Technology Tracker
Source: data.gov.uk (2020-10-08)

The Technology Tracker started in 2004. This research measures awareness, access, use of and attitudes towards fixed and mobile telecoms, internet, multi-channel TV, and radio, among UK adults (aged 16+). 
Across the UK overall, and within each UK nation, the Technology Tracker provides detailed analysis by key population demographics, sub-region, and by urban vs. rural. It collects data that enable comparisons to be made with older data collected by Ofcom, informing Ofcom analysis, reports and decisions.

Up to and including 2014, there were three waves of research per year: from 2015 to 2017, there were two waves per year, in April and October. From 2018  there will be one wave of research per year.

The data have  been published in csv format since 2011. The datasets from 2011 to 2015 inclusive contain the chart data only: from 2016 onwards they will contain all the data from the .spss files.

1 Preface 
This volume contains the full computer tabulations for the 2014 Wave 2 Technology 
Tracker, study, which has been run by Saville Rossiter-Base on behalf of Ofcom. The 
objective of the survey is to track the attitudes and behaviour of the general public with 
respect to the residential telecommunications market as well as broadcasting more 
generally. 
Quadrangle Operations interviewed a quota sample of 2,877 adults, aged 16+, in the UK.  
Interviews were carried out across 231 different sampling points in the UK, face-to-face, in-
home.  All interviews were conducted between 12th May and 26th July 2014. 
The data are initially weighted to correct the over-representation of nations, regions and 
areas to produce a geographically representative sample.  They are then weighted by age, 
gender, social class, working status, and region to match the known population profile. 
Details of the sampling frame, research methodology, and weighting procedures are 
outlined in the following pages. A note on statistical reliability is also included. 
Sample Design 
To ensure consistency with trend data, the sample approach to sampling has been used 
as in previous waves, using Output Areas (OAs) as the basic building block for sampling, 
then using quota control by three key variables (age, gender and SEG) to control the 
sample interviewed within each sampling point.   
First Stage 
The OAs in the UK were grouped into sampling units (SUs), which were then were 
stratified by region and rural/urban: 
• firstly, all the SUs were sorted by region,  
• the SUs were then sorted within region by rural/urban.  
The sample extracted was checked for close correspondence to the UK population on two 
key variables:  
• Deprivation Index for Great Britain.  Currently there is no deprivation index for 
Northern Ireland. 
• Cable/ non-cabled area  
Since region has been used as the first sorting variable, regional distribution of SUs will be 
more or less in proportion to the number of residential addresses in each region.   
 

 
Second stage 
The size of a SU is measured by the number of addresses it contains. The SUs were 
selected with a probability proportionate to size. This ensures that all households within an 
SU have an equal chance of being selected, regardless of the size of the SU in which a 
household is situated. The number of interviews per SU was 12. 
 
Quotas 
The following quotas were set (within each SU) to represent the population within that SU, 
which means the overall quotas across the UK will closely match the UK population. 
Quotas were set using 2011 Census data for Great Britain and Northern Ireland.  
• Age (16-24, 25-44, 45+) 
• Socio-economic grade (SEG) 
• Gender 
 
Fieldwork 
Interviewers were provided with specific addresses. The average SU contains around 130 
households in England and Wales and 160 households in Scotland, thus affording tight 
control over the addresses the interviewers called at. All interviews were conducted in the 
home, using pen and paper. 
 
Reporting  
The sample is drawn on the basis of households within SUs, while quotas are set on the 
basis of adult population profiles. The data is then weighted to the profile of UK adults and 
so the data is representative of adults aged 16+.  Therefore, when reporting it is necessary 
to state that the data represents the percentage of adults rather than the percentage of 
households.  
 

 
Weighting 
The data are weighted to the national UK profile using target rim weights for age, gender, 
socio-economic group (SEG), working status, region and cable/ non-cable. The following 
table shows the initial unweighted sample and the final weighted sample profile. 
Figures are based on UK 
adults 
% Weighted 
% Unweighted 
 
Profile 
Interviews achieved  
Gender – Male 16+ 
48% 
48% 
Gender – Female 16+ 
52% 
52% 
Age – 16-34 
33% 
28% 
Age – 35-54 
35% 
32% 
Age – 55+ 
33% 
40% 
SEG – AB 
25% 
21% 
SEG – C1 
30% 
30% 
SEG – C2 
18% 
22% 
SEG – DE 
27% 
27% 
Working Status – working 
56% 
47% 
Working Status – not working 
43% 
53% 
Region – London 
12% 
9% 
Region – South East 
14% 
9% 
Region – East of England 
9% 
9% 
Region – South West 
8% 
9% 
Region – East Midlands 
7% 
9% 
Region – West Midlands 
9% 
9% 
Region – Yorkshire & Humber 
8% 
9% 
Region – North East 
4% 
3% 
Region – North West 
11% 
6% 
Region – Scotland 
9% 
9% 
Region – Wales 
5% 
9% 
Region – Northern Ireland 
3% 
9% 
Cable 
51% 
47% 
Non cable 
49% 
53% 
 
The percentages described above as ‘% Weighted’ are the targets used to weight the 
data. The figures for age, gender and location are taken from the 2001 Census. Cable/ 
non cable figures come from published data on the proportion of UK households in cabled 
areas, and SEG profiles come from NRS published data.  The ‘% Unweighted’ column 
shows the actual percentage of interviews achieved in the May/ June/ July 2014 fieldwork.   
 

 
2 Appendix A – Deprivation 
Business Geographics’ ‘Small Area Deprivation Index’ is designed to detect ‘pockets’ of 
deprivation within wards.  The deprivation index is created using a combination of socio-
economic variables.  Please note that the deprivation index only applies to Great Britain.  
The index composition score is based on the following four variables: 
1. Unemployment – unemployed residents 
2. Overcrowding – households with more than one person per room 
3. Non-car ownership – households without a car 
4. Non-home ownership – households not owning (or buying) their own home 
The deprivation index ranges from 0, equalling the least deprived, to 100, equalling the 
most deprived.  This is broken down into a high/medium/low classification for the overall 
population.  The higher the index, the more deprived the area. 
Wave 2 2014 fieldwork achieved the following break-down of interviews: 
 
GB Profile 
(SU based) 
GB Interviews 
achieved: 
Weighted 
GB Interviews 
achieved: 
Unweighted 
Low Deprivation 
(0-33.33) 
61% 
61% 
62% 
Medium 
Deprivation (33.34 
– 66.66) 
36% 
37% 
36% 
High Deprivation 
(66.67 – 100) 
3% 
2% 
2% 
 
 

 
3 Appendix B – Quotas 
The following quotas were set at the outset of the project:  
 
Adults 16+ 
Quotas set 
Interviews achieved 
May-July 2014: 
Weighted 
Interviews achieved 
May-July 2014: 
Unweighted 
Gender – Male 
49% 
48% 
48% 
Gender – Female 
51% 
52% 
52% 
Age – 16-24 
14% 
15% 
13% 
Age – 25-44 
31% 
37% 
32% 
Age – 45-64 
34% 
29% 
30% 
Age – 65+ 
22% 
20% 
25% 
SEG – AB 
23% 
25% 
21% 
SEG – C1 
31% 
30% 
30% 
SEG – C2 
22% 
18% 
22% 
SEG – DE 
26% 
27% 
27% 
 
4 Appendix C - Guide to Statistical Reliability 
The variation between the sample results and the “true” values (the findings that would 
have been obtained if everyone had been interviewed) can be predicted from the sample 
sizes on which the results are based, and on the number of times that a particular answer 
is given.  The confidence with which we can make this prediction is usually chosen to be 
95%, that is, the chances are 95 in 100 that the “true” values will fall within a specified 
range.  However, as the sample is weighted, we need to use the effective sample size 
(ESS) rather than actual sample size to judge the accuracy of results.  The following table 
compares ESS & actual samples for some of the main analysis groups. 
 
Actual 
ESS 
Total 
2,877 
2,357 
URBANITY: RURAL 
470 
374 
URBANITY: URBAN 
2,407 
1,995 
GENDER: MALE 
1,369 
1,127 
GENDER: FEMALE 
1,508 
1,230 
AGE: 16-24 
384 
320 
AGE: 25-44 
916 
765 
AGE: 45-64 
860 
716 
AGE: 65-74 
346 
283 
AGE: 75+ 
371 
307 
SEG – AB 
608 
512 
SEG - C1 
855 
704 
SEG - C2 
621 
505 
SEG - DE 
785 
652 
HOUSEHOLD INCOME: UNDER £11.5K 
497 
407 
 

 
HOUSEHOLD INCOME: £11.5K-£17.5K 
366 
298 
HOUSEHOLD INCOME: £17.5K-£29.9K 
336 
269 
HOUSEHOLD INCOME: £30K+ 
402 
345 
WORKING: YES 
1,345 
1,146 
WORKING: NO 
1,518 
1,271 
ETHNIC ORIGIN: WHITE 
2,626 
2,133 
ETHNIC ORIGIN: EMG 
244 
193 
PERSONAL DISABILITY: ANY 
555 
433 
PERSONAL DISABILITY: VISUAL 
102 
83 
PERSONAL DISABILITY: HEARING 
114 
88 
PERSONAL DISABILITY: MOBILITY 
202 
170 
MOBILE PHONE USER 
2,615 
2,151 
INTERNET ACCESS AT HOME 
2,287 
1,892 
 
The table below illustrates the required ranges for different sample sizes and percentage 
results at the “95% confidence interval”: 
Approximate sampling tolerances applicable to percentages at or near 
these levels 
 
Effective sample size 
10% or 
90% 
± 
20% or 
80% 
± 
30% or 
70% 
± 
40% or 
60% 
± 
50% 
± 
2,357 (All respondents) 
1.2% 
1.6% 
1.9% 
2.0% 
2.1% 
1,127 (Male) 
1.8% 
2.4% 
2.7% 
2.9% 
3.0% 
704 (SEG C1) 
2.3% 
3.0% 
3.5% 
3.7% 
3.8% 
374 (Rural)  
3.1% 
4.1% 
4.7% 
5.1% 
5.2% 
 
For example, if 30% or 70% of a sample of 2,357 gives a particular answer, the chances 
are 95 in 100 that the “true” value will fall within the range of + 1.9 percentage points from 
the sample results. 
When results are compared between separate groups within a sample, different results 
may be obtained.  The difference may be “real”, or it may occur by chance (because not 
everyone has been interviewed).  To test if the difference is a real one – i.e. if it is 
“statistically significant” – we again have to know the size of the samples, the percentages 
giving a certain answer and the degree of confidence chosen.  If we assume “95% 
confidence interval”, the difference between two sample results must be greater than the 
values given in the table below to be significant: 
 
 
 

 
Differences required for significant at or near these percentages 
Sample sizes being  
compared 
(sub-groups or trends) 
10% 
or 
90% 
± 
20% 
or 
80% 
± 
30% 
or 
70% 
± 
40% 
or 
60% 
± 
 
50%     
± 
1,127 v 1,230  (male vs. female) 
2.4% 
3.2% 
3.7% 
4.0% 
4.0% 
512 v 704 (SEG AB vs. C1) 
3.4% 
4.6% 
5.2% 
5.6% 
5.7%