Implications for RAMS when SAARF moved to a new demographer
for the universe updates
The May RAMS 2012 release used the new 2011 population updates from IHS Global Insight
estimates. These updates, which see the adult 15+ population growing by 2.7%, had a significant
impact on the RAMS results due to the fact that there are some differences in the model they use to
determine the population profile compared to the model used by the previous demographers. The
industry should carefully examine these population changes, bearing them in mind when dealing with
changed audience results as there can be some trend-line breaks.
POPULATION UPDATE
The new 2011 population updates from the IHS Global Insight estimates have had a significant
impact on RAMS results.
In total, the 15+ population has increased by 2.7%, from 34.02-million to 34.934-million, with a
number of demographics changing because of this.
For many media, the new population estimates have affected audiences in thousands, even if
incidence does not reflect any change.
By understanding the effects of the population update, the industry will be able to get a better
understanding of what has happened to audience results.
BACKGROUND TO THE POPULATION CHANGE
The previous population update for RAMS reflected mid-year 2010 estimates supplied by the Bureau
of Market Research of UNISA (BMR). The next population update was deferred to 2012, in order to
take into account the mid-year 2011 estimates from Stats SA.
This update was implemented in the May RAMS 2012
IHS Global Insight’s demographic model differs from the previously employed BMR model in a
number of technical areas:



The cohort component model handles mortality in a different way, specifically with regard to
the impact of HIV/Aids. Specifically, the BMR model shows a greater impact.
For regional distribution, slightly different techniques are employed.
The model is checked for consistency with the economic, labour, income and development
factors of every region in South Africa.
The resultant population updates are, therefore, different to the previous population estimates for a
number of demographics.
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(2010 figures are derived from BMR population estimates, and 2011 figures are derived from IHS
Global Insight population estimates.)
SEX
While the changes in male and female proportions have not
been significant, the percentages are none the less closer
together, indicating slightly more males.
2010
2011
‘000
%
‘000
%
Male
16 113
47.4
16 879
48.3
Female
17 907
52.6
18 055
51.7
AGE
There are less 15-24 year olds in the IHS estimate. Numbers for
the 25-49 age groups remain similar, while the estimates for
50+ are higher than they were with BMR.
2010
2011
‘000
%
‘000
%
15-24
10 048
29.5
9 820
28.1
25-34
7 749
22.8
7 905
22.6
35-49
8 569
25.2
8 814
25.2
50+
7 654
22.5
8 395
24.0
Significant increase
POPULATION
GROUP
Significant decrease
Most of the population increase has come from the black
community, which has risen by over one million adults. The
number of coloureds remains similar, as has the number of
Indians. There has been a decrease in the white population by
about 300 000. Media which target these population groups may
see a difference in their audience in thousands.
2010
‘000
2011
%
‘000
%
Black
25 613
75.3
26 784
76.7
Coloured
2 942
8.6
3 006
8.6
Indian
927
2.7
936
2.7
White
4 538
13.3
4 208
12.0
Significant increase
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Significant decrease
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COMMUNITY SIZE
There have been many shifts in the classification of places.
There has been growth in the metros, and two new metros
have emerged: Krugersdorp and Germiston. Many places
have had their community size either upgraded to city/large
town status, such as Knysna and Barberton, while others, such
as Brits and Vryheid, have lost this classification.
2010
2011
‘000
%
‘000
%
$ 250 000+
11 541
33.9
12 700
36.4
$ 40 000-249 999
4 626
13.6
4 735
13.6
$ 500 -39 999
4 148
12.2
4 223
12.1
Total urban
20 314
59.7
21 658
62.0
Less than 500/rural
13 706
40.3
13 276
38.0
Significant increase;
PROVINCE
Significant decrease; $ Movement of places in urban
categories
The Western Cape, Northern Cape, Mpumalanga and
Limpopo have remained fairly unchanged in terms of
proportion to the total population. The Free State has
declined significantly, down by 100 000. The Eastern Cape is
down slightly. KwaZulu-Natal grew significantly in the
previous BMR update, and has maintained these numbers.
North-West is significantly down, by 400,000. The greatest
difference has occurred in Gauteng, which is up by 1.3million, which makes sense intuitively, as this is where the
country’s growth is.
2010
2011
‘000
%
‘000
%
Western Cape
3 524
10.4
3 556
10.2
Northern Cape
718
2.1
796
2.3
Free State
2 210
6.5
2 078
5.9
Eastern Cape
4 734
13.9
4 672
13.4
KwaZulu-Natal
7 148
21.0
7 117
20.4
Mpumalanga
2 340
6.9
2 487
7.1
Limpopo
3 752
11.0
3 724
10.7
Gauteng
6 882
20.2
8 201
23.5
North West
2 712
8.0
2 303
6.6
Significant increase
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Significant decrease
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METROPOLITAN AREA
In general, metros as a group have increased in size. All the
Gauteng metros have grown – Pretoria and Reef in
particular – with the exception of Soweto which has
declined by 100 000. Durban has maintained but there has
been a slight decrease in Pietermaritzburg as is the case for
Cape Town.
These changes could affect radio stations and other
regional media.
2010
‘000
2011
%
‘000
%
Cape Town
2 298
6.8
2212
6.3
Cape Town Fringe
332
1.0
313
0.9
PE/Uitenhage
853
2.5
885
2.5
East London
386
1.1
388
1.1
Durban
2 063
6.1
2096
6.0
Pietermaritzburg
372
1.1
317
0.9
Kimberley
133
0.4
139
0.4
Bloemfontein
317
0.9
358
1.0
Vaal
716
2.1
840
2.4
Greater Johannesburg
1 934
5.7
2127
6.1
Soweto
907
2.7
804
2.3
Reef
2 710
8.0
3365
9.6
Pretoria
1 344
3.9
1615
4.6
Significant increase
Significant decrease
In addition to the new IHS Global Insight estimates, the RAMS May 2012 release also included the
latest small urban/rural data, covering July to December 2011 fieldwork.
SUGGESTIONS ON HOW TO LOOK AT THE RAMS DATA BEARING THE NEW UNIVERSE
CHANGES IN MIND
As different radio stations have different target markets not all of them will have been affected to
the same degree by the new universe updates i.e. if a big part of your specific radio station’s target
market is white, the fact that in the new universe update whites as a group are significantly down
will influence your radio station more than one where this is not a big part of their target market.
Although the new universe profile makes it difficult to establish what movement is due to the
population changes and which are not, it is possible to see movements above and beyond those
imposed by the new demographer when users drill down into the data.
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If you look at East Coast Radio for example and you look within KwaZulu-Natal (compare province
within province as that takes care of any variation between provinces due to the new update) for the
February RAMS 2012 release (BMR figures) and the RAMS May 2012 release (IHS figures) you can
compare the universe movements for certain demographics versus the station’s movements for
these demographics.
KwaZulu-Natal
Feb Rams
2012
(BMR)
7 148 000
May RAMS
2012
(IHS)
7 117 000
Population
change
=
East Coast
Radio change
-
Population Group
%
%
Black
80.2
82.8
+
+
Coloured
1.0
1.1
=
=
Indian
10.3
9.4
=
-
White
8.5
6.7
-
-
Please note that only the Indian audience moved in a different direction to the population
changes, with the rest of the changes being in line.
From the above table we can see that KwaZulu-Natal as a province has stayed stable in the
population update, but that East Coast Radio has lost listeners
To understand what is happening, it is important to also look at the station’s profile within the
province: East Coast’s profile is only 50% Blacks, and this is the group showing growth within
KwaZulu-Natal. The population drop in White adults is impacting on East Coast’s total thousands. In
addition, there was some real decline in Indian audience.
Users should also note that when there is a universe update (whether done by a new demographer
or the same demographer) the figures in thousands that you look at may not be directly comparable
with one another. In this instance the figures for the 15+ population in total went from 34.02-million
to 34.934-million. When calculating the change from one year to another, it is extremely important
that you use the percentage figures and not the thousands as a percentage is based on the relevant
population total.
Before deciding if a station is going up or down, you should review at least three releases, although it
might take longer to understand a trend. Since the May 2012 RAMS release, there are now also a June
and August 2012 RAMS release and thus one can use three RAMS releases to see if your radio station is
declining or growing since the demographer change.
Smoothing the data helps to detect patterns within the data, while cancelling out “noise”. That is, if you
look at an average of the data, outliers or extreme incidences become moderated by the previous
releases. This can be done using a linear, or moving average equation to show an average across the
releases in Excel.
It is also very important when you compare data over a period of time to take the margin of error, or
significant difference into account. Margin of Error is the relationship between the sample and the
population it represents. It helps to determine whether a figure has changed significantly from survey to
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survey. That is, if the change has been a statistically meaningful change. For more information on how to
calculate the Margin of Error go to:
http://www.saarf.co.za/amps/calculatesignificant/Significant%20Difference%20User's%20Guide.pdf
Other aspects that users should bear in mind when comparing one RAMS release with another are
the following:
 Make sure you have not eroded your sample size with too many filters
 Look at the whole picture i.e. even if you are only interested in LSM 8-10, do a run that has
LSM 1-4, LSM 5-7 and LSM 8-10 in. This way you can look at your “target market” in relation
to the rest. In fact you might find out that your “true” target market is actually LSM 5-7 and
not LSM 8-10.
 Make sure there were no unusual events like the “World Cup Soccer” in your fieldwork
period
 Don’t just look at your station, also look at competing media and other activities
 Look at extraneous factors like a bad economic downturn
 Look at all the internal changes you have made at your own radio station, remembering that
the effect of this can be in the “system” for a long time.
For more detailed information on the “Best Practice for using RAMS Survey Data” go to:
http://www.saarf.co.za/RAMS/Best%20Practice%20Note.docx
END
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