Customer Data at De Persgroep. Luc Verbist CIO De Persgroep

Customer Data

at De Persgroep

Luc Verbist CIO De Persgroep 10 – 10 – 2013

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De Persgroep

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Marketing B2C

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Strategy

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Architecture

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Privacy

Agenda

NEWSPAPERS

Activities

N°

1

Activities

MAGAZINES

N°

1

Activities

Print products

Activities

RADIO

Activities

TELEVISION

Activities

DIGITAL

Classified

Sites

E-commerce

iPad &

mobile

News

Pay-per-view

Activities

MOBILE TELEPHONY

Cellphone

Operator

Financial Results

(Mio €)

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De Persgroep

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Marketing B2C

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Strategy

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Architecture

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Privacy

Agenda

Marketing B2C

As Is

Clustering Segmentation

James Bond Movies 65.000 in 5 weeks Cooking Books 135.000 on 1 day DVD players 35.000 on 1 day

Reactions not logged Operational processing

Social Media not followed No logging

Surfers or behaviour Behavior on App

 not logged

To Be

Mass Marketing + Micro/Individual Marketing

To Be

1.200.000 Customers 11.000.000 Prospects 1.400.000 Deliveries/day 10.000 Calls/day 11.000.000 Prospects 2.000.000 Marketing deliveries/year 10.000 Tweets/day titels 100.000 Tweets/day customers 120.000.000 Pageviews/day

Marketing B2C

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De Persgroep

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Marketing B2C

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Strategy



Architecture

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Privacy

Agenda

CRM strategy for DIGITAL (focus on traffic building) CRM strategy for PRINT (focus on recruitment) Little synergy

1. Integrated strategy for print and digital on the basis of a uniform view of the consumer in all its relationships with a title.

2. To map Recency and Frequency of reading habits in each channel.

3. Infer / clustering interest according to preferences for different categories (region, sports, politics…)

Opportunities :

Readers Marketing:

Readers recruitment

Upsell and cross-Sales

Conservation

Reduce churn

Advertising use:

More targetted campaigns

Personalize ads

Multi channel campaings

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De Persgroep



Marketing B2C

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Strategy



Architecture

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Privacy

Agenda

Architecture

Challenges :

 Multiple data sources

 Multiple formats

 No or different Unique Identifiers

 Speed of operation is essential

 Huge volumes of data

 Manage Operational cost

 Moving data requires (some) technical expertise

 No real standards defined

Architecture

Active Newspaper Subscriptions Online Customers & Prospects Newspaper Subscription & Payment History Customer & Prospects Contacts Integrati on Data Custo mer Consumer Behaviour Interests aggregates External Data Data Cleansing, Quality check, Enrichment Subscriber Communication History Digital Newspaper downloads Website visits Newsletter subscriptions

Architecture

Business rules :

 How to identify/recognize a unique human being

 Matching algoritm Windowkey Pattern Co m pa ny N am e G ender _Initi al s Fi rs t N am e Las t N am e Str ee t H o us e N r B us N r Zi p C d Lo cat io n Em ai l Bi rth Dt Tel N r G sm N r V at N r A bo n Id NAW

100/101 First + Last + Address + Email E E E E E E E

First + Last + Address + Email F F F E E E E

110/111 First + Last + Address E E E E E E

First + Last + Address F F F E E E

120/121 Initial + Last + Address + Birthdate E E E E E E E

Initial + Last + Address + Birthdate E F F E E E E

130/131 Gender + Initial + Last + Address E E E E E E E

Gender + Initial + Last + Address E E F F E E E

Email

140 Email + First + Last E E E

Email + First + Last F F E

150 Email + Initial + Last E F E

160 Email + Birtdate E E 170 Email + Abon Id E E 180 Email + Gsm Nr E E Gsm Nr 190 Gsm Nr + First + Last E E E Gsm Nr + First + Last F F E 200 Gsm Nr + Last + Initial E E 210 Gsm Nr + Abon Id E E Tel Nr 220

Tel Nr + First + Last E E E Tel Nr + First + Last F F E

Architecture

Business rules :

 Assign quality levels to data

 Use specialised software or services (e.g.Trillium)

 Use exact and fuzzy matching algoritm

 What level of correctness is required? (Pareto)

Architecture

A H _G B C F E D ...

Federation of companies : enriching & correcting data Starting from the data strenght of each company

Strategy

 Deduplication and identification a real tough job.

 Handling massive volumes is something your staff needs to learn.

 Involve experts (from outside your company).

 Nothing is perfect yet in de Big Data market.

 Hard to justify the project as you can not predict tangible benefits upfront.

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De Persgroep

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Marketing B2C

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Strategy

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Architecture

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Privacy

Agenda

Privacy

Quid Privacy legislation?

Personal data = any information of any type relating to an

identified or identifiable natural person.

Data must be processed fairly and lawfully and be up to date

Privacy

Quid Privacy legislation?

Purpose Limitation : Specific, explicit and legitimate

Formalities Prior notification Belgian Commission for the

Protection of Privacy

Privacy

What is the risk?

Reputation

Future data protection rules in EU : 2% of annual ww turnover

Sanctions : administrative, criminal, civil and damage

Privacy

Quid Privacy legislation?

DP wants * highest possible transparency to consumer and his data * possibility of control and adjustment to own data

 Project My Account

Privacy

Quid Privacy legislation?

Non-intrusive questions or polls reveal more about a person than he/she realizes. What kind of swim shorts do you prefer?

Your choice reveals a lot about your age.

Q&A

Luc Verbist CIO De Persgroep [email protected]