Turning Data into Value: Case Studies in ROPO (Research Online Purchase Offline) and LTV (Lifetime Value)

David BoothFounding & Senior Partner, Cardinal Path

Percent of CMOs reporting underpreparedness

Percentage of projects using marketing analytics in companies

Data & Analytics Maturity

Balanced growth enables value

In plan, in budget, top down support

In plan, in budget, top down support

How can we better allocate media spend?How can we better

allocate media spend?

Add CRM, media & analytics data

Add CRM, media & analytics dataInternal staff, hire

specialist agencyInternal staff, hire specialist agency

Clear project plan, deliverables & phasesClear project plan,

deliverables & phases

Existing stack, clean the data, SAS

Existing stack, clean the data, SAS

Traditional approach

Cost/Lead Volume Lead Value Value Cost ROI

Online - Search $4.00 400 $10.00 $4,000.00 $1,600.00 150%

Online - Display $5.75 300 $10.00 $3,000.00 $1,725.00 74%

Offline - Outdoor $9.00 100 $10.00 $1,000.00 $900.00 11%

Offline - Print $7.00 350 $10.00 $3,500.00 $2,450.00 43%

Offline - TV $6.50 700 $10.00 $7,000.00 $4,550.00 54%

But all customers are not the same…

Customer data

Average selling price, frequency, etc…

Who can STAY a customer (churn)?

Just like coffee drinkers…

…not all students provide the same value

All students add value…but some add more than others

7%60% of revenue 29% of

students

40% of revenue

71% of students

29%

71%

Who are these students?How can we attract more of them?

Who are these students?How much are we spending to acquire them?

“Sticky” Students “Risky” Students

Often women, – Live in higher income zip codes– Maintain >= 3.0 GPA– AU= Masters and/or Doctorate

degree– BM= Diploma– AU Age =(>23) – BM Age =(>30)

These students are:– 44% more valuable from a LTV

measure because:– they are 68% less likely to churn

Often younger (<23) – Live in lower income zip codes– Near the ground schools– Associate and/or Bachelor degrees

(AU & BM) – Struggle to maintain > 2.0 GPA

These students:– Account for a greater proportion of

revenue leakage– Often do not make it out of year 1

GPA

Days Enrolled 1 2 3 4

30 99% 92% 64% 23%

60 98% 91% 62% 21%

90 98% 90% 60% 20%

180 98% 88% 54% 16%

270 97% 85% 48% 13%

360 96% 81% 41% 10%

540 94% 72% 30% 6%

720 90% 60% 20% 4%

Increasing GPA

Incr

easi

ng T

enur

e

Modeling & predicting churn

Influencing factors can be modeled

Female

Age (+)Doctorate

Master

Zip Income (+)

Legal

Health

Media Arts

Education

Behavioral

CertificateBusiness

DiplomaAssociate

Bachelor

Male Demo

Degree

Program

Location

But we’ve got great conversion rates!

Target young, low income, close to campus!

…and you’ll target your least valuable students

Optimize media for the RIGHT audiences

Research Online, Purchase Offline (ROPO)

You’ve got to show data to get more budget!

You’ve got to show data to get more budget!

How can we demonstrate that

we’re driving offline sales?

How can we demonstrate that

we’re driving offline sales?

Online > Offline intent modeling

Online > Offline intent modelingInternal staff, hire

specialist agencyInternal staff, hire specialist agency

Tried & true data science techniquesTried & true data

science techniques

POS/in-store, GA Premium, Doubleclick, BigQuery, ETL,

POS/in-store, GA Premium, Doubleclick, BigQuery, ETL,

Broken link…

Digital investment short-changed

Over-inflating contribution of

offline sales staff

Media mix decisions misguided by

inaccurate data

>25% of the valueof digital media

was hidden

The approach

Google Analytics

Premium

Doubleclick DCM

BigQuery

Leveraged powerful tools to ingest

massive data sets from multiple

sources

Cleaned, joined, and reduced data to

create one seamless report

Scripts to allow for monthly processing

Extract, transform, load

AutomateTools Data

Governance & scope bridges gaps

EDW GA Premium3rd – Party

Sales ReportingData

FullConsumerJourney+ + =

Using data to drive ACTION:

over 50%

True depiction of customer behavior across channels enables:

• Media mix optimization & modeling• Better forecasting models• Adjustment of staff compensation models

http://bit.ly/USCellular

Re-classification of

of activations formerly classified as offline-sourced

Start with a basic assessment

bit.ly/oammbit.ly/oamm

Thank you!Questions & answers

+Dave Booth@davidabooth