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Writer's pictureSteffan Willis

Econ Insights: Mapping Internet Usage and Skills

Updated: May 2, 2023

In this series, we look at interesting data sets to uncover hidden insights.


The 2018 Internet User Classification (IUC), created by the Consumer Data Research Centre (CDRC) provides a unique granular dataset of how people across the country use the internet.


The data classifies lower super output areas (LSOAs) into 10 categories based on the dominant form of internet use and engagement. These categories are:

  • e-Withdrawn

  • Settled Offline Communities

  • Digital Seniors

  • Passive and Uncommitted Users

  • e-Mainstream

  • e-Rational Utilitarians

  • Youthful Urban Fringe

  • e-Veterans

  • e-Professionals

  • e-Cultural Creators

The chart below shows how these categories are distributed across the UK, dark colours being associated with limited moving through to lighter shades showing higher levels of engagement.


Map of Dominant Form of Internet Use by LSOA
Internet User Classification 2018

Aside from creating beautiful maps this data can be used to perform some interesting economic analysis.


The most common group of users in rural areas are 'e-Rational Utilitarians' (red colour) who use the internet for shopping and accessing services rather than for communication or entertainment. These users are likely constrained by poor quality broadband connections.


In more isolated areas of Wales and Scotland this turns to black, any one who has spent in a cottage in Snowdonia can attest that all but the most basic services are inaccessible. What is interesting is that many of the areas with limited internet engagement are not rural but border towns with good connectivity.


The map below is filtered to only show urban areas and highlights those areas classified as having limited internet use (e-Withdrawn, Settled Offline Communities, Digital Seniors, Passive and Uncommitted Users).

Map of limited use of the internet which aligns to areas with high deprivation

Seeing this map reminded of the pattern of 'left behind' local authorities. Intrigued, I constructed a similar index based on qualifications and low skill occupations for LSOAs. Income and productivity data is not available at this level of granular detail.


The results were surprising. Filtering for the 75th percentile of LSOAs in urban areas produced an almost identical distribution.

Map of 'Left Behind' places

What implications does this have? The first is that is clearly a significant population for whom the internet is not widely used. As more services move online there is clearly a risk that these individuals become increasingly disenfranchised. The governments drive towards 'digital first' is a good example of this.


From an employment perspective, computer literacy is and will become an increasingly important aspect of many of jobs. An area which lacks these skills will be a significant disadvantage compared to more technological adept areas. These areas are already dominated by low-skill employment, without digital skills these areas are unlikely to attract the high value jobs they need to thrive.


Note: Maps created using QGIS

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