IMPROVING CUSTOMER EXPERIENCE THROUGH DATA

MATHIEU ROCHE Implementation Consultant, La Redoute

COMPANY CREATED IN 1837

WEBSITE LAUNCHED IN 1994

7M UU / MONTH 10M ACTIVE CLIENTS IN 26 COUNTRIES

80%+ OF REVENUE ONLINE TOP 10 E-COMMERCE WEBSITE IN FRANCE LEADER ON FEMALE CLOTHING & HOME FURNITURE

A BUSINESS TURNAROUND PLAN BASED ON 3 CHALLENGES:

- CONTROL THE PRODUCT OFFERING THROUGH ITS OWN LABELS

- FOCUS ON DELIVERY AND CUSTOMER SERVICE

- IMPROVE CUSTOMER ACQUISITION AND RETENTION THROUGH

ADVANCED USE OF DATA

LA REDOUTE’S DATA MANAGEMENT PLATFORM

COLLECTION

SEARCH

DISPLAY

MEDIA DATA

ANALYTICS DATA

WEB SITES

& APPS

CRM DATA

3RD PARTY DATA

ACTIVATION

DSPs

CMS

E-MAILING

CRM

SEGMENTATION

UNIFIED PROFILES

DATABASE

SEGMENTATION ENGINE

APPLICATION #1: RETARGET VISITORS VIA E-MAIL

PROCESS

REDUCED RE-ENGAGEMENT TIMEFRAME FROM 24 HR TO 1 HR

MULTIPLIED POST-VISIT E-MAIL CONVERSION RATE x3

RESULTS

IMPROVE THE QUALITY AND EFFICIENCY OF POST-VISIT ENGAGEMENT TO OPTIMISE CONVERSION RATES

GOAL

DMP DATA INGESTION

Reception of La Redoute

customers IDs when they

connect to their online account

SEGMENTS CREATION

Every hour, the DMP records all

visitors IDs which have not

filled the shopping basket and

products IDs consulted during

the visit

SEGMENTS TRANSFERT

Hourly transfer of visitors IDs

who have not filled the shopping

basket to La Redoute.

La Redoute transfers these

audiences to Neolane for e-mail

retarging

APPLICATION #2: OPTIMISE CUSTOMER RE-ACTIVATION

DATA INGESTION

- Synchronise Client IDs w/ DMP

IDs through Login pages & e-mail

openings

-Ingest La Redoute CRM profiles to

the DMP

IMPLEMENT PURCHASE RECENCY SEGMENTATION IN DMP

- Create audiences of buyers

0-6 months / 7-12 months /

13-24 months / +24 months

TRANSFER SEGMENTS TO CRITEO FOR ACTIVATION

- Server-side transfer of

audiences

PROCESS

MEASURE IMPACT OF PURCHASE RECENCY ON CONVERSION RATE TO OPTIMISE DISPLAY ENGAGEMENT STRATEGIES

GOAL

IDENTIFIED 1 TO 4 PERFORMANCE DIFFERENCE BETWEEN RECENCY SEGMENTS

ENABLED CRITEO TO MANAGE REACH & FREQUENCY STRATEGIES BY SEGMENT TO OPTIMISE CPA BY 20%

RESULTS

APPLICATION #3: IMPROVE CUSTOMER ACQUISITON

USE LOOK-ALIKE MODELLING TO IDENTIFY BEST PROSPECTS TO TARGET FOR EACH PRODUCT CATEGORY

GOAL

IDENTIFY SUCCESS SAMPLE

- Track purchases on Children /

Baby clothing category for 30

days

CALCULATE PROSPECT VALUE SCORE THROUGH C-CLONES ALGORITHM

- Identify explanatory

variables using

segmentation trees to

predict purchase likelyhood

v. average

CREATE PROSPECTION AUDIENCES AND ACTIVATE THROUGH TRADING DESK

- Create complementary

audiences based on

affinity scores

- Transfer to TD’s

AppNexus seat via

server-side connection

PROCESS

Total basis

Ind. = 1 Pop. = 100%

Intensity level >=8,5

Ind. = 1,32 Pop. = 43%

Infants & children >=0,5

Ind. = 1,57 Pop. = 29%

Male =6,5

Ind. = 1,66 Pop. = 1%

Toys & games >= 11,5

Ind. = 1,49 Pop. = 2%

Toys & games

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Série1

Série2

Cumulative conversion rate evolution per UU of data segment vs non-targeted segment (Index 100= Performance of non-targeted segment):

After 3 weeks, data segment becomes less performant. A buyers profile re-modelization is needed.

Segments from decision trees perform 2.63 times betters than non-targeted ones

Cumulative conversion rate

263

100

Data segment cumulative conversion rate

Non-targeted segment cumulative conversion rate

Weeks W1 W2 W3 W4 W5

X 2,63

Global uplift targeted vs

non-targeted

X3,1 Cumulative max. uplift vs

non-targeted

APPLICATION #3: IMPROVE CUSTOMER ACQUISITON

DELIVERED 25M TARGETED IMPRESSIONS + 5M RANDOM

MESURED A 2.63 TIMES UPLIFT BETWEEN TARGET AUDIENCE AND RANDOM CAMPAIGN

WITNESS A DROP IN PERFORMANCE AFTER 3 WEEKS –NEED TO UPDATE PREDICTION MODEL

RESULTS

PROJECT PREPARATION

• Work with consultants to formalise data strategy

• Identify concrete use cases + desired project timeline

• Identify potential tech vendors

RFP PHASE

• Issue RFP to vendors

• Collect written responses and define shortlist

• Organise face-to-face presentation of shortlisted offers

TRIAL PERIOD

• Select vendor(s) for pilot phase

• Select 3 priority use case to implement during pilot phase

• Mesure performance improvement as part of use cases to build business case

ROLL-OUT

• Roll-out full DMP capabilities

(4 months)

(3 months)

(6 months)

(4 months)

IMPLEMENTING THE WEBORAMA DMP AT LA REDOUTE

BEST PRACTICES & RECOMMANDATIONS

YOUR DATA STRATEGY SHOULD BE DEFINED BEFORE LAUNCHING A TECHNOLOGY RFP

DON’T GUESS –TEST, MEASURE AND LEARN AS MUCH AS YOU CAN

THIS IS A PARTNERSHIP –PREPARE A TRIAL PERIOD TO TEST QUALITY OF SERVICE AND TECHNOLOGY

THANK YOU FOR YOUR ATTENTION

MATHIEU ROCHE Implementation Consultant, La Redoute

mroche@weborama.com