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The Best Review Citation Sources in Canada and the UK

By | Data | No Comments

Hot Dang! It has been 6 months since I published my list of the best US review citation sources – 6 months it took me to get to this. Crazy.

You may remember, in January I caught the data bug, and put together a list of review sources based on these buggers:

scraped citations

These are sources where one’s business data has appeared, and Goog has matched the data up to this Google+ Local listing. Note: while I will call them review sources, in many cases, there were NO reviews to be found. So, we know, when it comes to local data Google finds valuable, the don’t discriminate at the review level, NOR at the type of site level. In fact, some sites they scraped were just plain shady. You’d almost think Google likes spam… 😉

A quick review of how we arrived at this data/list, we, in this order, AND NOT MANUALLY (thank god!):

  1. Pushed a button, did a jig (possibly several), and watched our scraper do…
  2. Applied, where possible, a close to as, city specific proxy
  3. Opened up maps.google.ca (or .co.uk)
  4. Conducted a search for [cityname, state/province/etc] + [category] ie. Vancouver, BC plumbers
  5. Opened up the top ten ranked listings on the first 3 pages (30 listings per query)
  6. scraped occurrences of properties appearing in “reviews from around the web.”
  7. Ranked ‘em like a boss

Note, this, like our previous study, was based on the category list found in David Mihm and Darren Shaw’s study. These guys are an endless source of inspiration. Follow them here and here.

Okay, so let me elaborate on the last item (Ranked ‘em like a boss), as it brings everything together. We ranked our UK and Canadian data by assigning 1 point to a property every time it showed up in the first 3 pages of places results. We did this to get a baseline for how popular each property is with the search engines. This is how we did it in our previous research.

Okay, you’re bored stiff. Without further ado, after having analysed nearly 250,000 listings, I give you our lists:

Best Canadian Review Citation Sources

directory
points
urbanspoon.com2413
tripadvisor.com2379
tripadvisor.ca1811
canpages.ca1226
monavis.ca1121
booking.com908
yellowpages.ca804
yahoo.com760
foursquare.com671
n49.ca594
homestars.com557
hotels.com458
tripadvisor.co.uk448
hotelscombined.com446
superpages.com446
weblocal.ca439
giftly.com386
pageinsider.com383
theblurb.ca350
insiderpages.com344
merchantcircle.com320
411.ca282
destinia.com265
restaurantica.com259
dealerrater.ca240
pagespan.com233
goldbook.ca222
pageglimpse.com213
ourfaves.com209
venere.com183
demandforce.com183
vetratingz.com176
tripadvisor.in162
citysearch.com151
foodpages.ca143
restaurant.ca142
opentable.com126
virtualtourist.com117
expedia.com116
dexknows.com106
tastegenius.com102
priceline.com102
dine.com101
aol.com97
greatschools.org97
dealerrater.com97
yellowpages.com97
giftrocket.com93
canadianhotelguide.com91
tripadvisor.com.au90

This list didn’t surprise me much at all, and overall, I think it is a pretty well balanced list. Tripadvisor is always a big one. Qype too, but it didn’t make the top 50 in this case. Things get a bit more interesting in the top 100, and even beyond. Like my US research, there are tons of outliers you’d NEVER think to submit to – nor would your competitors 😉

Want 500+ more killer, Canadian review citation sources?

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Top UK Review Citation Review Sources

directory
points
thomsonlocal.com11417
qype.co.uk7218
tripadvisor.com3290
booking.com2585
tripadvisor.ca2473
tripadvisor.co.uk2055
yell.com1948
laterooms.com1678
allagents.co.uk964
destinia.com896
enjoyengland click resources.com870
foursquare.com851
toptable.com837
freeindex.co.uk770
fancyapint.com721
bizwiki.co.uk686
urbanspoon.com668
cylex-uk.co.uk642
beerintheevening.com636
tripadvisor.in636
venere.com616
londontown.com549
viewlondon.co.uk509
qype.ie351
pageinsider.com345
thebestof.co.uk343
pageglimpse.com322
restaurant-guide.com308
allinlondon.co.uk306
1golf.eu306
tilllate.com290
tripadvisor.com.au273
here.com261
yahoo.com249
hotels.com237
referenceline.com233
hotelscombined.com226
pagespan.com226
cosmotourist.com225
whatsonhere.co.uk208
touchnottingham.com198
wahanda.com188
touchlondon.co.uk187
viewmanchester.co.uk167
trivago.co.uk157
timeout.com157
whatclinic.com150
viewbirmingham.co.uk150
hardens.com146
scotsman.com142

Looking back on this, I think I would try and categorize the types of properties. For example, break up all the hotel related ones, all the restaurant related ones. I think in my next iteration I will. For the time being, you are going to have to do a bit of digging yourself. Fortunately, I have laid it out fairly simply for you, so it shouldn’t be too hard to identify which are specific to you. Finally, it’s worth mentioning, that even if you don’t quite “fit in” on a property, that doesn’t mean you won’t get reviews there, and it certainly doesn’t mean it isn’t a valuable citation source.

Want 500+ more killer, UK review citation sources?

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What the heck would I want UK or CAN data for? Give me US data! Get, get, GET IT!

QUESTION: Suppose we opened up our tool to you, so you could perform these searches and uncover the best review citation sources in your area/niche…Is that something you’d be interested in? Let us know! If we get a good response, we may just pick you as our beta tester : )

BluMihmShaw Day 1: Some Local Data For Your Dome

By | Data | No Comments

Oops! It appears my commitment to the last Thursday of each month (aka BluMihmShaw Day) escaped me. While I had all the data long ready to go, I spent my week focusing on collecting and correcting the data from an earlier post. Rats!

The data I have for you today is very simple. It’s all about these:
scraped citations

You will remember, the above are properties that Google has scraped, and places on the Google+ Local page -near the bottom. Not long ago I did a <a href="http://www.leanmarketing useful source.ca/lean-top-50-best-local-citation-sources-in-the-usa/” >bit of research, though I am afraid it was a bit backwards.

You see, these properties that Google is scraping are important. I knew that before I did the research. Google, above all other properties, chose to scrape these websites. While I can only make assumptions for the “why”, I knew, based on working in the space long enough, that there was connection between these, and rank. The more the better I was sure. And so, without digging around to see if there was any connection between how many you had and rank, I scraped all the damn properties Google had, and told you which ones, in which markets, and in which cities stuck out most. Because I think they are darn important. Here is the data in case you missed it.

Now, I only realized that this was backwards once Darren Shaw brought it to my attention. Quick note: you will hear me reference Darren a lot because more often than not, before and after publishing/researching any data, I consult him. Between me and you, he’s a local data whisperer. When I brought this previous data to him he said something like “cool, but so what?” I nearly died. I don’t recall how many hours I spent pulling that data, but my heart was broken. He was right though. How does he know these properties mean anything? What proof is there that Google scraping them is a positive thing? None. Eff!

And so, I said to Darren, “I’ll Be Back!! I’m Not Done With You!”

Here’s the proof. Sort of*.

The only way that I could think of that might tell me if Google scraping these things influenced rank at all was: IF on page 1 for any given local term there were more scraped properties than page 2, and page 2 had more than page 3, etc. As it turned out, as I predicted, and anyone with half a brain could have predicted, my assumptions were correct. Here are the numbers:

Page 1: 13,975
Page 2: 12,361
Page 3: 11,703

We scraped Google+ Local listings in 55 cities and 71 industries. If you assume there was 10 listings on each page (we conducted our searches in maps.google.com), and we went back 3 pages then we scraped 117,150 listings. One point was assigned to every property found scraped, for example, in the above picture, that would count at 3 points, which was all be pooled into three totals: page 1, 2 and 3. The totals are as follows:

Now, I said “sort of” above because while this tells us that that listing with more scraped properties tend to have more choice rankings, it does not prove anything. I cannot tell you that if you submit to the properties most commonly found scraped in my previous research, and they get scraped you will rank better. While there is probably some truth, this data does not prove that.

So, I will let you interpret it in whatever way you wish, and do with it what you will.

I however will be making sure that I my clients, at the very least, are all submitted to these properties 😉 But that’s just me.

Am I crazy? Let me know below.

Where do we go from here? Well, my next step is collect some of these properties for our UK and Canadian friends, as I only focused on the US last time. Once those are published, I may do a couple popular niches. Fortunately for me, I have built a tool that collects this data for me, and so gone are the days where we do this manually. With a bit more work, I just may open this to you guys. If you wish you have first dibs, please register to our newsletter, so I can keep ya in the know – I will need a few beta testers!!

Finally, thanks to Phil Rozek’s valuable input, our next BluMihmShaw Day will be about CATEGORIES! Stay tuned!