in SEO Tips and Tricks - 22 Mar, 2018
by proseo - no comments
An Advice to help get better rankings on local search results

Local SEO services offer a very targeted online marketing approach, (it’s not like dropping off brochures on front-porch steps or paying for an ad in a local newspaper that may or may not be seen by a potential customer that is actually interested in your products or services). Local SEO companies allows you to position your business on search engines and other digital marketing platforms so you’re seen by potential customers — on their terms.

What kind of results did we get?

The most important factors

The overall most important factors showed to be the following variables: Profile connected with G+ (in this case the correlation was the strongest), Web profile and Number of ratings. The correlation between the variable Ranking and two other variables – Number of citations and Web profile showed to be of very low statistical significance reaching the value of 0.05.

Therefore the formula for the calculation of position is as follows:

Ranking = 4.33 – 0.001 x Number of citations – 0.73 x Web profile

Correlation between the three variables showed to be of low statistical significance reaching the value of 0.10. At the same time we also took into consideration the possible dependencies between the explanatory variables and decided to add the following explanatory variables into our model: Keyword in name, Number of citations, Rating – number of stars and Web profile.

Therefore the formula for the calculation of position is as follows:

Ranking = 4.33 – 0.001 x Number of citations – 0.38 x Key word in name – 0.73 x Web profile.

For the regressive analysis we used a lineal regressive model which we have created following these steps:

  1. Backward elimination – we added all the independent variables into the model and then taking into account the significance of their regressive coefficient, eliminated the insignificant ones.
  2. Forward elimination – we started adding variables accordingly to their p-value from the test of significance of regressive coefficient.
  3. Maximum R-squared improvement – in this step we added variables with the maximum value of determination coefficient. Model with two explanatory variables showed to be the most suitable for the purpose of our research.
  4. Additionally, we also added variables which correlation with the variable Ranking was statistically significant, reaching the value of 0.10. We added the following explanatory variables: Keyword in name, Number of citations, Rating – number of stars and Web profile.

We collected and analyzed Google local results data to find the answer. Working with statisticians from the University of Žilina,  we evaluated a sample of 308 search results from 42 different searches and estimated a model that would best suit our data.

Our dependent variable was the position in the search results. Additionally, we chose the factors often presented in SEO articles as important ranking factors in local searches, to serve as possible explanatory variables.

local search results

Numeric variables

  • how many times are company’s contact details such as address and telephone number mentioned on the web just like on Google+ (Number of citations)
  • how many times is company mentioned on the web but without the telephone number
  • how many +1s has company on its Google+ profile (Number of +1s on Google+)
  • how many followers company has on Google+ (Number of followers)
  • how many ratings company has on Google+ (Number of ratings)
  • how many stars has company in its ratings on avarage (Rating)

Binary variables (yes/no being the only possible values)

  • whether company is verified in Google (Verified company)
  • whether company has a key word or so called dummy variable in its name (Key word in name)
  • whether company has any photos added to its profile (Photos)
  • whether company has a description with relevant keywords (Relevant description)
  • whether it has set the right category – for example plumbers for plumber (Right category)
  • whether it has its profile connected to Google+ (Profile connected to Google+)
  • whether it has a Google maps profile (Web profile)
  • whether it has set the “publisher” connection to Google+ (Google+ connected to web)

The keywords on which we chose to perform the searches served as so called dummy variables. Value 1 was assigned to searches with connection to key words and value 0 to those not connected to the chosen keywords. These are some of the phrases we have tested: bed and breakfast London, sushi Wien, bistro Bratislava, pâtisserie Lyon, kaviareň Košice…and somewhere

The set of measurements was divided into two parts based on the values of “Web profile” variable. This variable gains the value 1 for companies with a local web profile from Google maps (107 companies) and value 0 for companies without such profile (201 companies).


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