Google eTowns Canada Methodology

A description of the methodology behind selecting the winner of Google eTowns in Canada

STAGE 1 – eTowns Shortlist

To develop the eTowns shortlist, Ipsos assembled a list of all Canadian towns, broken down by population size. Google then added the AdWords data for each town to calculate the top five towns in each of the regions with the highest AdWords penetration relative to population size.

  1. A list of all valid zip code areas and town names was created for each region with population data for each zip code area and town.
  2. Google created an AdWords penetration figure for each region, by dividing the total population of each town by the number of AdWords customers in that region.
  3. If a town appeared in duplicate regions, the population and AdWords was aggregated and the town assigned to the region where its population was the largest.
  4. Ipsos was then asked to conduct desk research in each of the top five AdWords penetration towns in each of the 5 regions.

STAGE 2 – Business Scoring

  1. Ipsos identified a random sample of 51 small and medium businesses (employing between 1 and 50 people) in each of the top 5 AdWords penetration towns from each region.
  2. The 51 businesses were divided according to company size
    • Self-employed (1 employee) (n=17)
    • 2 to 10 employees (n=17)
    • 11 to 50 employees (n=17)
  3. The profile of small businesses in each town was quota'd according to employee band to ensure an even distribution of each.
  4. Each of the randomly selected businesses were then marked according to the following criteria:
  5. Was it listed in an online directory (such as Yellowpages, 411.ca, Yelp, manta.com, canpages)? (YES / NO)
    • Did it have its own website? (YES / NO)
    • Did it have a social network presence? (YES / NO)
    • Did its website allow eCommerce? (YES / NO) [Directly within the site, there must be a section to purchase product / service offered]
    • Did 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 did the website (if it has one) score on www.howtogomo.com? Overall score and Speed.
  6. Each answer was given a score and the scores from each business were aggregated to provide the town with a total score. The town with the highest score in each region was then awarded eTown status.
  7. Scores were calculated as below:
    • Was it listed in an online directory? (YES / NO) [If Yes=1, if No=0]
    • Did it have its own website? (YES / NO) [If Yes=10, if No=0]
    • Did 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]
    • Did it have a blog? (YES / NO) [If Yes=3, if No=0]
    • How did the website (if it has one) score on www.howtogomo.com – Overall score and speed.
      1. i Score = the score
      2. ii Speed – If >0 and =5 =3, if 0 or >5 = 0.
    • The total score was calculated by the sum of all yes/no scores +the average of the two howtogomo scores.

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