Big Data - from hype to reality

Dr. Richard Benjamins

Director Business Intelligence

Telefonica Digital

Big Data –

From hype to reality

Telefonica

Digital

© 2013

2Telefonica Digital

The hype remains

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is getting more and more crowded

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“Data-driven” pays off, but it is hard to get there

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Privacy remains an issue

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PI EconomyBig Data for other businessBig Data to optimise

your business

How can businesses play in the Big Data space?

Different “business” models with different maturities and different risks

Leverage data to

understand and

improve business

(x/up sell, churn)

and products

Data = improved

business

Recognize that

digital data is

delicate (privacy)

Turn that into an

opportunity

Data = risk =

business

Insights that help

improve

businesses and

governments

Data = business

Leverage data for

targeting users

with relevant ads

and higher CTR

and conversion

Data = better

advertising

Telefonica Dynamic Insights

Smart cities

Improve

services

AdvertisingAccess to

insights

Become a

gatekeeper of

personal data

7Telefonica Digital

Big Data to optimise Telefonica Digital’s

business• Traditionally, insights from data are generated in a fragmented way across the organisation,

limiting the quality of decisions

• There is an “easy” opportunity to create a more integrated view of customers, products and

markets, leveraging Open Data as well

Analyst reports

Macro KPIs, markets

Social media DWH

Campaigns & Sentiment

analysis

Business KPIs

Network

data

Network KPIs

Strategy

dept.

Marketing

dept.

BI

dept.

Network

dept.

Report 1 Report 2 Report 3 Report 4

From a fragmented view on markets and

products

Open Data

Analyst reports

Social media DWH Network

data

Big Data Platform

One consolidated

view

To an integrated view based on

internal data of P&S, social

media, network data, analyst data

and Open Data

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Deliver Big Data in your organisation –

become data-driven

From To Considerations

Multi-million up-front

investments

Pay as you grow • Legacy systems?

• Agile progress

Focus only on large

business cases

Allowing exploratory self-

serve

• Skills, culture

• Tools to empower

Central Distributed

Self serve

• Skills

• Culture

Data as an afterthought Data by design and by

default

• Culture

• Process

Expensive on demand

data capture

Data as the rule • Provider contracts

• Process

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....made betterBig decisions…..

1st product – “Smart Steps” for Retailers:

• Decide on store location

• Understanding store performance vs footfall

• Plan local marketing campaigns and track their impact

• Optimise resource planning – staffing/open hours

Smart steps, for retailers

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Retailers have questions...

I know the activity that

goes on inside my stores.

But what % of my target

market is walking past

outside? What is the

opportunity that I am

missing?

I am a large supermarket

owner and one of my

competitors has opened up

down the road. I need to

identify our battleground.

Where is my competitor

strongest and weakest? Where should I locate

my new store?

Where should I target loyalty

or acquisition marketing

campaigns? Where are my

customers coming from?

I need to manage my resources.

When are my peak times? Could I be

operationally more effective if I

changed my opening times?

Strategic Decisions

Performance Management

Retailers worry about …


Smart steps

Telefonica

Dynamic InsightsGfk

Mobile Behavioural Patterns Consumer Data Assets

Smart Steps


39

%

39

2G Network

3G Network

900 MHz

1800 MHz

2100 MHz

2013 4G Network

NETWORK DATA

The o2 mobile network has hundreds of cells to measure the trends in

footfall across the country


PRIVACY

ANONYMISATIONBefore Telefonica Dynamic Insights (TDI) receives the data, all

personal information is removed. The data TDI receives are

cryptographically hashed values

AGGREGATION

The hashed values are aggregated into groups, i.e. gender & age

band. At this stage there are only crowds of o2 customers

EXTRAPOLATIONWe take our sample and extrapolate to population totals, using

mathematical algorithms. This gives us the grouped values Smart

Steps uses.

A 3 step process


39

%

39

Easier to use

Further

protecting

anonymity

Extrapolated to

represent local

population

200 x 200 GRID

Footfall is rendered into 200 x 200 metre grid squares across the country


Example question of a marketer

COUNT

What are the profiles of the

people in the area of my store?

How does the footfall in our

area change throughout the

day?


Differential aspect

Export data and

combine with other

sources

Today’s data tomorrow.

Fastest data delivery in

the market

Insights 24/7/365. Data

every hour, day, week

and month. You choose.

Intuitive web tool

covering the whole of

the UK to draw insights

from

Eliminates retailers’

blind spots. The profile

of the footfall in their

area

Vast sample base

based on observed

crowd behaviour

Technology

Big Data - from hype to reality