What I did was take three important keyword phrases for our local clients, get the top 20 local results, and compare those on these factors:
For the Google local portion:
- Reviews
- Number of incidences of parts of keyword in local business listing title
- Photos/videos
- User content
- Webpages
For the destination URL:
- Inbound links
- Pagerank
- Number of pages in site
- Number of incidences of parts of keyword in homepage title tag
With all that data and my very naive statistical abilities (am I the only guy who wishes he had a statistics professor chained to a dingy, cobweb-ridden cubicle in the corner?) I created scatter graphs and found R2 values.
Unfortunately, the strongest correlation is still considered "weak" in statistical parlance. I suspect someone from Google will read this and laugh at my non-PhD-ish bafflement. Nonetheless, I know where to go next- so there will be a part two.
Strongest correlation: More reviews equals better ranking
The correlation of two important SEO factors... also weak:
Other factors and correlative values (all weak, but strongest first):
- Number of photos and videos (listed in local details): R2=0.2053
- Number of webpages (listed in local details): R2=0.1862
- Number of user content (listed in local details): R2=0.1788
- PageRank: R2=0.154
- Keyword element instances in local listing name: R2=0.079
- Keyword element instances in homepage title tag: R2=0.0011
Next up, I'm going to examine:
- More keywords for # of reviews, larger dataset to get more certain R2 value for this
- Keyword prominence for homepage title and LBL name
- Keyword integrity (whole keyword in order) in homepage title and LBL name