PAMS BRANDS PEOPLE, PRODUCTS, PLATFORMS

BROUGHT TO YOU BY SOUTH AFRICA’S FUSION LEADERS

THREE FUSED STUDIES GIVE YOU TRIPLE THE INSIGHTS

TODAY'S PRESENTATION

Welcome by the CEO

The PRC Fusion Journey

Fusion Overview and PAMS BRANDS recap

Nielsen Digital PPP Study

Examples of the power of the data

WELCOME BY THE CEO

THE SA FUSION JOURNEY

2013 FUSION MODEL – HUB AND SPOKE

Radio surveyProducts and brand survey TV panel

Readership survey

OOH survey

Online survey Ambient media Future media

Establishment survey

Intermedia comparative data

2017

CPS 2018

Ø AutomotiveØ Banking Ø CellularØ Retail (FFF)

2018/19 FUSION ACTUAL – CHAIN

Ø Actual audited purchasesØ 52 weeks yearØ Over 3,000 FMCG brands

2018PAMS BRANDS

PPP 2019

PAMS BRANDS PPP

2019Ø TV, Print, DigitalØ Devices/MediaØ By daypart

2020 FUSION FUTURE – LINKS ADDED TO CHAIN

CPS 2020

PAMS BRANDS

2020

PAMS BRANDS PPP

2019

2019

APRIL JULY OCT

PAMS BRANDS MULTI2020

++

FUSION OVERVIEW AND PAMS BRANDS RECAP

FUSION METHODOLOGY FOR THE NEW MILLENNIUM

Data Fusion is the process of integrating multiple data sources by using common variables to match two or more datasets at the respondent level and create one unified database

Fusion reduces the cost and technical difficulties in capturing all the data of interest in a single-source survey

Bringing previously separate media assets together for the most granular view of People’s behaviour across media Platforms, and Product consumption

FUSION HOW IT WORKS

We start by looking for linking variables (fusion hooks) between the 2 sets of data:

READS SUNDAY

TIMESHEAVY

MAGAZINE READER

BANKS FNB

SHOPS ONLINE

OMO LIGHT

TASTIC EVER

POWERADE

GENDER

ETHNICITY

AGE

LOCATION

INCOME

OCCUPATION

EDUCATION

SEM

LANGUAGE

DRIVES TOYOTA

NO MEAT BRANDS

VARIABLE GROUPS CELLSAGE 4 4 GENDER 2 8 OCCUPATION 8 64 ETHNICITY 4 256 EDUCATION 6 1 536 LANGUAGE 9 13 824 INCOME 6 82 944 SEM 10 829 440 LOCATION 9 7 464 960 BEHAVIOURAL 7 52 254 720

FUSION MADE POSSIBLE BY THE RISE IN COMPUTING POWER

Gordon Moore of Intel popularised the saying that computer power will double every two years.

• Intel 4004 had 2,300 transistors in 1971

• Intel 8086 had 29,000 transistors in 1978

• Intel 80486 had 1,000,000 transistors in 1989

• Intel Pentium had 21,000,000 transistors in 2000

• Intel Core i7 had 2,270,000,000 transistors in 2010

• Apple A13 bionic 8,500,000,000 transistors in 2019

The transistor count on chips has shown this exponential growth since the 1970s.

PAMS Set 1: (Base) Demos & publication

title readingby platform

CPS Data Set 2: (Donor)

FMCG brandconsumption

PAMS BRANDS Set 3: (linked)

Demos & publication title FMCG consumption by platform

FUSION HOW IT WORKS

Statistical analytics and modelling in order to create a single data set that incorporates the attributes from both

Data Set 4: PPP (Donor)Nielsen Digital Study

PAMS BRANDS PPP Set 5: (multi-links)Publication title/retail brands/FMCG

and digital usage by daypart

FUSION THE SAME AS SINGLE SOURCE – BUT WAY MORE DATA

PAMS BRANDS (PAMS 2017 & NIELSEN CPS 2018)

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URBAN HOUSEHOLDS ARE AUDITED TWICE A MONTH, RURAL HOUSEHOLDS ONCE A MONTH

Household Panelof 4000

Demographically & Geographically

representative of all SA Households

Actual Audited Consumption

(not claimed) of HH’s FMCG usage across all

retail outlets

(Remember TAMS is 3000)

New brands are automatically picked up with new incidence

PAMS BRANDS

WHAT CPS PANELLISTS DO

Panel members purchase their FMCG goods and take

them home.

1

At home they record their purchases in their barcode diary. Documenting when they shopped, where they

shopped and each individual item they purchased.

2

Once they have recorded a product in their diary, they

take the corresponding Nielsen barcode sticker and

attach it to the product purchased beside the actual

barcode. This is so the auditor can later cross-

reference the product with what is recorded in the

panellists diary.

3

The panellists keep their till receipts for the auditor,

product packages are then either stored in the pantry or

disposed of in a Nielsen dustbin. The auditor uses

packaging to verify the information collected in the

barcode book and vice versa.

4

WHAT CPS AUDITORS DO

Auditors go to the panellists diary and scan all items that have been recorded as purchased since their last visit.

1

They check that all items on the till slips have been recorded.

2

They check the pantry to cross-reference the information provided in the diary, and to ensure nothing has been excluded from the read.

3

They use their handheld scanner to immediately send all of the information they collected back to Nielsen.

4

They cross out the product barcode and the diary barcode on all products they have scanned to ensure they won’t be scanned again in future.

5

They then go through the panellists rubbish bin to check their discarded packaging.

6

AUDITED ACTUAL VS. CLAIMED

If the AMPS paper product diary leave behind was accurate, how come over 35 manufacturers each year have purchased Nielsen audited CPS

data at around R2M per category for the past 20 years?

QUESTION:

ANSWER:

A diary is not worth the paper it is written on. It is claimed purchases, based on the

fallible memory of one HH purchaser, over a single week, on a limited number of advertised brands, with over 50 pages

completed hurriedly at the last moment.

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RELATIVE DIFFERENCE IN NUMBER OF BRANDS BOUGHTBY CATEGORY SG5 VS. SG1

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RELATIVE DIFFERENCE IN NUMBER OF BRANDS BOUGHTBY CATEGORY SG5 VS. SG1

Source: PAMS Brands 2018

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SEM PROFILE BY CPS CATEGORY

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- DR

INKI

NG

FRES

H CR

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ENSE

D M

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SPRE

ADS

- FIS

H AN

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EXTR

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FLAV

OU

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MIL

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ROAT

LOZ

ENG

ES /

DRO

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- CAN

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CAST

OR

/ ICI

NG S

UGAR

COND

ITIO

NER

S - R

INSE

OFF

INST

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MAS

HCH

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- SP

ECIA

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ET S

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- LI

QU

IDDI

SHW

ASHI

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OW

DER

/ RIN

SE A

IDRI

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FLAV

OUR

EDCH

EWIN

G G

UMAD

HES

IVES

(GEN

ERAL

)SH

AVIN

G P

REPS

SG 1

SG 2

SG 3

SG 4

SG 5

Source: PAMS Brands 2018

SEM PROFILE BY CPS CATEGORY

Heavy Users

NIELSEN DIGITAL PPP STUDY & FUSION

The study was conducted in South Africa from September to November2018.

THE NIELSEN DIGITAL STUDY

A sample of 1,104 past month online users aged 15 years and above was captured; using an online survey methodology. Participants were sent an email and invited to complete the online survey; via any connected device.

Quotas were set based on key demographic variables, to ensure a sample representative of the past month online population was obtained. These were set for age, gender, population group and province. In line with the online profile, the sample was largely metropolitan/large urban.

THE NIELSEN DIGITAL STUDY

The data provided has been weighted to IHS population estimates, in order to deliver a complete representative sample.

The study focuses on the online population. There is no analysis of the behaviour or profile of consumers who do not use the internet.

IndonesiaMalaysiaPhilippinesSouth KoreaThailand

BelgiumBrazilGreeceItalyMexico

EAST WEST

NetherlandsSpainSouth AfricaUkraineUK

15 Markets

MARKETS SURVEYED

45%

SMARTPHONE COMPUTER TABLET

48% 7%

TYPES OF DEVICES USED

MaleFemale

15 – 2425 – 3435 – 49

50 +

Eastern CapeFree StateGauteng

KwaZulu-NatalLimpopo

MpumalangaNorth West

Northern CapeWestern Cape

GENDER AGE PROVINCE

BlackColoured

Indian/AsianWhite

POPULATION GROUP

TARGET QUOTAS

Demographic % Quota

MaleFemale

49.2150.79

541559

15 – 2425 – 3435 – 4950+

29.4933.4325.0911.99

324368276132

BlackColouredIndian/AsianWhite

74.179.353.47

13.01

81610338

143

Province % Quota

Eastern Cape 10.81 119

Free State 4.71 52

Gauteng 31.32 345

KwaZulu-Natal 17.44 192

Limpopo 7.85 86

Mpumalanga 7.03 77

North West 5.64 62

Northern Cape 1.64 18

Western Cape 13.55 149

UNWEIGHTED SAMPLE

2PRODUCTS

3PLATFORMS

Banking

Automotive

Cellular

FMCG

TV

Print

Digital

RadioRetail (FFF)

WHAT DO YOU GET IN THE FUSION

1PEOPLE

SEMs

LSMs

Demos

Geos

LSMsSEMs DEMOS

LSM groupsLiving Standards

Measure

SEM groupsSocio-Economic

Measure

Demographic audience profile

PEOPLE

Financial Institution

Main Bank Credit Cards

Where accounts or cards are held

Which bank Personal usage

11Financial

Institutions

11Banks

FINANCE

Number of Vehicles

Person Ownership/

UsageVehicle Brand Vehicle

Obtained In household

Own or company carPersonally driven New or second-hand

56Vehicle Brands

AUTOMOTIVE

Number of cellphones

Personal ownership

Type used most often

Network provider

In household Own or use Ordinary feature

smartphone

VodacomCell C

TelkomMTN

CELLULAR

Food and Grocery

Furniture and Appliances

Fashion Store Cards

12 Stores

22 Stores

25 Stores

RETAIL OUTLETS

Categories Brands Usage200 Categories >3000 Brands Heavy, medium, light

consumption

FMCG

TVStandard Live TVTime-Shifted TVOTT/Streaming

(Netflix/YouTube/ShowMaxetc.)

RadioRadio Live Listening

Radio Online Streaming

DigitalInternet usage

Social MediaDevices/AppsTech in Home

PrintNewspaper/Magazines

PaperDigital

Different devices and media throughout the day (a day in the life)

PLATFORMS

EXAMPLES OF THE POWER OF THE DATA

“THE PROLIFERATION OF DIGITAL DEVICES AND PLATFORMS ISDRIVING THE MEDIA REVOLUTION AND RENDERING OBSOLETE THESILOS OF TRADITIONAL MEDIA STRATEGY.”

This artwork was created using Nielsen data.

Copyright © 2019 The Nielsen Company (US), LLC. Confidential and proprietary. Do not distribute. 9

Digital Consumer Survey 2019 Report

“THE MEDIA LANDSCAPE IN SOUTH AFRICA MAY HAVE CHANGEDINEXORABLY, BUT TO SKETCH THE DIGITAL LANDSCAPE, TO THEEXCLUSION OF OTHER TRADITIONAL MEDIA

PREMATURE.”PLATFORMS, IS

Digital Consumer Survey 2019 Report

This artwork was created using Nielsen data.

Copyright © 2019 The Nielsen Company (US), LLC. Confidential and proprietary. Do not distribute.24

WEIGHTING AND UNIVERSE NOTE

• When using any of the categories/brands in PAMS any weight can be used

• When using any of the categories/brands in PAMS BRANDS use HH weight

• When using some of the questions in PPP you should use a matched universe i.e. code past month internet access

WAYS TO WATCH TV/MOVIES THESE DAYS

SOURCE::PAMS BRANDS PPP 2019

ONLINE SOURCES AND SERVICES FOR TV/MOVIES

SOURCE::PAMS BRANDS PPP 2019

37 21 31 39 48 53

19 10 16 20 26 28

15 9 12 16 21 22

11 6 9 12 15 14

8 5 7 7 911

4 2 3 4 4 7

2 1 1 2 3 42 1 2 2 3 3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total Super Group 1 Super Group 2 Super Group 3 Super Group 4 Super Group 5

YouTube Netflix ShowmaxGoogle play movies Other BitTorrent Amazon Prime video

TIME SPENT PER WEEK ON THE INTERNET BY DEVICE

Total SEM SG 1 SEM SG 5 BMW / Merc Standard Bank Woolworths

31h 20MIN 34.42 30.43 27.13 29.28 32.29

5H 41MIN 6.16 5.17 4.02 5.25 5.54

14H 56MIN 17.24 13.23 11.45 13.29 14.05

Computer

Smartphone

Tablet

10H 44 MIN 11.02 12. 03 11.25 10.34 12.29

SOURCE: PAMS BRANDS PPP 2019Past Month Online Universe

ACTIVITY BY PLATFORM BY DAYPART

21% 14% 13% 10% 8%

11%9% 10%

8% 9%

26%27% 24%

22% 23%

13%16%

13%11% 10%

15% 22%22%

25% 30%

14% 13% 18% 25% 19%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

BEFORE 9 9H00-15H00 15H00-18H00 18H00-22H00 AFTER 22H00RADIO

ONLINEONLINE

ONLINE

PRINTED

TV

LISTENING

READING

VIEWING

11

TOTAL ADULTS (ONLINE UNIVERSE)

222

SOURCE: PAMS BRANDS PPP 2019Past Month Online Universe. Activities aggregated and profiled. Reading is News and Magazine only

ACTIVITY BY PLATFORM BY DAYPART

20% 14% 13% 9% 8%

12%10% 10%

9% 10%

26%27% 24%

21% 22%

13%16%

13%11% 11%

15% 21%23%

26%31%

14% 12% 17% 23% 17%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

BEFORE 9 9H00-15H00 15H00-18H00 18H00-22H00 AFTER 22H00RADIO

ONLINEONLINE

ONLINE

PRINTED

TV

LISTENING

READING

VIEWING

11

CAPITEC (ONLINE UNIVERSE)

222

SOURCE: PAMS BRANDS PPP 2019Past Month Online Universe. Activities aggregated and profiled. Reading is News and Magazine only

TYPES OF PROGRAMMESWATCHED VIA THE INTERNET

SOURCE: PAMS BRANDS PPP 2019Past Month Online Universe

WATCH TV AND USE THE INTERNET AT SAME TIME

SOURCE: PAMS BRANDS PPP 2019Past Month Online Universe

Total SEM SG 1 SEM SG 5 Mr Price Edgars WoolworthsOnline

retailer e.g. Superbalist

Daily %Col 39 43 33 42 38 37 29Almost every day %Col 28 29 28 27 29 28 33Several times per week %Col 14 11 14 14 14 12 16Once per week or less %Col 12 9 14 10 10 13 10Never %Col 8 7 11 7 8 9 11

Desktop Computer %Col 5 4 5 5 5 4 2Laptop/Notebook %Col 12 11 16 12 12 11 13Smartphone %Col 59 61 54 60 59 60 59Tablet (e.g. iPad) %Col 7 7 6 6 7 5 2

QUALITY OF ATTENTION – READERS ARE FOCUSED

SOURCE: MEDIA ENGAGEMENT STUDY 2017 N=3000

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JOSEPHINE BUYS

Unit 8 Burnside Office Park 410 Jan Smuts Ave Craighall JHB South Africa

+27 11 326 4041 +27 82 604 5940 www.prc.za.com josephine@prc.za.com