Google eTowns Methodology

There are around 2,000 towns in the UK. The first step of the research was to filter the number of towns using Google AdWords data and population size of towns within each to calculate which towns had the highest penetration of AdWords relative to population size.

The author(s)

  • Adam Sheridan Creative Excellence, UK
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STAGE 1 – AdWords short-list

There are around 2,000 towns in the UK. The first step of the research was to filter the number of towns using Google AdWords data and population size of towns within each to calculate which towns had the highest penetration of AdWords relative to population size.

  1. The UK was first split into: Scotland, Wales, Northern Ireland and then nine regions within England, North East, North West, Yorkshire and The Humber, East Midlands, West Midlands, East of England, London, South East and South West.
  2. A list of all valid postcode area/town names was created for each region with population data for each postcode area/town.
  3.  An AdWords penetration figure is created for each postcode area/town by dividing the number of AdWords customers into the total population of each town within each region.
  4.  If a town appears in duplicate regions the population data and AdWords are aggregated and the town is assigned to the region where its population is biggest. (e.g. Romford in the UK could appear in ‘London’ or ‘East England’ and would be assigned to wherever the majority of the Romford population live).
  5. Very small towns; those with less than 25 AdWords customers and a population smaller than 10,000 are removed from the list
  6. This provides the shortlist of the top five towns by AdWords penetration within each region.

STAGE 2 – Business Scoring

1. Using business lists covering each of the 60 short-listed towns we identified a random sample of 50 small and medium businesses (employing between 1 and 50 people) in each of the top 5 AdWords towns from each region.

2. The 50 businesses were divided according to company size 

  • Self-employed (1 employee)
  • 2 to 10 employees
  • 11 to 50 employees

3. The profile of small businesses in each town will be quota'd according to employee band to ensure an even distribution of each

4. Each of the randomly selected businesses was then marked according to the following criteria

  • Is it listed in an online directory? (YES / NO)
  • Does it have its own website? (YES / NO)
  • Does it have a social network presence?  (YES / NO)
  • Does its website allow eCommerce? (YES / NO) [Directly within the site, there must be a section to purchase product / service offered]
  • Does it have a blog? [This can be a page within the company’s website OR a page on a blogging site e.g. Tumblr / blogspot]
  • How does the website (if it has one) score on www.howtogomo.com? Overall score and Speed.

5. Each answer is given a score and the scores from each business are aggregated to provide the town with a total score. The town with the highest score in each region is then awarded eTown status
Scores were calculated as below:

  • Is it listed in an online directory? (YES / NO) [If Yes=1, if No=0]
  • Does it have its own website? (YES / NO) [If Yes=10, if No=0]
  • Does it have a social network presence? (YES / NO) [If Yes=5, if No=0]
  • Does its website allow eCommerce? (YES / NO) [If Yes=7, if No=0]
  • Does it have a blog? (YES / NO) [If Yes=3, if No=0]
  • How does the website (if it has one) score on www.howtogomo.com – Overall score and Speed.
    i Score = the score
    ii Speed – If >0 and <=5 =3, if 0 or >5 = 0.
  • The total score is calculated by the sum of all yes/no scores +the  average of the two www.howtogomo.com scores

6. The winning town per region is that with the highest sum of business scores as calculated above.

The author(s)

  • Adam Sheridan Creative Excellence, UK

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