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Customer Lifetime Value in Digital MarketingDATA restart, 22. 4. 2016Pavel 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)

% o

f Tot

al P

rofit

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

RevenueValue 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 activitiesSeeing 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 dataFuture 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

MaleUSER ID123456 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