs. lost-for-good)
Continuous buying
Variable-spending environment
Partial identification possibilities

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Google Analytics only helps you to focus on top
purchases and their traffic sources

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Reports of lifetime value in Google Analytics serve
its own purpose
support.google.com/analytics/answer/6182550?hl=en

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How does CLV look like in reality?
For each customer you typically estimate lifetime profit
(discounted in following years).
I’ve found out that for better actionability it is useful to
estimate profit for some shorter term: ¼ to 3 years. This
should be selected depending on the nature of business
when your customer have high probability of
repurchasing.
Also, you typically calculate CLV each month/week/day in
order to see how your predictions evolve.

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Your monthly calculations for each
customer. Naturally, CLV models
change when customer purchases and
“fade out” the value when the customer
is inactive.

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Levels of CLV that you might use
Trend of exact values: 107 CZK → 123 CZK
Current exact value: 123.45 CZK
Bucket: CLV High (3000+ CZK)

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The simplest way to estimate CLV:
sum up profits by acquisition cohorts
Gross Profit for all customers

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Easy way to estimate simplifications
https://life-time-value.appspot.com/

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Can you choose CLV as your KPI?
CPA
ROAS
Profit
Revenue
Value Optimized
ROI and Total
Profit Optimized
Conversions
Cost Optimized
PNO
(CtRR, ERS,
COS)
Conversions
Cost Optimized
Long term
Profit
Customer Equity
Customer Lifetime Value
Optimized (CLV)
Can you manage and optimize CLV
directly? Or do you need to speak in
terms of CPA and ROAS with your
advertising platform?

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Simplifications of
marketing activities
Seeing all touchpoints
Attribution of conversions and costs
Word of mouth and referrals
Cross-environment behavior
(cross-device, omnichannel)
External and indirect effects
Individual campaigns vs. portfolio
approach
Simplifications of
customer data
Future incremental purchases
Past behaviour of a customer
(new customer?)
Variable spending
Volume of sales
Averages vs customer heterogeneity
Data in the right moment
At each step, you come across many simplifications

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When a path is the goal
P | alive
Monthly or annual repurchase rate
Ratio of new customers
Ratio of profitable customers
Number of customers with annual profit of 1000+
You can benefit from customer centric
KPIs while not talking directly about
CLV. Don’t hesitate to start with
examples like this at first phase.

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Areas where online marketers
can benefit from CLV

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Main areas where online marketers
can benefit from CLV
Theoretically:
➔ Customer Acquisition - Expansion - Support - Retention
➔ Direct Campaigns
➔ Customer Intelligence (CRM, managerial reporting)
Ideas of use cases like those mentioned on The Wise Marketer, on Econsultancy
and Custora are nice, but lack details.

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1) Customer Acquisition
How much can we afford to pay for a new customer? What is the true value per
acquisition? Should that influence CPA / ROAS targeting?
What products drive higher CLV?
How fast can we estimate CLV for a fresh user/customer?
When can we compare CAC and Historical Profit + CLV?

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Kevin Hillstrom
There is a direct correlation
between annual repurchase rates
and the length of time you are
willing to wait for payback.
http://blog.minethatdata.com/2015/10/lifetime-value.html

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2) Customer Expansion
For what segments of customers should we increase/decrease marketing
activities (/costs)? When?
When can we push marketing efforts on fresh customers?
What is the impact of (up|x)-selling on CLV?
What less profitable customers should we remove from mailing?
What if CLV estimation rises?

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3) Customer Support
Should we give a customer a gift or an exclusive deal?
Who can (not) be given a discount?
Who should wait in a queue for a support?

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4) Customer Retention
How much can we afford to pay to retain a customer and still being profitable?
What to do when CLV estimation drops?
How to treat customers with low or negative CLV?
Should we give incentives when CLV rises?

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5) Evaluate Direct Campaigns by change in CLV
Decide which customers by CLV to select for a campaign.
Can we get top 10% customers by CLV?
Use ratio of CLV as max costs per campaign.

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6) Customer Intelligence and managerial reporting
of your customer base
Where will high profits come from? What are profit drivers?
How well can we forecast sales?
How does CLV/Customer Equity evolve? For various companies, markets,
customer types, segments of customers.
What activities can you do to support the growth?

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2 examples of acting upon CLV

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Actionability concerns
Reporting vs. optimization
Using the data: support of bidding mechanisms
Having the right technology platform for all of it
Is there an opportunity for incremental conversions?

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Step 1: Store GCLID upon conversion
Step 2: Predict CLV using tools like the
Google Prediction API
Step 3: Upload conversion to AdWords
using Offline Conversion Import based
on GCLID (using CSVs or API)
Step 4: AW Auto-bidding optimizes bids
based on CLV
$ - Sale or Sign-up
Prediction of CLV
A) Optimize for Lifetime Value using Offline Import

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Offline Conversion Import
1
2
Create a CSV with Conversion Value of CLV, paired to a gclid.
Try uploading the CSV

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In AdWords, you then can get a custom column of imported conversions.
It is recommended to start with a separate value, i.e. not including this metric in
Conversions.

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Target ROAS bidding strategy (simple example)
Current ROAS: 6.67 (Revenue = 1,000,000, Cost = 150,000)
Sum of CLV_12months: 350,000 (of incremental gross profit)
Expected 12 months ROAS: 9.00 (+35%, Revenue = 1,350,000, Cost = 150,000)
You can calibrate target ROAS by -35 % to 4.33 and estimate the reach of the
same or even higher revenue.

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Read more about Offline Conversion Import
https://support.google.com/adwords/answer/2998031?hl=en
and learn how to optimize it via API
https://developers.google.com/adwords/api/docs/guides/importing-conversions
More about target ROAS auto-bidding strategy
https://support.google.com/adwords/answer/6268637?hl=en

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B) Google Analytics CRM Integration
CRM Visitor
ID: 123456
Loyalty
● Lifetime Value: High, $100k
● Gender: Male
● Visited Store on 3/15/16
Male
USER ID
123456
High
Customer uploads CRM data using CRM
Visitor ID as join key via a csv file, API or
Measurement Protocol
3 Remarketing list is defined in GA based on CRM imported user attributes and exported to
Adwords/DoubleClick
Customer generates CRM Visitor ID and sends
it to GA via Custom Dimension (or utilizing
User ID) during site visit
1 2
pred_CLV High

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Act on CRM User Insights, e.g. CLV bucket
Step 1: Create user segments based on the integrated
CRM data
Step 2: Compare the performance of, i.e. loyalty-
targeted campaigns across members
Step 3: Optimize campaign targeting and bidding
Step 4: Use GA remarketing for robust CRM-linked
audiences retargeting (RLSA, GDN)
pred_CLV High
Segment: High CLV

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tl;dr
1. When you care about long-term profit,
go for the pure CLV!
2. Act on CLV by importing it into your marketing
solution and calibrating performance targets.
3. Target ROAS, RLSA and GDN remarketing are
your actionable friends.

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Additional reading
For managerial overview of CLV and Customer Equity, read Peter Fader’s book on
Customer Centricity. It is thin and recommended.
If you want to start with modeling of CLV, read Gupta’s article (PDF) and study
Bruce Hardie’s notes. For e-commerce, start with Pareto/NBD (if you use R, there
is a package Buy 'Til You Die).
Find out more about Pavel’s research project http://clvresearch.github.io/public/

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jasek@google.com
@paveljasek